proceeding of 2nd national soil workshop

Transcription

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Publication
Serial
No.
00167-177/2014/2015
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PROCEEDINGS OF THE SECOND NATIONAL SOIL
FERTILITY RESEARCH WORKSHOP
Celebrating International Year of Soils 2015
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Soil Science Division
Sponsors for the Second National Soil Fertility Research Workshop
1.
2.
3.
4.
5.
Soil Science Division, NARC, Khumaltar, Lalitpur, Nepal
Soil Management Directorate, DoAD, Hariharbhawan, Lalitpur, Nepal
CYMMYT, South Asia Regional Office, Kathmandu, Nepal
IRRI, Country Office, NARC Building, Kathmandu, Nepal
BTC Private Limited, BTC Complex, Kupandole, Lalitpur, Nepal,
Email: info@btcnepal.com, URL: www.btcnepal.com
Proprietor: Narendra Goel (Scientific Instrument Supplier and Service Provider)
6. Divya Organic Fertilizer, Mangalpur-9, Chitwan (Proprietor Mr. Narendra Giri)
Celebrating International Year of Soils, 2015
PROCEEDINGS OF THE SECOND NATIONAL
SOIL FERTILITY RESEARCH WORKSHOP
March 24-25, 2015
(10-11 Chaitra 2071 B.S.)
Kathmandu, Nepal
Editors
Dr. Krishna Bahadur Karki, SSD, NARC
Dr. Bhaba Prasad Tripathi, IRRI, Nepal
Dr. Ramita Manandhar, MoAD, Nepal
Mr. Bishnu Hari Adhikary, SSD, NARC
Dr. Shree Prasad Vista, SSD, NARC
Government of Nepal
Nepal Agricultural Research Council (NARC)
Khumaltar, Lalitpur, Nepal
June, 2015
© 2015 by Soil Science Division, NARI, Nepal Agricultural Research Council
Second National Soil Fertility Research Workshop
Organizers: Soil Science Division, National Agricultural Research Institute
(NARI), Nepal Agricultural Research Council (NARC),
Soil Management Directorate, Department of Agriculture (DoA)
CIMMYT, South Asia Regional Office (SARO), Kathmandu,
Nepal
IRRI, Kathmandu Office, Nepal
Theme:
Healthy soils for a healthy life
Venue:
NARI Hall, National Agricultural Research Institute (NARI),
NARC, Khumaltar, Lalitpur, Nepal
Date:
24-25 March, 2015 (10-11 Chaitra, 2071)
Published by: Soil Science Division, National Agriculture Research Institute
(NARI), Nepal Agricultural Research Council (NARC),
Correct Citation: Karki KB, BP Tripathi, R Manandhar, BH Adhikary and SP
Vista. 2015. Proceedings of the Second National Soil
Fertility Research Workshop, 24-25 March, 2015. Soil
Science Division, NARC, Khumaltar, Lalitpur, Nepal.
ISSN 2392-4942
Printed at:
Siddhartha Printing Press, Lalitpur, Nepal
Layout and Computer Design: Rashila Manandhar K.C, Soil Science
Division, Khumaltar
ii
Foreword
Plant nutrients are the key factors for attaining food and nutrition security. Inadequate
and unbalanced use of chemical fertilizers and less use of organic and green manures
are the main causes of nutrient deficiencies especially in South Asia. Farming system
intensification requires an adequate flow of nutrients to the crops and their greater take.
Micronutrient deficiency complexities in crops are being increasingly reported
resulting into malnutrition and in-born deformities in human being.
To mark the “International Year of Soils, 2015”, Soil Science Division under NARC,
Soil Management Directorate under DoA, CIMMYT and IRRIjointly organized the
"Second National Soil Fertility Research Workshop"which provided a great
opportunity for scientists, extension professionals and students involved in soil and
allied sciences to discuss the soil related problems and find the solutions for the benefit
of farming communities. The workshop was alsoa valuable platform for sharing ideas
and experiences for addressing nutrient problems in soils, plants and human health.
I am grateful to all the institutionswho contributed for organizingthe workshop. I
specially appreciate the tireless efforts made by Mr. Bishnu Hari Adhikary and the
team for successfully organizing the workshop and bringing out the proceedings in this
form.Thanks are also due to the members of the editing committee for their valuable
time. Ialso thank all the participants for their active interaction during the technical
sessions.
I believe that the scientific messages included in this proceedings will be beneficial to
the extension personal, students, researchers and farmers involved in the agricultural
research and development endeavors in Nepal and throughout the world as well.
I wish for the continuity of such workshops in the future.
YR Pandey, PhD
Executive Director, NARC
Patron, Workshop Organizing Committee
iii
iv
Message from the First Chief Soil Scientist
The Chief,
Soil Science Division, Khumaltar.
Having come to know about the celebration of “International Year of Soils, 2015” by
Soil Science Division, Khumaltar by organizing a two-days Second National Soil
Fertility Research Workshop, my happiness has reached beyond limitations. I feel quite
honoured in remembering me on such auspicious occasion by the organizing
committee. At the very outset, I would like to thank and congratulate organizing
committee for inviting in such a grand celebration. I am sorry to say that due to my
health condition, I am unable to attend the Workshop.
Development of our nation solely relies on Agriculture and Soil is the basis of
Agricultural development. I wish all scientists to come forward and make it success in
the days to come. Soil is the basis of our life and therefore, let us all contribute in
proper management of our soil (Mato hamro jiban ko aadhar, tasartha garau yesko
uchit shyhar)
Thank you
Bidur Kumar Thapa
Ex Chief Soil Scientist, Soil Science Division, Khumaltar
And, Joint Secretary (Retired), Ministry of Agriculture,
Government of Nepal.
The 24th March, 2015
v
vi
Preface
This book of Proceedings is the outcome of the Second National Soil Fertility Research
Workshop that was held in Khumaltar, Lalitpur from 24-25 March 2015. We were
inspired to organize this Workshop by Mr. Dhruva Joshy, ex- Executive Director,
NARC and ex-Chief Soil Scientist Dr. Krishna Bahadur Karki which was held after 17
years. This Workshop was organized as a part of the celebration of “International
Year of Soils 2015”. The objectives was to establish the status of current soil fertility
research knowledge and identify future research needs related to plant nutrient, their
proper management and develop climate change smart technologies in Nepal. The
main focus of the Workshop was to develop soil science strategies , and the
participation of the researchers and scientists concerned with the human nutrition and
plant-soil interactions served to make the Workshop a truly inter and intra-disciplinary
event. The major objectives of the Workshop were to review and present the findings
of Soil Science research and development technologies related to Soil Science.
Similarly, the workshop aimed to identify issues and opportunities related to soil
research and scaling-up of the findings and recommendations.
Workshop was inaugurated by Hon. Minister Mr. Hari Prasad Parajuli, Ministry of
Agricultural Development. We are very grateful to Dr. Bharatendu Mishra, Member,
National Planning Commission for chairing as a Special Guest in the opening
ceremony. Altogether 65 abstracts of papers were received, published and distributed
of which 1 key note address, 4 thematic lectures and 44 general research articles were
presented during the Workshop. Both oral and poster sessions were organized. Two
National Chief Soil Scientists (retired) and one Principal Scientist from IRRI,
Philippines were awarded. Similarly, three best posters were also awarded during the
Workshop ceremony.
This book is the compilation of the research articles presented in the oral and poster
sessions of the workshop. Forty nine scientific papers were received from the different
authors across the country and abroad and the organizing committee decided to publish
them after peer review of the articles by the editors, and this book of Proceedings has
been published in this form. I want to acknowledge and extend my sincere gratitude to
Dr. KB Karki, Dr. BP Tripathi, Dr. Ramita Manandhar and Dr. SP Vista for their hard
work in editing the manuscript. We believe that the recommendations and wayforward included in this book will be beneficial to the scientists, researchers, students,
extentionists and other related stakeholders involved in the field of Soil Science
research and development. The organizers hope that the content of his book will
provide a humble contribution by generating farm income and improving livelihoods
and wellbeing of the farmers of Nepal.
Thank you.
Bishnu Hari Adhikary
(Chief Soil Scientist)
Co-ordinator, and Member Secretary,
Second National Soil Fertility Research Workshop.
vii
viii
Inaugural Address
by
Mr. Hari Prasad Parajuli
Chief Guest, and Minister, Ministry of Agricultural Development
Government of Nepal
Respected Chairman,
Special Guest, Member of NPC
Officiating Secretary, Ministry of Agricultural Development (MoAD),
Distinguished Scientists, Journalist, Ladies and Gentlemen
It is indeed a matter of great pleasure for me to get this opportunity to participate and
inaugurate Second National Soil Fertility Research Workshop. I am quite fortunate to
be with great Soil Scientists of Nepal and abroad. At the very outset, I would like to
thank organizing committee (NARC) for inviting me as a Chief Guest in such a Grand
Workshop.
Mr. Chairman, Ladies and Gentlemen
We are all aware about the importance of soil and its conservation. We are all actively
involved in doing research and developmental activities. Government of Nepal is also
actively contributing to manage and maintain agricultural production and productivity
as per the need and situation. Our major concern should probably focus on our issues
and effort we are doing to make it meaningful. We must seriously analyze whether
these so far developed technologies are helpful for enhancing agrarian livelihood or
not. Vigorous discussion among technocrats must be done over developed
technologies. Technological inputs for various crop productions have been developed
so much but till date only few technologies have been put into practice. Everyone must
be aware about the importance of soil. I feel, Nepal has in general six types of soils
based on mineral composition. Some soils have reserved calcium where others have
more iron but equally they are rich in organic matter. Under such circumstances, we
must focus on what to add to the soil to make it more productive. In general, we always
recommend adding all nutrients to attain higher production which simultaneously
accelerates the cost of production and most often the production cost become
expensive to the growers resulting uncompetitive in the market. Scientist must bear in
mind all aspects of production at micro level. One of our old saying says, “Every drop
of water makes an ocean and every grain of food makes a granary”. They have the
ability to analyze situation at micro level and they have been advising us from
generation to generation. They simply lack macro level vision. So as a tradition, we
also lack the analytical aptitude. If we could critically analyze it and make it result
ix
oriented then only farmers’ livelihood will be enhanced and we can proudly say that
our contribution has helped the needy people and the nation. We all must be proud to
say that till date we are all continuously contributing for our growers and nation.
Though my knowledge is limited, I have been trying to update my knowledge
regarding technological innovations from workshops, conference, dialogue and
discussion. Since all of you are scientists, you are all equipped with plenty of
knowledge; the only lacking in you is meaningful and serious expressions. Expressing
your knowledge will definitely accelerate the technological interventions in Nepal and
abroad. I hope this two days Workshop will highlight all such technological
innovations that will reflect the identity of Nepalese Scientist at National and
International arena. Let the world feel that Nepalese Scientists have the ability to
critically analyse situation from different aspects to derive meaningful, dynamic and
reasonable conclusions.
Finally, I hope this Workshop will discuss soil science related technologies in Nepal
and provide guidelines for future studies. At last I would like to thank all the
participants for your active participation and look forward to suitable recommendations
of the technologies. I like to thank organizer of this Workshop for giving me
opportunity to share my views and I wish this Workshop a grand success.
Thank you.
Hari Prasad Parajuli
Minister
Ministry of Agricultural Development
Government of Nepal
24 March 2015
x
Welcome Address and Highlights on Objectives of the Workshop
by
Sambhu Prasad Khatiwada
Director of Crops and Horticulture (NARC)
Mr. Chairman, The Executive Director (NARC)
Chief Guest, Hon’ble Minister Sri Hari Prasad Parajuli, Ministry of Agricultural
Development, Dr. Bharatendu Mishra, Hon’ble Member of National Planning
Commission; Joint Secretaries from MoAD, Dr. Yubak Dhoj G.C, Director General,
DoA; Distinguished Guests, Ladies and Gentlemen!
It is my pleasure to have this opportunity to participate and welcome you all in the
inaugural function of this Second National Soil Fertility Research Workshop. We are
also celebrating International Year of Soils, 2015 which tend us to be gathered in one
place to celebrate the Soil Year 2015. I want to welcome the Agriculture Minister Mr.
Hari Prasad Parajuli for your presence and inauguration of this workshop. I also want
to welcome all the Joint Secretaries, MoAD and Director General Dr. Yubak Dhoj GC,
DoA for the presence in this Inaugural ceremony. I welcome to all the ex-Executive
Directors of NARC, Director from DoAD and NARC and to all the participants and
journalists of this workshop.
Mr. Chairman
The major objectives of the workshop are set as follows:
1. To review and present the findings of soil science research and development of
technologies related to soil science.
2. To identify issues and opportunities related to soil research and scaling up.
3. To make recommendation for future research and dissemination.
4. To facilitate interaction among stakeholders for collaboration and networking.
Soil Science Division (NARC) is organizing Second National Soil Fertility Research
Workshop after full 17 years. I would like to welcome all the co-organizers Soil
Management Directorate, DoAD, CIMMYT-SARO and IRRI-Nepal to contribute and
participate in the workshop. I believe that technical papers that are going to be
presented in this workshop might be helpful and will be documented and published in
the proceedings in near future. We all know that soil is the basis of life. Healthy soils
can produce healthy crops and it is only possible with adequate plant nutrient
management and healthy environment. We know every harvest removes large amount
of nutrients from the soil causing nutrient depletion. Nutrient management is a major
xi
issue to be addressed to understand the reasons for decline in yields. Soil acidification,
soil erosion, carbon emission, crop intensification and so many other factors are the
cause of low productivity. We have to protect and nourish our soils.
Finally, I hope that this workshop will discuss on different aspects of soil fertility
management technologies generated by the scientists and researchers and identify
major soil fertility related problems and carry out studies for its management in the
future. At last, I am sure that this workshop will give a forum for the researchers,
scientists, planners and policy makers to discuss and draw a valuable conclusion to
sustain the production and productivity for the long term perspective through adequate
and appropriate soil fertility technologies generation. At last I would like to welcome
you all again for your active participation.
Thank you.
xii
Vote of Thanks
Respected chairman; Chief Guest Honorable Minister, Ministry of Agriculture
Development; Honorable member of National Planning Commission; Officiating
Secretary of Agri. Development Ministry Mr. Shyam Kishor Sah; NAST Vice
Chancellor Dr. Jibraj Pokharel; Joint Secretary, Mr UC Thakur, Yogendra Karki, and
all Joint Secretary of MoAD; Director General, Department of Agriculture
Department Dr. Yubak Dhoj G.C.; Dr. BP Tripathi from CIMMY; NARC ED; DDG
and Directors from DoAD and NARC; NARC Division Chiefs, Dr. Dipak Rijal, Libird; distinguished participants, Ladies and Gentlemen.
It is my great pleasure to be with you in this morning for the opportunity to extend my
thanks for your valuable participation in this Second National Soil Fertility Research
Workshop. We are celebrating International Year of Soil 2015. In this occasion Soil
Science Division (NARC) feel pleasure and is highly grateful to you all. I believe that
your presence at the moment and contributions to the workshops keeps a great value
for all of us. Theme and policy paper as well as the research articles which are going
to be presented in this big forum could be a guideline for future progress in Nepal in
the field of Soil Science. We expect it will add a new feather in agriculture
development.
This is the 2nd National Workshop organized after 17 years. Respected chairman, we all
know that soil is very important for lifes whether a very small and tiny organism to
higher plants and animals. The promotion of sustainable soil and land management is
central to ensured sustainable productivity, improved rural livelihoods and a healthy
environment. We all depend on soils. Healthy soils are the basis for healthy food
productions. Soils are the foundation for vegetation which is cultivated or managed for
feed, fiber, fuel and medicinal plants and products. It not only support earth's biodiversity but also help combat and adapt to climate change by playing a key role in the
carbon cycle. Soil is also store house of water and filters the water improving our
resilience to floods and droughts especially in the hills and mountains regions of Nepal.
It is non-renewable resource, its protection and preservation is very essential for food
security and for our sustainable future. Also soil is the habitat of so many microorganisms, bacteria, fungi, actinomycetes etc which plays a vital role in nutrient
mineralization, N,P, S cycle. The multiple roles of soil goes unnoticed. We need
healthy soils to achieve our food security and nutrition goals. World biodiversity helps
to mitigate and adopt the climate change. One third of all soils are degraded due to
erosions, compaction, soil sealing, salinization, soil OM and nutrition depletion,
xiii
acidification, pollution and other process caused by poor management practices. The
International Year of Soil aims at raising full awareness among civil society and
decision makers about the profound importance of soil for human life.
At last I would like to say thank you very much again for your kind participation. Your
suggestions and positive critics would help our Soil Science to develop new
technologies and their wider disseminations. In this occasion, I would like to propose
next workshop be held in every 5 years.
Thank you.
Bishnu Hari Adhikary
Chief Soil Scientist
Secretary and Co-ordinator, SNSFR Workshop
xiv
ABBREVIATIONS
CA
CAPS
CEC
CIMMYT
CO2
CT
DAS
DoAD
FY
FYM
GDD
GIS
GPS
HICAST
HWSD
IAAS
INM
INSEY
IRRI
kg ha-1
LRMP
MM
MSTL
NARC
NARI
NDVI
NIR
NMRP
NRs
OM
POM
RCBD
RI
RS
SARO
SOC
SOM
SSD
SSMP
ST
t ha-1
TU
WRB
YPN
Conservation Agriculture
Conservation Agriculture Production System
Cation Exchange Capacity
International Maize and Wheat Research Centre
Carbon Dioxide
Conventional Tillage
Days after Sowing
Department of Agriculture Development
Fiscal Year
Farm Yard Manure
Growing Degree Days
Geographic Information Systems
Global Positioning System
Himalayan College of Agricultural Science and Technology
Harmonized World Soil Database
Institute of Agriculture and Animal Science
Integrated Nutrient Management
In-Season Estimated Yield
International Rice Research Institute
Kilogram Per Hectare
Land Resources Mapping Project
Mineral Materials
Mobile Soil Testing Laboratory
Nepal Agricultural Research Council
National Agriculture Research Institute
Normalized Difference Vegetation Index
Near Infrared
National Maize Research Programme
Nepali Rupees
Organic Matter
Particulate Organic Matter
Randomized Complete Block Design
Response Index
Remote Sensing
South Asia Regional Office
Soil Organic Carbon
Soil Organic Matter
Sustainable Soil Management Programme
Strip Tillage
Ton per Hectare
Tribhuvan University
World Reference Base
Predicted Yield with Added Nitrogen
xv
xvi
Table of Contents
1. Key-note Address
Soils and Food Production
Dhruva Joshy
1
1
Mobile Soil Testing Laboratory (MSTL): Experience of Soil Management 6
Directorate to Aware Farmers about Soil Health
Durga P Dawadi , Chandra P Risal , Kiran H Maskey , Balaram Rijal
and Tuk B Thapa
Soil Fertility and Fertilizer Use in Nepal: past, present and future
Krishna Bahdur Karki
16
Soil Degradation and its Management
Bhaba P Tripathi
26
Healthy Soils for a Healthy Life: Research Efforts and its Challenges
Shree P Vista and Bishnu H Adhikary
36
2. Soil Fertility
Soil Fertility Status of Nepal: Report from Laboratory Analysis of Soil
Samples of Five Developmental Regions
Durga P Dawadi and Manita Thapa
42
Evaluation of Soil Properties and Wheat (Triticumaestivum L.) Productivity 53
Influenced y Nitrogen Levels and Sowing Dates under Zero Tillage
condition in Chitwan, Nepal
Ran B Mahato, Keshab R Pande and Anant P Regmi
Response of Soybean to Boron and Molybdenum Application Under Rampur 62
condition
Rita Amgain and Renuka Shrestha
On-Farm Monitoring of Improved Management of Farmyard Manure and Soil 68
Nutrient Fertility in the Middle Hills of Nepal
Bishnu K Bishwakarma, Richard Allen, Juerg Merz, Bishnu K Dhital,
Niranjan P Rajbhandari, Shiva K Shrestha and Ian C Baillie
Use of Optical Sensor for In-Season Nitrogen Management and Grain Yield 79
Prediction in Maize
Bandhu R Baral and Parbati Adhikari
Effect of Long-term Application of Organic Manures and Inorganic Fertilizers 87
on Soil Properties and Yield of Rice and Wheat under Rice-Wheat System
Narayan Khatri, Ram D Yadav, Nawal K Yadav, Surya N Sah and
Kulananda Mishra
xvii
Nutrient management experiment in wheat – common bean system at high 92
hills condition in Nepal
Laxman Lal Shrestha and Gautam Shrestha
Utilizing nvasive
lant
pecies, Eupatorium for Increasing
productivity Through Making iochar in Nepal
Naba R Pandit, Bishnu H Pandit and Hans-Peter Schmidt
and 101
Potential Options for Sustainable Land Management and Intensified 111
Agriculture
Bajracharya R, K Atreya, N Raut, BM Dahal, HL Shrestha, NR Dahal,
DK Gautam and P Karmacharya
Studies on Sustainable Soil Fertility Management on Rapeseed
Rajan Malla, Shankar Shrestha, Himal P Timalsina, Bahuri P
Chaudhary and Om N Chaudhary
128
Study on Soil Fertility Status of Vegetable Growing Pocket Areas of Dhading 135
District, Nepal
Binita Thapa, Dinesh Khadka and Shree P Vista
Effect of Different Sources of Organic and Inorganic Nutrients in Wheat 141
under Terai Condition
Sabina Devkota, Shova Shrestha and Shree P Vista
Sustainability of Long-term Soil Fertility Management in Rice Wheat 144
Cropping Pattern n Eastern Mid Hills of Nepal
Parashuram Bhantana1, Shree P Vista and Ram B Katuwal
Effects Drought the Mobility Foliar-Applied Boron
Arjun Shrestha Thomas Eichert
Plants
151
Efficacy of Nitrogen and Phosphorus on Rice under Rice-Tomato Cropping 163
System at Central Terai Region, Nepal
Shova Shrestha, Sabina Devkota, Bishnu H Adhikary and Sahabuddin
Khan
Long-term Soil Fertility Experiment Under Rice – Wheat Cropping System in 166
Regional Agricultural Research Station, Parwanipur, Bara, Nepal
Shova Shrestha, Gautam Shrestha, Maheshwor P Sah, Kailash P Bhurer
and, Bishnu H Adhikary
Biochar: ts ole in oil anagement and otentiality in Nepalese Agriculture
Shree P Vista, Ananta G Ghimire, Schmidt Hans Peter, Simon Shackley
and Bishnu H Adhikary
174
Effect of Organic Matter and Iron Slime on Changes in Soil Properties
S
P Vista and Dipankar Saha
178
xviii
Efficacy of Fertilization Levels and Genotypes on the Grain Yield of Winter 190
Maize (Zea mays L.) in the Acidic Soils of Chitwan Valley
Bishnu H Adhikary, Bandhu R Baral, Jiban Shrestha and Robinson
Adhikary
Sowing Time and Nutrient Management in Cowpea Under Light Textured 199
Acidic Soil of Central Chitwan Valley, Rampur
Renuka Shrestha, Bhim N Adhikari and Ramesh Shrestha
E
m
209
Roshan B Ojha
Phosphorus Speciation in Nitisol from Ethiopian Highlands
Hari R Upadhayay, Soraya C França and Pascal Boeckx
216
Yield Trend and Soil Fertility Status After a 36-Years Rice-Rice-Wheat 233
Experiment
Nabin Rawal, Dev R Chalise, Dinesh Khadka and Khim B Thapa
Long-term oil ertility rial in ice heat ystem in regional 244
agricultural esearch tation, Khajura, Banke: esults of oil nalysis ata
from 1998 to 2006 and 2014 AD
Gautam Shrestha
Response of Tribeni Organic Complexal to Potato and Rice
Shree P Vista, Shambhu Raut, Dinesh Khadka, Laxman Lakhe and
Bishnu H Adhikary
257
3. Soil Microbiology
Nematodes and Soil Fertility
Pradipna R Panta
261
261
Efficacy of Azolla pinnata in Rice (Oriza sativa L.) Production in the Central 273
Region of Nepal
Bishnu H Adhikary, Sanukeshari Bajracharya, Robinson Adhikary,
Kailash P Bhurer and Shree P Vista
Symbiotic Characterictics of Nepalese Bradyrhizobium Isolates from Soybean 281
(Glycene max) and Mungbean (Vignaradiata) Crops
Chandra P Risal and Balaram Rijal
The Trichoderma spp.: A Biological Control Agents from Nepalese Soil
Ram D Timila, Shrinkhala Manandhar, Chetana Manandhar and
Baidhya N Mahto
294
Efficacy of Jeevatu Jho Mal (JJM) to Radish (Raphanussativus L.)Production 301
in the Central Valley of Kathmandu
Sanu K Bajracharya, Bishnu H Adhikary and Sri K KC
xix
4. Geographical Information System (
) and
308
Soil Types and Fertility Status in Western Terai Region of Nepal: A Case
from the BankatawaVDC of the Banke District
Krishna R Tiwari
Soil Fertility Evaluation of Middle Mountain of Nepal: a case of Shikharpur 316
Municipality, Kathmandu District
Raju Rai, Rajendra P Tandan and Krishna B Karki
Assessment of Soil Fertility Status and Preparation of Their Maps of National 330
Wheat Research Program (NWRP), Bhairahawa, Nepal
Dinesh Khadka, Sushil Lamichhane, Binita Thapa, Nabin Rawal, Dev R
Chalise, Shree P Vista, and Laxman Lakhe
Preparation of VDC Level Land Use, Soil and Land Capability Maps of 345
Chaumala VDC,Kailali
D
Chalise, Abhasha Joshi, Chet R Bam, Bikesh Twanabasu, Nabin
Rawal and Saroj Amgai
Soil Nutrition Distribution in Eastern Tarai of Nepal: A Case Study of 358
Jhorahat VDC of Morang District
Rajendra P Tandan, Raju Rai, Laxmi Basnet and Krishna B Karki
Soil Organic Carbon Stocks Estimation and Mapping by Using Geographic 368
Information Systems in Rautahat District
Kamal Sah, Sushil Lamichhane and Binod Silwal
Geographical Information System and Remote Sensing (GIS and RS) 374
Supported Soil Fertility Mapping
Ragindra M Rajbhandari and K
B Karki
Preparation of ata ase and Soil Map of Nepal using WRB 2010
Classification System
Subhasha N Vaidya
Kamal Sah
Modeling of Soil Organic Matter Content from World View-2 Sensor in
Nayavelhani VDC of Nawalparasi District, Nepal
Umesh K Mandal
5. Soil Environment
Carbon Dioxide Emission from Soil Grown to Wheat Crop at Khumaltar,
Lalitpur
Saraswoti Kandel, Shree C Shah Ananda K Gautam and Keshab R
Pande
xx
393
403
412
412
6. Resource Conservation Technolgy
Enhancing Soil Fertility and Crop Production Through Promoting
Conservation Agriculture Production Systems (CAPS) in the Mid Hills of
Western Nepal
Bir B Tamang, Keshab Thapa, Roshan Pudasaini, Bikash Paudel, Susan
Crow, Jacklene Halbrendt,Ted Radovich and Catherine Chan
Tillage Affects the Soil Properties and Crop Yields
Tika Karki and Jiban Shrestha
7. Soil Policy
Soil cientists ngaged in esearch,
and
in Nepal: Where o e o?
Keshav R Adhikari
421
421
432
439
439
Chemical Pesticide Application: An Impending Threat to Soil-Health 447
Maintenance
Ram Babu Paneru, Sunil Aryal and Yagya P Giri
8. Workshop Recommendations
9. Questions and Answers
ANNEXES
Annex 1: Authors Index
Annex 2: Keywords Index
Annex 3: List of Participants
Annex 4: Workshop Programme Schedule
xxi
458
462
464
465
467
471
xxii
24-25 March 2015
Proceedings of the workshop
KA-1
Soils and Food Production
Dhruva Joshy
Former Executive Director of the NARC
Abstract
Historically Nepal has never been a major food deficit country. But since the 1980s it has
become increasingly dependent on cereal imports. The number of malnourished people is
in rise. Whenever the monsoon fails the country has to reel under hunger due to reduced
food availability caused by low agricultural production. Never before the threat of
starvation has been so greater than it is today in the country. The threat is not due to the
country’s reduced capacity to food production. Indeed, the capacity is greater today than
it ever been and will continue to grow as the new vistas of science keep unfolding by the
research scientists. The problem lies in the lower adoption of the modern technologies
compounded by spiraling population growth and lack of adequate fund for agricultural
research.
Our agricultural scientists have tools to increase the country’s food production by many
folds, if supported with adequate funding through national government policies, but
frustratingly they cannot control the population rise. The fight to feed the country’s
population is not yet a lost battle. But to win this war we must require technological and
scientific inputs of a magnitude not yet realized. An environment needs to be created by
the concerned agencies by which the farmers can easily adopt the new technologies
without any problems – be it availability of technology, be it finance or be it market. And
among the most important of these inputs are those relating to soils and soil science. Our
soils must be protected and properly managed if they are to produce enough food needed
to feed our ever growing population.
Keywords: Food deficit, research scientists, spiraling population growth, technological
and scientific inputs.
Overview
It is customary for every government to make tall claims about its achievements. In
spite of such ostentatious claims the stark reality is that the country’s agriculture is not
being able to produce enough food to feed its people without importing foodgrain. The
crisis is nothing but the manifestation of everything that can go wrong has gone wrong.
Country’s largest private sector, steeped in neglect, dogged by problems and afflicted
with policy malaise, needs immediate hospitalization. Instead, it receives government
support as first aid only. We all know doling out government largesse is only a respite,
not a long term solution to bring people out of hunger and poverty. To change this
situation unless country’s agriculture develops and to develop agriculture unless the
condition of agricultural research starving for funds remains unchanged, the battle on
hunger and poverty will not be realized.
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24-25 March 2015
Country’s Food Production Situation
The recent news of importing rice worth of billion rupees every month unfolds the
largest and the most enigmatic agricultural crisis the country has faced ever. Largest,
because the country had been able to produce five million tons of paddy, a record
harvest in 2012, yet not enough to feed its people without import. This year the
government indicates that agricultural growth rate will decrease and has revised its
annual targets. Enigmatic, because it is a crisis that has build up due to skewed vision
of bureaucracy, in spite of having plans like APP and other good policies.
The reality is that our farm productivity is being held back, our competitiveness in the
market is being undermined, and our national prosperity is being unnecessarily limited
because the agricultural research services are starved of the modest level of resources
that they require, as compared to most items of the national expenditures. The
casualties of the situation will not be research scientists, but they will be the poor of the
country. Therefore, support for agriculture research is not a matter of charity but it is a
step of wisdom and prudence for the government.
Despite more than five decades of our planned development agriculture is a neglected
professions against our old saying Uttam kheti, Madhyam byapar… (Farming is the
best occupation, second best is business and working for someone else is the worst).
Since farming is increasingly becoming a non-profitable profession, younger
generation is least interested to take up this profession. In stead they are ready to toil at
the desert of Gulf countries or hostile environment of other countries as migrant
workers. Because of such situation, land is left untilled due to shortage of working
hands. The situation is deteriorating year after year, if long term remedial measures are
not taken up by the government. The Ministry of Agriculture has no plan to address
such problems vis-à-vis soil fatigue as has been developed by over-exploitation of
plant nutrients and organic matter in intensive cropping areas. Chure bhabar range is
turning into barren land with the threat of desertification looming large due to wanton
tree felling, overwhelming soil and nutrient wash, receding water table and
unmanageable operation of stone quarries. President Ram Baran Yadav’s unremitting
zeal to reclaim Chure region had heralded a glad tidings but Nepalese bureaucrats has
turned it into a hasty afterthought.
The problem of such nature and magnitude can not be addressed by a mind-set of
business as usual. In order to respond such crisis one needs to have an out-of-the-box
thinking which is clearly not visible with the government at present. This will force
more and more marginal farmers to opt out their current farming profession on one
hand and on the other, the younger generation, which has no attraction towards
farming, will be tempted to go out of the country in torrents as migrant workers. If land
remains untilled due to shortage of agricultural labours in our villages, how our
agriculture would be able to produce enough food to feed our growing population.Let
us not fazed by the challenge the agriculture sector faces. Inadequacy of food in the
country is not due to its reduced capacity of agriculture to produce more food. In fact
the capacity is greater today than it has ever been because of the modern technologies
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24-25 March 2015
research has been inventing. The moot question is – how these technologies are made
available to our farmers and are they in the position to use them? At present the
adoption of these technologies is at a very low lever due variety of reasons ranging
from socio-economics to post harvesting processing to marketing. But we all know that
agriculture can be a powerful engine of economic growth in a country like Nepal where
national economy is largely dependent on agriculture. The bureaucrats, policy makers
and political leaders alike must understand there can be no economics without politics,
but more importantly there can be no politics without economics.
Country’s Natural Resources
Soils are natural occurring bodies. A pedologist is concerned with its origin,
classification and characterization for the variety of purposes – farm and nonfarm uses.
While the edaphologist, on the other hand, is concerned principally with the most
important use of soils i.e. as a medium for the plant growth and particularly food crop
plants. In this regards, soils must be protected and managed properly if they are to
produce enough food needed to feed the growing population.
Despite its geographically small size, Nepal has diverse topography with three distinct ,
parallel running east to west physiographic regions known as the High mountains in
the north, the Hills in the middle and the flat land of the Terai in the south. The country
has a little more than 14.5 million hectare of land area. The high mountain in the north
and hill in the middle account for 35 and 42 percent each of the total area, while the
Terai has a share of 23 percent. More than half of the country’s area is non arable due
to hills and mountains which are too cold and too steep for tillage. The arable land in
the high mountains is only 10 percent while the hills and the Terai have 56 and 33
percent each. The distribution of arable land in the country is skewed due to dominant
mountain topography.
There are two ways that a nation may fallow to utilize its land resources to increase its
food production. They are:
(a) clear and cultivate arable land that has not been tilled until now, or
(b) intensify production on lands already under cultivation.
There is little opportunity to increase land under agriculture, perhaps, less than 10
percent as most of the arable land is already under cultivation. Expanding agricultural
land will further entail on forest land which will have negative bearing on our ecology.
Thus under the given situation only option we have left to produce more food is by
increasing annual crop yields per hectare by augmenting soil fertility of our arable
lands. Here agriculture research can play a very important role if supported by proper
policy guide lines.
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24-25 March 2015
Factors Influencing Food production
Nations’ capacity to produce food is determined by various factors. These include a
complex of social, economic and political factors most of which decide the farmers
incentive to produce food. Besides, there are a number of physical and biological
factors also that have bearing on food production. They are:
• The natural resources available, particularly soils and water.
• Availability of technologies in proper management of crops, animals and
soils.
• Availability of improved varieties and breeds that respond to
propermanagement.
• Supply of agricultural inputs.
• Market incentive.
Except the last one, each of the above factors is affected by the quality of soils – their
natural productivity and response to management. If a nation needs to produce
adequate food, satisfactory soil properties should be high in the list of prerequisites.
Requisites for Higher Production
A nation’s ability to feed itself depends upon many factors, of which access to
improved agricultural technologies is the most important one. Such technologies
largely depend on science and more specifically on research and education. These
technologies must have direct relevance in increasing crop yields under our socioeconomic situation and not be a mere transplant of what is available in developed
nations.
The important aspect of these requisites is that the improved technologies must provide
a package of all the inputs upon which a successful crop production could depend.
Such package must consider economic, social, political and biological factors that
affect farmers’ incentive to grow more.
A final requisite, a nation should consider, in the quest of increasing food production is
a pool of trained personnel. They range from scientists (from whose test tubes or field
plots new technologies and perhaps new food products may come) to their
subordinates. To efficiently utilize our scarce resources we must have adequate number
of research scientists whose interest relates directly to the solution of the food
problems. On many occasions we have experienced that lending institutions and
international consulting firms are not the best reservoir of knowledge to be banked
upon, as we ha seen, they have left many world economies in doldrums.
Let us acknowledge that our problems are unique to us and so will be our solutions.
We have been implementing our periodic plans, based on the Soviet Union’s five-yearplan model, over many years have only helped us to remain as a mediocre country of
the least developed nations. Why it is so? It needs a dispassionate analysis. Since it is
beyond the topic given to me, I, therefore, acted as a devil’s advocate only. To reap the
fruits of modern technologies the country must raise its investment in agricultural
research to a level of one percent of the AGDP. Again, mere financial allocation would
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24-25 March 2015
not help. Our research organizations need to be backed by proper policy environment
suited to its functioning as a research organization in a true form.
Too much focus on the service delivery institutions, without enough deliverables at
hand, has dampened our agriculture’s growth trajectory significantly. This is a truism
one has to agree with whether one likes it or not. The government and Planning
Commission need to see a reasonable match in its financial allocation between research
and service delivery institutions. Or else, we will remain as a food importing country
for many more five-year plans to come. To excel as a research organization, we must
cultivate a culture of “let the best beat the rest”, not the one who carries the baggage
of political leaders or parties.
The fight to feed the increasing population is not yet lost. Our planners and policy
makers must realize that to win that war it will require technological inputs of a
magnitude not yet realized. And among the most important of these inputs are those
relating to soils and soil science.
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24-25 March 2015
TH-1
Mobile Soil Testing Laboratory (MSTL): Experience of Soil Management
Directorate to Aware Farmers about Soil Health
D
P Dawadi, C
P Risal, Kiran H Maskey, B
Soil Management Directorate
Rijal and T
B Thapa
Hariharbhawan, Lalitpur
Abstract
Soil testing is the basis for soil fertility management that maintains the productivity of soil
and improves the quality of crops. It promotes more efficient use of fertilizers at a lower
cost, and prevents environmental pollution from excess fertilizer. Unbalanced use of
chemical fertilizer is a common problem in Nepal. In particular, much nitrogen fertilizer is
often applied at the expense of other nutrients in major vegetable pocket areas.
Soil Management Directorate under Ministry of Agriculture Development implements the
soil management programs all over the country. It has seven static soil test laboratories at
least one at each development regions. However, the existing soil analysis facility under the
Soil Management Directorate and its laboratories are very inadequate. Recently, Paradeep
Phosphate Limited (PPL) one of the leading Diammonium Phosphate (DAP) fertilizers
producing company at India has provided one Mobile Soil Testing Laboratory (MSTL) to
Soil Management Directorate (SMD). SMD has organized eight soil test campaign with
MSTL in Kavre, Dhading, Kaski, Palpa and Gulmi districts of the country. Convincing
farmers of the target area with different documentary show is done just one day before
conducting soil test campaign. Generally the shows are related to the importance of soil
testing, how to collect soil samples
the success stories etc.
MSTL has facilities to test Organic carbon, pH, EC, Phosphorus and Potash content in the
soil with all the accessories and power back up. Farmers can get the soil test results on the
same day. Just after the soil test campaign, farmers are trained about the results and the
respective management practices. As a whole, MSTL is an effective tool to provide soil test
services to farmers at their nearest points and it has been proved to be a convincing method
to aware farmers about soil health.
Keywords:
Mobile soil testing laboratory (
)
fertility
unbalanced use ofchemical fertilizer.
Introduction
Soil is a living medium which serves as a natural nutrient source for growth of plants.
The components of soils are mineral, organic matter, water and air, the proportions of
which vary and together form a system for plant growth. Soils are studied and
classified according to their use. Soil survey is kept under the discipline of Natural
Resource Management and soil Testing is a part of the discipline of Fertilizer Use and
Management.
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24-25 March 2015
The pace of soil degradation is the highest in mountains because of fragile environment
and the steep slopes. Moreover, due to rugged mountainous topography, active
tectonics and concentrated monsoon precipitation, Nepal is naturally highly vulnerable
to soil erosion on slopes and flooding in the low-lands. (Tulachan 1999).
In Nepal, high topography, climatic conditions, improper soil management practices,
indiscriminate use of synthetic chemicals and the declined use of organic matter for
soil management are the major reasons for reduced soil fertility. This has led to the
degradation of thousands of hectares of land through erosion, acidification, and
pollution by heavy metals.
Nepal’s economy largely depends on agriculture as it contributes one third of Gross
Domestic Productions. Rate of population increment is greater than that of agricultural
productions. There is very little chance of expanding the cultivable land, so the
inevitable food crisis must be solved by raising the productivity of existing arable land.
Among the different means of increasing productivity of crop, ‘soil fertility
improvement’ is one of the key factors.
Fertility status of soils
The soils of Nepal are pre-dominantly acidic in nature, about 70% soils are acidic, 20%
normal and about 10% alkaline soils. About 60% soils are low in organic matter.
Phosphorus is low in 40% soils and medium & high in 30% soils each. Available
potash which was high in 68% soils in 2003 has declined to 26% in 2013, which is a
matter of concern.
Status of Soil Testing Programme
In Nepal Soil Management Directorate under Ministry of Agriculture Development
implements the soil management programs. Besides five Regional Soil Testing
Laboratories at five different development regions there is one more Soil Testing
Laboratory at the Surunga of Jhapa district mandated for the soil sample analysis of
industrial crops, especially for tea and cardamom.
The major programs conducted through Soil Management Directorate include soil
analysis, fertilizer analysis, micronutrient analysis, Integrated Plant Nutrient
Management System, Nutrient deficiencies study, Soil fertility maps of different
districts, training related to soil management and laboratory procedures, Farm Yard
Manure (FYM) and Compost Management programs etc. However, the existing soil
analysis facility under the Soil Management Directorate and it’s laboratories are very
inadequate.
Organic farming in Nepal is in very primary stage though government policies support
it. Organic certified area is 50,000 ha. and also another 26,800 ha. are organic
cultivated but not yet certified. The major organic products exported are coffee, tea
and herbal. Government interventions towards organic fertilizer promotion seems to be
having impact for Organic farming.
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Need for Soil Health Card (SHC) in Nepal
Nepal is facing a serious problem of soil quality decline as a result of recent changes in
agricultural practices and increasing resource constraints. There are several constraints
in soil fertility management in Nepal because of deforestation and other land use
changes. These changes include non-agricultural uses of fertile land, land
fragmentation and cultivation in marginalized areas, cultivation on the slopes,
overgrazing, burning of crop residues, imbalanced use of agrochemicals, and decline in
use of organic manure. In South and South-East Asia, the principal soil degradation
processes associated with use changes include accelerated erosion by water and wind,
salinization, flooding, water logging, and soil acidity. (Pandey et al 2008).
The increasing gap between soil management and soil fertility decline became a big
challenge for sustainable soil management program and great concern for agricultural
production. Due to lack of soil fertility information of the individual farm or of a
particular area, fertilizer application is unscientific and overall soil fertility
improvement attempts have been unsuccessful. Therefore, to recover the deteriorated
fertility status of the soil and harness the maximum productivity, it is essential to know
the existing soil fertility status and manage them on the basis of soil test results. The
practical way to know the existing soil fertility status is the collection and analysis of
soil samples in the soil test laboratories. However, farmers have been applying
fertilizers randomly without their soil test result because of limited soil testing
facilities. Sustaining soil fertility is one of the great challenges for agricultural growth
in Nepal.
Agriculture Perspective Plan (MoAD, 2013) of Nepal and its different periodic plans
have put emphasis on boosting up the agriculture production through use of chemical
fertilizers and irrigation in high production potential areas. Sustainable soil fertility
management is an important requirement for sustainable farming. Nepalese farming
system is strongly interlinked among livestock, forestry and agriculture. The traditional
agriculture is based on organic source of input and largely depends upon the forest
resources and livestock raising practices for soil fertility management.
In the context of growing number of commercial farmers in Nepal, the demand for soil
testing and maintaining soil health is also increasing. To meet this demand there is
limited number of soil testing laboratories and technical manpower in the country.
Those technicians who are involved in laboratory analysis are not well trained and
equipped with the lab equipments. Hence, the stated project aims to strengthen the
existing laboratories as well as expand the services. Similarly, it will develop the skill
of the technical manpower in the field of soil management.
Therefore, to ensure food security of the Nepalese people through improvement of
fertility status of soil by periodic soil fertility analysis and management as per the soil
health report the necessity of Soil Health Card (SHC) system in Nepal is extremely
important.
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24-25 March 2015
To achieve the objectives of providing SHC to all the farmers in Nepal, a national level
project with the following strategies is necessary:
i)
ii)
iii)
iv)
v)
Promote soil analysis & fertiliser recommendations for all 35 lakh of
farmers within 5 years by strengthening soil testing programme in the
country.
Promote Integrated Nutrient Management amongst the farmers through
issue of Soil Health Cards.
Promote fertiliser & organic resource use efficiency and crop productivity
through application of site specific soil fertility management practices.
Promote quality control facilities for fertilizer and organic inputs.
Develop human resource for fertilizer quality control, soil testing, organic
certification, etc.
Capacity building for Soil Testing
The soil testing capacity in Nepal is 20,000 soil samples per annum. There are 7 Soil
Testing Laboratories (STLs) under Soil Management Directorate (SMD). Initially
strengthening / setting up new STLs are proposed.
Strengthening capacity of existing soil testing facilities under Department of
Agriculture (DOA) and Nepal Agricultural Research Council (NARC) and to enable
them to analyze 6,95,000 soil samples per year and issue soil health card (SHC) for
farmers, based on the soil sample analysis. After completion of project, with this
capacity, all farm holdings can be provided SHC every 5th year.
Strengthening of 16 existing Soil Testing Laboratories (7 under SMD and 9 under
NARC) are to be strengthened for NPK as well as micro-nutrient testing facilities to
upgrade their capacity to 10,000 samples per annum per laboratory (Total 1,60,000
samples per annum). Funds amounting to NR 50 lakh per laboratory is required.
Seven new Mobile Soil Testing Laboratories (STL), one Mobile STL attached to each
existing STL of SMD with a capacity of 5000 samples per Mobile STL per year (Total
35,000 samples per annum) are proposed to be set up at a cost of NR 80 lakh per
Mobile STL.
Fifty new static Soil Testing Laboratories are to be set up on PPP Mode with a cost of
NR 25 lakh per laboratory to analyse only major nutrients. The capacity of each
laboratory will be 10,000 samples per annum (Total 5,00,000 samples per annum).
These laboratories will test soil samples on charged basis.
Mobile Soil Test Laboratory (MSTL) in Nepal
There is a growing concern over Soil and Soil Health issues all over the world due to
the increasing concern of people over their health. United Nations has officially
declared the Dec 5 as World Soil Day beginning from 2014. And, has announced 2015
as International Year of Soil. In this context, Soil Management Directorate (SMD) is
9
24-25 March 2015
launching nationwide MSTL campaigns with the slogan of “Healthy Soil Wealthy
Nation” to mark International Year of Soil.
Healthy soil gives us clean water, good crops and forests, productive land, diverse
wildlife, and beautiful landscapes. Healthy soil does all this by performing five
essential functions of regulating water, supplying nutrients to plant, filtering potential
pollutants, cycling nutrients and supporting plants.
A master training programme of MSTL operation was conducted in 2014 in Odissa
state of India for six soil scientists in SMD in collaboration with Paradeep Phosphates
Limited (PPL), India as a initiation of the program. With the completion of this training
program one MSTL has been gifted by PPL to SMD as a symbol of goodwill between
Nepal and India. After receiving the MSTL, SMD has organized eight MSTL
campaigns in six districts. The Soil Test Awareness shows and MSTL operation are the
important activities during the campaign. Evening Film shows in villages for
awareness of soil testing will be conducted just before the MSTL campaign.
Demonstration on Soil Sampling method is also a major part of the documentary show.
Processs of operating MSTL in the field and the analysis methods:
•
•
•
•
•
•
•
Collection of Soil Samples, registration & Money Receipt for soil analysis
charges
Soil Processing before analysis
Analysis of Soil pH by pH meter
Organic Carbon Analysis by Uv Spectro Photometer
o 2g Soil +2 ml 2.5 N K2 Cr2 O7+2.5 ml H2 SO4+ 5 drops conc. H3 PO4(
volume made up to 50ml mark) after 8hrs waiting supernatant
solutiom reacting for O.C taken in specro photometer at 660 nm after
standard calibration of glucose solution.
AvailablePhosphorus
( Acidic Soil- Bray’s Method, Alkaline- Olsen’s Method)
Bray’s Method:- 2g Soil + 20 ml Bray’s reagent( shaking), filterate
5ml+ 5ml Amm. Molybdate + 10 ml diatilled water + 1ml SnCl4 make
upto 25ml. Reading thru spectro photometer.
Estimation of Available Potash with Flame photometer
o 5g Soil + 25ml Nutral Normal Ammonium Acetate shaking for 5 mins
o Filter the solution & reading through flame photometer after standard
calibration.
Distribution of Soil Test Reports to farmers with tips on fertilizer
recommendations.
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24-25 March 2015
Table 1: Summary of soil test results through MSTL in Nepal.
pH
Alk
NN
SA
A
Total
57
303
229
21
0
610
OM
VL
L
M
H
VH
N
3
361
189
56
1
610
VL
L
M
H
VH
P2O5
3
307
184
115
1
610
K2O
VL
L
M
H
VH
192
121
60
74
163
610
VL
L
M
H
VH
59
89
284
119
59
610
Alk= Alkaline, NN= Nearly Neutral, SA= Slightly Acidic, A= Acidic
VL= Very Low, L= Low, M= Medium, H= High, VH= Very High
Table 2:Summary of soil test results through MSTL at Panchkhal, Kavre.
pH
Alk
NN
SA
A
OM
8
105
131
16
0
260
Total
VL
L
M
H
VH
N
0
259
1
0
0
260
VL
L
M
H
VH
0
258
2
0
0
260
VL
L
M
H
VH
P2O5
161
82
12
5
0
260
K2O
VL
L
M
H
VH
48
37
162
11
2
260
Table 3: Summary of soil test results through MSTL in Dhading district.
pH
Alk
NN
SA
A
OM
32
65
9
1
0
107
Total
VL
L
M
H
VH
N
2
76
29
0
0
107
VL
L
M
H
VH
P2O5
2
37
67
1
0
107
VL
L
M
H
VH
K2O
3
12
6
24
62
107
VL
L
M
H
VH
7
23
48
24
5
107
Table 4:Summary of soil test results through MSTL in Pokhara (Organic fair).
pH
OM
N
P2O5
K2O
Alk
9
VL
1
VL
1
VL
8
VL
1
NN
10
L
10
L
6
L
3
L
13
SA
11
M
17
M
21
M
5
M
11
A
0
H
1
H
1
H
4
H
4
0
VH
1
VH
1
VH
10
VH
Total
30
30
30
11
30
1
30
24-25 March 2015
Table 5: Summary of soil test results through MSTL in Palpa district.
pH
OM
N
P2O5
K2O
Alk
6
VL
0
VL
0
VL
5
VL
2
NN
56
L
14
L
5
L
7
L
9
SA
23
M
35
M
35
M
4
M
27
A
1
H
37
H
46
H
19
H
31
0
VH
0
VH
0
VH
51
VH
17
Total
86
86
86
86
86
Table 6: Summary of soil test results through MSTL in Gulmi district.
pH
Alk
NN
SA
A
Total
OM
2
67
55
3
0
127
VL
L
M
H
VH
N
0
2
107
18
0
127
VL
L
M
H
VH
P2O5
0
1
59
67
0
127
VL
L
M
H
VH
K2O
15
17
33
22
40
127
VL
L
M
H
VH
1
7
36
49
34
127
Indian experience on Soil Health Card
• Scheme provides for issue of Soil Health Cards (SHC) once in every 3 years
along with recommendations on appropriate dosage of nutrients to be applied
for production of crop.
•
Soil analysis will be done with uniform sampling procedures.
•
SHC provides information to the farmers on soil texture, density, porosity,
acidity / salinity and nutrient content.
Soil Health Card-Steps
Activity
Soil sampling
Soil analysis
Recommendations of doses
Data base
Issue of SHC to farmers
Particulars
Samples from cropped area / twice a year
Primary nutrients -NPK
Secondary- Ca, Mg & S
Micro-Zn, Fe, Cu, Mn, Mo, B & Cl.
Based on soil analysis data &
management practices
Through NIC
Hard copy in person /Distribution
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24-25 March 2015
Farmer ID and Soil Health Card
SHC NO.:………………………………………
Farmer ID:……………………………………
Village:………………………………………..
Block:…………………………………………
Taluka/Sub Division:……………………….
Date of Collection of Soil sample:…………
Date of soil analysis:………………………..
Name of Soil analysis lab/
mobile unit:…………………………………
SOIL HEALTH DATA
A. Physical Characters: 1. Soil type/texture:………..
B. Nutrient Status:
1. pH ……………, 2. EC (mmhos/cm)…………………..
3. Organic Carbon (%)………………………………….
4. Major nutrients (kg/ha) i. Nitrogen…..… ii. Phosphorous……..…. iii. Potassium……...
5. Seocndary/Micronutrients (%/ppm) i. Calcium…….ii. Sulphur….. iii. Magnesium…….
iv. Zinc……. v. Manganese………….. vi. Boron………. vii. Iron……… viii. Copper………
ix. Molybdenum………………..
Outsourcing
Model 1 :
• State Government provides: Soil Testing Laboratory, Chemicals, Glasswares
& samples to be analysed.
• Outsourcing company provides: Analysis of samples, report preparation,
computer entry, preparation of SHC and delivery of SHC to District
Agriculture Officer.
• Charges: Rs.60 for NPK analysis and Rs.80 for NPK + micro-nutrients.
Model 2 :
• Outsourcing company provides: Soil Testing Laboratory, Chemicals,
Glassware, Collection of samples, Analysis of samples, report preparation,
computer entry, preparation of SHC and delivery of SHC to District
Agriculture Officer.
• State Government provides: Provide only charges to the outsourcing company.
Providing Soil Health Cards to all farmers in Nepal
 Total number of farm holdings – 33.64 lakh
 Agricultural land cultivated – 30.91 lakh ha.
 Irrigated area – 12.54 lakh
 Existing number of Soil Testing Labs – 7
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24-25 March 2015
(5 RSTL, namely; Sunderpur, Khajura, Pokhra, Hetauda & Jhumka + 1 STL at
Surunga + 1 STL at Soil Management Directorate, Kathmandu)
Source: Statistical Information on Nepalese Agriculture 2011-12 .
Option 1:
To draw samples in a grid of 5 ha and issue SHC to all farmers falling in the grid.
•
•
•
•
•
Agricultural land cultivated – 30.91 lakh ha.
Total Number of soil samples to be analysed @1 in 5 ha – 6.18 lakh
Total Number of soil samples to be analysed annually– 2.06 lakh
Number of Soil Testing Labs (STLs) with 10,000 samples capacity required to
analyse 2.06 lakh samples – 21 STLs.
New additional STLs required = 14 STLs
Cost involved
To draw samples in a grid of 5 ha and issue SHC to all farmers falling in the grid.



Cost for setting up of 14 new STLs @ NRs. 200 lakh per STL (80 lakh for
equipment and 120 lakh for land and building) –NRs. 28 Crore.
Cost of analyzing 2.06 lakh samples @ NRs. 400 per sample- NRs. 8.24 Crore.
Total Cost- NRs. 36.24 Crore.
Outsourcing:
(i)
(ii)
Outsource all activities including collection of samples, analysis, preparation
of SHC and distribution to farmers.
Provide Soil Testing Laboratories, chemicals, glassware, soil samples and
outsource only analysis of soil samples and preparation of SHC in PPP mode.
Providing of portable soil testing kits:
(i)
Agricultural Extension workers can be provided with portable soil testing kits
to analyze soil samples on the spot in the field and provide fertiliser
recommendations. Both color chart as well as direct reading portable kits are
available.
(ii)
Cost of portable soil testing kit developed by ATC, Pulchowk is about Rs
6,500/-. To distribute large number of kits, a tie up with ATC can be made.
Conclusion
Nepal’s agricultural land consists dominance of Acidic soil with poor organic matter
and Nitrogen content.Phosphorus and Potassium mining from the agricultural soil is
prominent as a result of imbalance use of chemical fertilizers.Provision of Soil Health
Card (SHC) for soil fertility management is utmost important for agricultural
development of Nepal.
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24-25 March 2015
References
MOAD. 2013. Statistical information on Nepalese agriculture, 2012/2013. AgriBusiness Promotion and Statistics Division, Ministry of Agriculture and Cooperatives, Kathmandu, Nepal.
Pandey PR, J Nagasawa and M Nakagawa. 2008. Sustainable Agricultural
Development in Nepal: Trends, Problems and Prospects. Journal of
Agriculture, Environment and Development. Agricultural and Greenenvironmental Research Institute (AGRI), Tokyo, Japan.
Tulachan PM. 1999. Trends and Prospects of Sustainable Mountain Agriculture in the
Hindu Kush-Himalayan Region (A comparative Analysis). International
Centre for Integrated Mountain Development (ICIMOD), Kathmandu, Nepal.
Issue in Mountain Development 1999/2. Pp. 6-8.
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24-25 March 2015
TH-2
Soil Fertility and Fertilizer Use in Nepal: past, present and future
Krishna Bahadur Karki
NARC, Nepal
Abstract
Soil delivers services to humans’ wellbeing and ecological balance. In extracting services
human has overexploited soil and now we are facing “the tragedy of global commons”.
Thus, the challenge for civilization is to reconcile the demands of human development in
tolerances with nature.
Knowledge of soil science is as old as civilisation and was used even from Vedic time
somewhere in 700 BC. Kautillyas’ Arthashastram (400 BC) mentioned improvement of
soil fertility and growing of rice and wheat crops in the fertile valley of Indus and
Ganges. At the same time western agriculture was also started. However systematic
study was recordedonly after 4th century A.D. Among others study of Robert Boyle,
Francis bacon, Arthur Young, Justus von Liebig, Birkland–Edieand Haberare remarkable
in the development of soil fertility and fertilizer. There were series of scientific
publications in soil science but only after Dokushaev’s work in soil genesis included soil
science in the scientific society.
Nepalese history of soil science goes back to 1957 when soil science was established
as a unit under the Department of Agriculture to conduct soil sample analysis and soil
fertility experiments. Later other units were added. Scientists with soil science as
academic qualification are lacking in the world by 40% whereas research publications in
soil science and its components is increasing exponentially indicating the importance of
soil science in the society. Nepal has the same fate. Similar to international organisations
holding the highest position by soil scientists, Nepalese soil scientists have held high
position in the Government of Nepal still we have not been able to persuade the people
and the government on the importance of soil science. We are only concentrating in
higher food production but not given any importance on the consequences which may
bring land degradation and desertification. Before it is too late, let us work hard and
convince the society that proper attention is given to restore soil fertility and soil health
so that soil will provide goods and sustainableservices.
Key words: Nepalese soil science, fertilizer use, soil fertility improvement, land
degradation, agriculturedevelopment.
Introduction
Soil delivers goods and services to humans, such as biomass for food, fodder and
renewable energy, filtering, buffering and transformation for clean ground water and
clean air, besides carbon sequestration and maintaining biodiversity. Excessive use
pattern of these services by the society to meet these demands of ever growing
population we are in pain of “tragedy of the global commons”(Singh 2011). Thus, the
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24-25 March 2015
challenge for civilization is to reconcile the demands of human development in
tolerances with nature.
Soil in most of the countries has been always related to agricultural production. Every
country in the world is striving to produce more food to meet the demand of ever
growing population and looking for the ways to produce more food. It is accepted that
food demand can be met fromthree ways: increase land for cultivation; higher crop
yields from unit of land; and reduction in postharvest losses. Scientists and planners
believe that greater part of the increase must come from the higher yield although
substantial increase in land area can be another option. FAO predicts that by the year
2020 world food production must increase by 13% cereal, 15% vegetables and 30% in
meat production of present rate(OECD_FAO 2011). Since expansion of area in most
countries is limited, efforts must be made to increase crop yield per unit area.Although
land balance in the world that land suitable for cultivation in developing countries is
estimated as 760 M ha (Young 1999), but exact location of these land is yet to be
identified.
History reveals that settlement started from the fertile alluvial soilsby the river banks
and took development momentum from the same river valleys.History divulges that
development of agriculture in the western and eastern society seemed to be developed
almost at the same time. Indian literature narrates that cultivation in this subcontinent
started some times 1000 to 500 BC. In Vedic Mythology Kautillya’sArthahsastra
mentioned the need to increase agricultural productivityand farmers’ income. Indus
and Ganges Valleys were the ones where rice, wheat, barley were first grown. Mango
and musk melon were the home to Indian subcontinent. Evidences show that soil was
ploughed several times before seeds were sown. Animal husbandrywas practised and
use of cow dung as manurewas used during the same period but there isno record of
any individual pioneering these activities.
Agricultural development and soil fertility maintenance in the western worldis well
documented. Among many others Aristole’s Human Theory (350BC), Cato (200BC),
have written similar agricultural practicesparallel to Indian subcontinent.Later, van
Helmont(1574- 1664) experimented willow plants growingin soil for 5 yearsadding
only water. He concluded that water was the source of plant nutrient as he found only
200g of soil from the original 5 kg was lost.
History of Agricultural development and fertilizer use in Nepal
Nepalese farmers applied organic manures mostly FYM to the upland crops where
maize and millets were grown. Rice crops depended on the flood sediments that
entered into the field through irrigation. There are reports that 60t ha-1 of FYM has
been applied by the farmers {Upreti cited by (Karki et al. 2007)}. Use of green leaves
of Ashuro (Adhatodavasica),TitePati (Artmesia vulgaris), and many other succulent
wild plants and leaves as fertilizer were used in rice nursery in the hills and mountain
of Nepal. In situ manuring by halting flocks of animals on different fallowland and
shifting animal sheds during winterwas practised in the early Nepalese agriculture. One
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24-25 March 2015
crop in a season was sufficient to feed the people. Then there was massive flood in the
hills and mountain in 1954 (2011 BS) that took many lives and properties leading to
widespread famine in Nepal. Specially suffered were the people in western hills. The
Government of India and United States of America supported Nepalwith food aid. The
following years instead of food,these countries assisted Nepal in the form of fertilizers.
Ammonium sulphate, single superphosphate and muriate of potash were imported
through Tribhuvan Gram VikashSamiti an integrated rural development program that
ran from 1952 (FAO 2010, Gurung 2011). This fertilizer aid coincided with Malaria
Eradication Program in the Terai and river valleys. Soil survey started to understand
the soil fertility to resettle the flood and landslide victims. Rapti Valley Development
Program was one such area where these flood victims were resettled and modern
agriculture was practiced using improved crop varieties and fertilizers.
Work in soil science started earlier but actual recognition was in 1957 when Soil
Science Section was set up as a unit under then Department of Agriculture. This unit
conducted soil sample analysis and soil fertility experiments. Later units such as soil
survey, soil physics, soil microbiology, plant nutrients, and recently GIS and remote
sensing were added. Soil scientists were posted to Khumaltar and Parwanipur
Agricultural Station only. In 1972more soil scientists were added to Bhairawa
Agricultural Station, Khajura Agricultural Station, Tarahara Agriculture Farm,
Rampur Agricultural Station and Janakpur Agriculture Farm. Farms established for
specific purposes of agricultural development felt the lack of soil scientists and
recruited additional soil scientists in their command area.Such farms and stationswere,
GADP Khairenitar, JADP Nakatajhij, Agriculture CenterLumle andPakhribas, and
Hill Agriculture Station Kavre. Other farms and stations having soil scientists were
Agricultural station Doti, Jumla Agricultural station, National Citrus Development
Program Paripatle, Kirtipur Horticulture station and Malepatan Horticulture Farm,
Tobacco Development Program to handle problems related to soil science. The farms
and station were assigned to take care of soil fertility experiments mostly variety cum
fertilizer trials and collected soil samples for analysis and sent to Khumaltar. Soil
laboratory at Khumaltarwas overloaded and hence additional soil labs were setup in
some of the farms and stations such as Parwanipur, Tarahara, Rampur,Khajura,
Bhairawa, and Khairenitar and later Lumle Agriculture Centre and
PakhribasAgriculture Centre. After the partition of DoA and NARC additional soil
laboratory were set up. NARC concentrating in soil related to research and DoA in
development activities such as providing soil analytical services. The soil laboratories
that DoA owns presently are, at Surunga (Jhapa), Jhumka (Sunsary), Hetauda
(Makawanpur), HariharBhawan (DOA Lalitpur), Pokhara (Kaski), Nepalganj (Banke)
and Sunderpur (Kanchanpur) with soil scientists and required staffs. Service provided
by these government laboratories can sufficiently cater the needs of the farmers if all
of them run properly. As the soil laboratories of the government could not cater the
need of soil samples analysis some private soil laboratories are also set up in
Kathmandu Valley and outside as well.
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24-25 March 2015
Human resources in soil science
The public profile of soil science and soil scientists in Nepal including other countries
is on a level of soil profile which is under ground and largely invisible. If we look into
the international organisation some soil scientists have hold highest positions in
International Organization such as World Bank, International Union of Scientific,
International Agricultural Research Institutes such as, ICRISAT, IRRI etc. These soil
scientists also have received prestigious award such as Nobel Prize as mentioned by
White (1997). Nationally when we look into the higher positions that our soil
scientistshad held were Director General of Department of Agricultureand Deputy
Director General(DoA), Joint Secretary (MoA/D), Executive Directorand Drectors
(NARC), the Dean of Institute of Agriculture and Animal Science and Dean of Institute
ofForestryPokhara (TU) but very little work has been done to persuade the general
public as well as the government to save the soil and create several posts of soil
scientistwhereas there is need of soil scientists in every districts and regions if we have
to save the soil and maintain sustainable food production in the country. It is ridiculous
that the Government of Nepal recruits fertilizer inspectors with no knowledge of
fertilizers and soil fertility from other faculties rather than soil. Another example of our
inability is; knowing that major soil is lost from cultivated land and soil conservation
activity is needed in upland cultivated field, the Department of Soil Conservation is
under the Ministry of Forest. As a result some other professionals have blowing our
trumpet in their rhythm.
With the limited number of soil scientists we have implemented soil and fertilizer
related programs, train technicians as well as farmers in balance use of fertilizers for
higher crop yield and soil management. But there is a tendency that farmers forget soil
fertility management when the program is terminated. This is mainly due to lack of
monitoring and the need is very badly felt. There were ample opportunities to create
posts of soil scientists and extend our activities to each and every district but it has not
been possible. Now scientists working in soil science have been decreasing every year.
It may be due to government and society is ignorant on the importance of soil in our
country. The same situation is everywhere. This has been one of the concerns of
International Union of Soil Science (IUSS) as well.
In the developed world, soil science as a discipline has been slowly amalgamated into
other disciples such as crop science, geology and environmental sciences mainly due to
less numbers of students interested in soil science. This could also be because they
have completed basic soil studies of their land and well recorded. Now they are
diverting their soil related studies through agronomic, environment and their relation to
the human’s health. Though the numbers of soil scientists in the world is lower by
40%(Baveye et al. 2006), the research publications in soil science are increasing
exponentially (Hartemink and McBratney 2008)indicating the importance of soil
science. In Nepal, number of soil scientists and students in soil science are diminishing
even though we have hardly have completed any work in saving our soils. It could be
due to less attention of the Government of Nepal in the care and management of soil
19
24-25 March 2015
and land use. But the Ministry of Land Reform and Development is using soil
pedology and soil fertility evaluation as a major component in its land use
zoningprogram country wise.There is high demand of soil science activities to save the
most fragile mountain ranges in the world which is increasingly threatened by large
scale human activities. Extensive deforestation and intensive farming on steep slopes,
heavy population pressure on natural resources have resulted in overall environmental
degradation (Shengji and Sharma 1998). Land degradation is increasing every year
acted by various agents in Nepal which is presented in Table 1.
Soil Science works atKhumaltar before formation of NARC.
From the beginning of inception of soil science as a unit, it started working in soil
analysis and soil sample collection. Later, soil fertility experiments in cereals
especially rice, wheat and maize were conducted and presented in some of the
workshops organised within the Department of Agriculture. During 1965 there had
been an expert in soil science from UNDP/FAO which supported and guided the
Nepalese soil scientists in soil survey and mapping including soil and water analysis.
This strengthened soil analytical service as all the members of soil survey including
soil fertility experiment carried out soil sample analysis themselves. This assured
quality of analytical results. Soil survey of most of the districts in Terai and Siwaliks
were completed including some of the important hills and mountain districts such as,
Andhikhola valley of Syangja, Pokhara valley, later, all Gandaki and Dhaulagiri
Zones. But very few reports were published.
In 1963 Dr. N. Borlaug came to India to implement his Green Revolution. This
revolution revolutionised fertilizer, seeds plant protection chemicals, agricultural
machineries, and water use. Intensive use of High Yielding Crop Varieties and NPK
fertilizers including maximum use of water in irrigation, crop production increased no
doubt but this project never paid any attention to soil biodiversity, micronutrients
exhaustion, water pollution including other environmental concerns that is
deteriorated due to soil mining and effect of pesticides in downstream ecology.
Activities of GreenRevolution were introduced in Nepal. Some improved varieties of
wheat such as Lerma Roho 52 were already introduced. As influenced by Green
Revolution DoAlaunched an UNDP special project namely “Increase Use of High
Yielding Crop Varieties and Fertilizer” (NEP-12, 1970-75). This project concentrated
on improvedvarieties of rice, wheatand maize where NPK fertilizerwas applied in
conjunction withirrigation. Several trials and demonstrations were conducted in the
districts of Narayani and Bagmati Zones. NEP-12 impacted positively in the Terai
districts but not much in the hills. Remarkable impact of this project was a report of
reconnaissance soil survey of Bagmati and Narayani zoneof the project area. This was
the only reconnaissance level soil survey report and still a good reference for the study
of soil science of this area. For the hills another FAO supported project named FRIP
was launched in 22 hill districts of western, Central and Eastern Regions from 19821992. Similar activities of NEP-12 were replicated. This project came up with site
specific recommendation of NPK fertilizers for rice, wheat, maize and potato.
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24-25 March 2015
Fertilizer did not respond well in absence of irrigation and hence International
organizations such as FAO/UNDP, ADB, The World Bank and many other multilateral
and bilateral projects supported Nepal in water use and constructed large irrigation
schemes. Many of these projects had feasibility and pre-feasibility studies and prepared
soil maps for their own use. Government soil scientists have very little knowledge of
them. In addition foreign universities have conducted academic as well as nonacademic researches on soil science and related fields in scattered way. Nobody in
Nepal including the Ministry of Agriculture has any knowledge ofthem. Most of the
irrigation projects kept one demonstration farm within each irrigation project which is
later handed over to the DoA to carry out demonstration to farmers and produce quality
seeds. Jhumka is one of such farm in the command area of Morang-Sunsary Irrigation
Project. Later DoI implemented feasibility studies of major and minor irrigation project
where soil survey was obligatory. But most of the Irrigation Engineers did soil survey
and made soil maps as they like.
Land degradation is one of the greatest challenges facing mankind and Nepal is no
exception. Anthropogenic causes such as deforestation, excessive use of agro-chemical
including fertilizers, overgrazing, construction works and unscientific farming in the
hills have resulted in erosion of top soil, loss of flora and fauna, occurrence of
landslides in the hills and flooding in the plains. This has led to severe environmental
degradation leading to poor socio-economic conditions and disruption of natural
ecosystems. In general the Department of Soil Conservation and Watershed
Management reports that about 11 % of the total land of Nepal is degraded. It shows
that total of 7.5 million ha of land is in the verge of degradation (Table 1).
Major soil loss is from the cultivated/agricultural fieldmainly due to faulty cultivation
practicessuch as cultivation in steep slopes. Slash and burn cultivation practice is
another example. In this practice surface organic debris is burnt where surface soil
including soil organic matter is also burnt exposing to massive soil erosion.
Table 1: Land Area under Some Kind of Degradation in Nepal.
S.No.
Land use category
1. Poorly managed forest
3. Poorly
managed
slopping terraces
5. Degraded
rangeland/open land
7. Area damaged by
floods and landslides
(1984-2003)
9. Forest encroachment
11. River bank cutting
Degraded
area, million
ha
2.100
S.No.
2.
Land use category
0.290
4.
Slumping
gullying
Mass wasting
0.647
6.
Wind erosion
0.106
8.
Flood and
logging
10.
12.
Water logging
Total
Degraded
area, million
ha
and
0.4244
0.116566
0.4249
0.119
1.6398
Source: MOEST, 2006
21
water
0.8987
0.7279
7.494266
24-25 March 2015
Nepalese Soil Science at present
Presently soil survey is digitised and computer aided programmes are used to prepare
maps with the help of GPS, much easier than previously used hard copy of topo-sheet
and aerial photos as base maps. In the laboratory in highly expensive equipment such
as AAS, DCP, ICP and CNS analyser are used in detection of elements. In a short span
of time a soil survey report with digitised map can be prepared.
Fertilizer experiment is a major work at soil science in NARC. Some initial work in
fertilizer use efficiency was also started. Chemically and biologically testing of some
fertilizer products are some of the activities. Digitising some of the previous soil
survey work and participatory fertilizer experiments are other activities, whereas soil
science in DoA is mainly concentrating soil fertility evaluation and mapping at the
district level and providing soil analytical service to farmers. Soil Service Directorate
is also involved in helping MoAD in formulating fertilizer policy.
Soil fertility evaluation is also done from some other agencies such as Ministry of Land
Reform and Development. A study carried out from the 8 districts from the Terai,
Siwaliks and found that most of the soil nutrients except K2O are low. Soil organic
matter content in all the districts is low except Kathmandu and Lalitpur (Table 2).
Table 2: Soil fertility evaluation of some of the soils in the 8 districts of Eastern,
Western, Mid and Far-Western Region of Nepal.
Morang
Surkhet
Nawalparasi
Bara
Banke
Lalitpur
Kathmandu
Kailali
PH
Total N,
%
P2O5,
kg ha-1
K2O,
kg ha-1
OM,%
SAND,%
CLAY,%
SILT,%
5.99
5.89
7.53
7.50
6.89
5.95
5.62
7.27
0.05
0.05
0.09
0.05
0.08
0.19
0.22
0.10
0.43
0.47
60.55
1.13
29.78
60.39
48.19
32.39
63.74
108.42
117.95
22.63
121.53
451.74
346.70
120.80
1.42
2.37
1.65
0.50
1.30
5.82
4.37
1.84
46.46
31.42
25.24
56.2
34.37
30.58
63.29
37.48
8.12
16.55
17.28
3.50
18.52
11.56
4.97
14.96
45.54
50.21
57.41
40.30
47.11
57.89
31.35
47.36
Source: Compilation of researcher’s own work.
Soil study carried out by education institutes
The oldest agricultural Institute (IAAS) of TU where master in soil science program is
started lately and students conduct Master Level thesis research mostly in the
agronomic studies. Some academic studies are also related to soil erosion and
conservation including micronutrients but all are agronomical studies.
Institute of Forestry of TU also offers master degree in forestry where graduate
students carry out research. They concentrate mostly on soil conservation whereas
students at Kathmandu University (KU) carryout research on environment science.
Numbers of foreign universities also have conducted thesis research and/or
collaborative projects with Nepalese counterparts but we have very few records.
22
24-25 March 2015
Carbon mapping studies, LikhuKhola Watershed studies and many others are some of
the examples. Some of the principal researchers have published the results on their
own. There is nothing left with us for reference. Professors and students from
European universities have the same system. Some of them do not even employ local
collaborator. This is most provably due of lack of government policy and
documentation centre with NARC and/or DoA.
Future soil science in Nepal
Soil science can be looked through the eyes of health and hygiene in the society.
Diseases pathogen such as helianthus organisms and other worms can house in the
soils and easily contaminate humans. Presence of radon causing cancer relates to the
poorly drained soils increasing infant mortality (Oliver 1997). We have no
knowledgeabout health risk of poorly drained soils whereas most of our town in lower
plains are flooded every year.Excess of micronutrients and heavy metals such as
aluminium, arsenic, cadmium, copper, fluorine, iodine, lead, selenium, thallium and
zinccan be toxic when they contaminate food.Examples include Keshan disease caused
by selenium deficiency, and itai-itai disease caused by excess cadmium. Likewise
deficiency of boron might lead to joint pain in elderly people(Nielsen and Meacham
2011). "Arthritis is caused by mineral deficiency - boron in particular."(Newnham
1994).Likewise soil deficient in micronutrients results in lowplant uptake which
ultimately creates micronutrients deficiency in human. Likewise selenium is found
beneficial in HIV Aids treatments. We have done some work and found that most of
the micronutrients are deficient in Nepalese soils (Karki et al. 2005). These
deficiencies might have consequences on the health of our people. Though we cannot
take right turn and start these activities right away but some thoughts need to be given
on how we can increase these nutrients in food throughbiofortification.Biofortification
of micronutrients could help improve health condition of infants, child and pregnant
women (Bouis and Welch 2010). Similarly there are other avenues that need to be
explored.
Recommendation
There are ample areas where soil scientists need to do alot. The followings are some of
the recommendations:
1. It is so unfortunate that so far Nepal do not have soil map of the country.
Government should initiate to restart the soil survey and mapping activities;
2. Due to cultural and economic reason land is abandoned leaving fallow is on
the rise mainly because farmers not getting economic results from it. Efforts
must be made and follow a good environmental ethics to care the soils and get
economically sustainable yield;
3. We are facing acute shortage of food leading to acute food insecurity and the
demand poses a huge challenge. Meeting food security is priority but let us not
irreversibly degrade our land. We have to improve yield without
compromising environmental integrity or public health. We have to try
23
24-25 March 2015
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
reducing hunger improving nutrition and thus the ability of people to better
reach their mental and physical potential.
The policy of the government should not only concentrate on food production.
To produce maximum yield care should be taken by maintaining environment
and minimising greenhouse gas emission.
Because of privatisation of fertilizer, many types of untested fertilizing
materials are available in the market. Farmers use them invariablyevery season
and to every crop. As observed in the field, some of the fertilizer elements
have shown toxicity. Therefore it is suggested that cropping system nutrient
balance be checked and monitored regularly.
In the developing countries core soil science study has been completed and
now they are diverting agronomic use of soil science and soil science for
health of the people. We cannot take right turn and take these steps but should
think in that line as well.
The way soil is over exploited as means to increase food grains and other
biomass production. Before it is too late, let us work hard and convince the
society that proper attention should be given to restore soil fertility and soil
health so that soil providessustainablegoods and services.
In view of shortage of students to study soil science in the universities and in
the fields, serious thought needs be given to popularise soil science in
education, research and development.
Different soil testing laboratories are following various methods to analyse,
soil, plant, fertilizer and water samples for agricultural use. Harmonising soil
analysis procedures is very much needed.
Soil is the source of pathogen as well as source of medicines and plant
nutrients. Sufficiently supply of microelement to soil and uptake by crops
could minimise health and hygiene of infant and pregnant women such as Zn
and B.
Our soil microbiology has been so far limited to Rhizobium culture only. We
could move forward and isolate useful organisms from our soil.
Our Farmers use quite large amount of fertilizers. Research results are
inadequate wheather applied nutrients are efficiently utilized. Therefore, time
has come to study Nutrient use efficiency.
Communication is soil science is limited. Exchange of information between
research, education and development is necessary.
Acknowledgement
I would like to extend my sincere thanks to organising committee in giving me this
opportunity to share my feelings with you all.
24
24-25 March 2015
References
Baveye P, AR Jacobson, SE Allaire, JP Tandarich and RB Bryant. 2006. Whither goes
Soil Science in the United States and Canada? Soil Sci.171, 501-5188.
Bouis HE and RM Welch. 2010. Biofortification- A Sustainable Agricultural Strategy
for Reducing Micronutrient Malnutrition in the Global South. Crop Sci.50, S20-S-32.
FAO. 2010. Agricultural Extension Services Delivery System in Nepal. Pp. 47.
Kathmandu: Food and Agriculture Organization (FAO).
Gurung N. 2011. Local Democracy in the Political Transition of Nepal. Pp. 18: South
Asian Institute and Alliance for Social Dialogue.
Hartemink AE and A McBratney. 2008 A soil science renaissance. Geoderma 148 123129.
Karki KB, DP Sherchan and RC Bhandari. 2007. Residual effect of organic and
inorganic fertilising materials especially NO3 (nitrate) in different crops under
different agro climatic condition In National Seminar on Organic Agriculture.
Pp. 7. Kirtipur, Kathmandu: Department of Agriculture, GoN.
Karki KB, JK Tuladhar, R Upreti and SL Maskey. 2005. Distribution of micronutrients
available to plants in different ecological regions of Nepal. In: Micronutrients
in South and South East Asia. PT Andersen, JK Tuladhar, KB Karki and SL
Maskey (eds.). Pp. 17-29. Kathmandu, Nepal. ICIMOD/NARC/ Bergen
University, Norway.
Newnham RE. 1994. Essentiality of Boron for Healthy Bones and Joints.
Environmental Health Perpectives. 102 (Suppl 7)83-85
Nielsen FH and SL Meacham. 2011. Growing Evidence for Human Health Benefits of
Boron. J. of Evidence-Based Comple. and Alternative Medicine. 16, 169-180.
OECD_FAO. 2011 Agricultural Outlook 2011-2020. In: G-20 Summit. Seol, Korea.
Oliver MA. 1997. Soil and human health: a review. Euro.J. of Soil Sci. 48, 573-592.
Shengji, P and UR Sharma. 1998. Transboundary biodiversity conservation in the
Himalayas. In: Ecoregional co-operation for biodiversity conservation in the
Himalaya In International meeting on Himalayan ecoregional cooperation. Pp.
199. Kathmandu: UNDP/WWF/ICIMOD.
Singh K. 2011. Tragedy of the Global Commons: Causes, Impacts and Mitigations.
Anand, Gujarat, India: India Natural Resource Economics and Management
(INREM) Foundation
White RE. 1997. Soil Science: raising the profile. Aust, J. Soil Res. 35, 961-977.
Young A. 1999. Is there really spare land? A critic of estimate of available cultiviable
land in developing countries.Environment Development and sustainability1, 318.
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24-25 March 2015
TH-3
Soil Degradation and its Management
Bhaba P Tripathi
IRRI-Nepal Country Office Singha Durbar Plaza, Kathmandu, Nepal
Abstract
Soil is the most important natural resource for all kind of living beings (plants, animals
and organisms). Soil has been degraded over years. Degradation of soil resources include
soil erosion by water and soil fertility decline (deterioration in soil physical, chemical
and biological properties). The major processes involved in the soil fertility decline are
the lowering of soil organic matter, degradation of soil physical properties (structure,
aeration, water holding capacity), reduction in the availability of major nutrients
(nitrogen, phosphorus and potassium), micronutrient deficiencies, and development of
nutrient imbalances as well as acidification through increased use of nitrogen fertilizer
alone.
Sloping topography, heavy seasonal rainfall and predominance of erosion prone soils and
human factors (intensive cultivation of land and erosion prone farming are the main
causes of soil losses and fertility decline in the mountains of Nepal. Various studies
carried out in Nepal showed that soil loss through surface erosion from agricultural lands
varies from less than 2 t ha-1 yr-1 to as high as 105 t ha-1 yr-1. Losses through leaching are
higher than nutrients losses through surface runoff. Reduction of soil erosion, use of
legume and cover crops, mulching, successful introduction of agro-forestry systems and
effective use of organic wastes are the components of environmentally sustainable
farming system.
Various field studies in continuous intensive cropping systems depicted that crop yield
loses and fertility decline have been recorded due to imbalance chemical fertilizer
applications. Long-term fertility trials carried out in different agro-climatic conditions of
Nepal confirmed that combination of organic and inorganic sources of fertilizers have
sustained crop productivity and maintained soil fertility in the long-run. Secondary
macro-nutrients (calcium, magnesium and sulphur) and micro-nutrients (boron, zinc,
molybdenum) deficiencies have been recorded in cereals (rice, maize and wheat) as well
as in legumes (lentil and chickpea), oilseeds, vegetable crops (cauliflower, cabbage and
radish) and fruit crops particularly citrus in the acidic soils of Nepal. Deficiencies of
these nutrients can be corrected with the amendments of agricultural lime and/ or organic
fertilizer as well as application soil or spray of micro-nutrient compounds for eN hancing
crop productivity.
Keywords: Agro-forestry system, crop productivity, degradation of soil resources.
Introduction
Soil is a dynamic natural body on the surface of the earth and is a critical resource for
supporting plant growth. It is composed of minerals, organic materials and living forms
and provide the necessary nutrients to the growing plants. Mismanagement and
indiscriminate use of soil and water resources result in land and environmental
degradation and may prove disastrous for humankind as well as animals. Therefore,
26
24-25 March 2015
judicious management and conservation of soil and water is essential for sustainable
productivity and environmental benefit.
Soil degradation through the loss of top soil is one of the major factors of low and
unstable crop yields. The middle mountain region (mid-hills) is the largest, occupying
about 30% of the total land area, and has the highest population density per unit of
cultivated land (Carson 1992 Maskey 2003). Much of the country’s land base is
environmentally fragile and susceptible to erosion and degradation. Cultivated on
sloping and terraced land is a common feature of Nepalese hill agriculture.
The agricultural land holding in the hills is very small-about 45% of the population
owning less than 0.5 ha of land- and highly fragmented with about 4 parcels per
holding (CBS 2004). Crops are cultivated mainly on rainfedupand, locally called Bari
land. Bari land constitutes 64% (1,717,000 ha) of the cultivated land in Neal, of which
61%lies in the middle hills alone (Carson 1992). Maintaining of Bari land is, therefore,
critical to the Nepalese population. Moreover, Bari soils are decreasing in fertility and
vulnerable to soil losses through a combination of natural factors, such as sloping
topography, heavy seasonal rainfall and predominance of erosion prone soil; and
human factors such as intensive cultivation of land erosion-prone farming practices
(Sherchan and Gurung 1992, Tripathi 1997).
Various studies conducted in Nepal show that soil loss through surface erosion from
agricultural land in the hills varies from less than 2 t ha-1 yr-1 to as high as 105 t/ha/yr
(Gardner and Gerrard 2003). However, Gardner et al. (2000) revealed that nutrient
losses through leaching exceed those in runoff and soil erosion, in contradiction to the
widely held believe that erosion losses are the major reason for declining soil fertility
and crop productivity in the Middle Hills of Nepal (Carson 1992, Turton et al. 1995;
Vaidya et al.(1995). Several studies have established that farmers in the middle hillsof
Nepal possess good knowledge about soil and water-related ecological processes and
they often make rational use of them to devise practice to combat the problem of soil
erosion and declining soil fertility (Gill 1991, Tamang 1991and 1992, Carson 1992,
Joshi et al. 1995, Nakarmi 1995, Shah 1995, Subedi and Lohar 1995, Joshy 1997,
Turton et al. 1995, Turton and Sherchan 1996. However, Gardner et al. (2000),
Gardner and Gerrard (2003) and Pilbeam et al. (2004) suggest that the soil erosion is
not a major loss of soil nutrients. Pilbeam et al. (2004) concurred and suggested that
from a fertility standpoint, the farming systems were sustainable, for a low level of
productivity, as losses in erosion were compensated by inputs from fodder recycled
through livestock.
One of the major contributing factors to decline soil fertility in Nepal is soil
acidification (Turton et al. 1996) and covers approximately 49% of the total
geographical area (Sherchan and Gurung 1996b). Tripathi (1999) reported that there
are five major causes of development of soil acidity in Nepal.
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24-25 March 2015
Types of Soil Degradation Nepalese hill ecosystem
The followings are the types of soil degradation:
i. Soil erosion by water: This is removal of soil particles by action of water, usually
seen as sheet erosion or gully erosion. One important feature of soil erosion by
water is the selective removal of finer and more fertile fraction of soil.
A total of 55.3 million ha land is affected by water erosion in south Asia region,
out of which 18.2 million ha with light erosion, 23.7 million ha with moderate, and
13.5 M ha strong erosion excluding dry zone and humid zone of this region. In
Nepal, 34% of the total land is affected by erosion (Young 1994).
(a) Soil Loss: Mean soil losses of three years (1997-1999) from different plots were
1.53 t, 7.29 t and 1.32 t ha-1 with mean of 3.38 t ha-1 at Bandipur, 4.21 t, 2.26 t, and
0.97 t ha-1 at Landruk with mean of 2.48 t ha-1and 4.36 t, 3.09 t, and 0.20 t ha-1 with
mean of 2.55 t ha-1at Nayatola site, respectively (Table 2), but ranged from 0.54 to
15.39 t ha-1, 0.64 to 5.86 t ha-1and 0.09 to 10.42 t ha-1at Bandipur, Landruk and
Nayatola sites, respectively. The largest soil lossof 35.40 t ha-1at Bandipur site in
1998 was due to collapse of terrace riser with high volume water in the infertile
soil of maize-fingermillet cropping system.
The above result showed that soil losses are not very alarming in the western hills.
However, it is noted that water run-on, slope angle, soil type, ground cover and soil
fertility status play an important role for soil losses in the hill slopes of Nepal.
Degree of Degradation: (a) light: Some what reduced agricultural productivity, (b)
moderate: Greatly reduced agricultural productivity, (c) strong: Un-reclaimed the farm
level major engineering works are required.
Table 1: Mean soil losses (t ha-1) in three different sites for 1997 to 1999.
Year
Bandipur, Tanahu
1997
1.53
1998
7.29
1999
1.32
Mean
3.38
Range
0.54-15.40
Source: Tripathi et al. (2001)
Landruk, Kaski
4.21
2.26
0.97
2.48
0.64-5.90
Nayatola, Palpa
4.36
3.09
0.20
2.5
0.10-10.4
(b) Nutrients loss dissolved in run-off water: : Mean losses of NO3-N, P and K
dissolved in run-off water were 1.15 kg, 3.45 kg, 7.36 kg-1 in Bandipur site; 0.62
Kg, 1.46 kg, 7.54 kg-1 in Landruk site; and 0.23 kg, 0.89 kg and 3.01 kg-1 in
Nayatola site (Table 3)
28
24-25 March 2015
Table 2: Mean losses of nitrogen, phosphors and potassium (kgha-1) in dissolved
run-off water in three different sites from 1997 to 1999.
Nutrients
Bandipur, Tanahu
Landruk, Kaski
Nayatola, Palpa
NO3-N
1.15
0.62
0.23
P
3.45
1.46
0.89
K
7.36
7.54
3.01
Source:Tripathi et al. (2001)
(c) Leaching loss of nutrients): Mean leaching losses of NO3-N, P and K in three years
were 10.20 kg, 21.10 and 44.90 kg-1in Bandipur; 53.00 kg, 8.70 kg and 114.50 kg1
in Landruk; and 34.00 kg, 9.70kg, and 70.00 kg-1in Nayatola site (Table 4).
Variation of run-off and leaching losses of these nutrients were recorded within
and among sites in all the years. Leaching losses of above nutrients were quite high
as compared to run-off losses.
Table 3: Mean leaching losses of nitrate nitrogen, Phosphorus and potassium (kgha-1)
three sites from 1997 to 1999.
Nutrients
Bandipur, Tanahu
Landruk, Kaski
Nayatola, Palpa
NO3-N
10.20
53.00
34.00
P
21.10
8.70
9.70
K
44.90
114.50
70.00
Source: Tripathi et al. (2001)
Measured concentrations of nutrients in eroded material and in the soil were not
comparable. For organic carbon C, total N, available P and exchangeable K,
concentrations were higher in the eroded sediments than they were in the bulk soil
(Table 5). It is apparent that the higher nutrient levels in the eroded sediments were as
a result of preferential erosion of finer silt particles, and the higher nutrient sorption on
such particles (Brady and Weil, 2002). Looking at the variation in particle size
distribution (texture) within plots, there was an accumulation of silt at the bottom of
the plots, resulting in higher sand and clay contents in the middle and at the bottom of
the slopes (Table 6).
Table 4: Nutrient content of soils and eroded sediments in 2002 in Nayatola, palpa,
Nepal.
Organic
(g ha-1)
Total
(g kg-1)
Available
(mg kg-1)
Exch.
(mg kg-1)
Maiza+
Ginger
Soils
Maize +
Legume
SED
Maiza+
Ginger
Eroded Sediments
Maize +
Legume
Control
Control
SED
10.90
11.60
10.95
1.40
16.60
15.20
2.50
1.40
1.30
1.32
0.10
2.20
1.90
28.80
31.40
27.30
1.00
37.30
29.70
42.10
6.91
160.80
127.70
165.70
8.90
232.40
216.00
264.30
125.70
C
13.00
N
2.20
0.20
P
K
Source: Acharya et al. (2008)
29
24-25 March 2015
Table 5: Variation of soil texture with plot portion in 2002 in Nayatola, Palpa.
Top
Middle
Bottom SED
Sand (g kg-1)
387.30
389.40
371.10
9.70
Silt (g kg-1)
392.50
395.10
417.50
9.30
Clay (g kg-1)
220.20
215.60
209.40
5.30
Source: Acharya et al. (2008)
ii. Soil erosion by wind: This is the removal of soil particles by wind action. Usually
this is sheet erosion, where soil is removed in thin layer. Wind erosion most easily
occurs with fine to medium size sand particles.
iii.Soil fertility decline: This is degradation of soil physical, biological and chemical
properties. Erosion leads to reduced soil productivity:
a. Reduction in soil organic matter with associated decline in soil biological
activity’
b. Degradation of soil physical properties as a result of reduced organic matter
(structure, aeration and water holding capacity may be affected).
c. Changes in soil nutrient leading to deficiencies or toxic level of nutrients
essential for healthy plant growth.
d. Build up of toxic substances, for example pollutions or incorrect application of
fertilizers.
Macro-nutrients Deficiency in Continuous Cereal system
Long-term experiment conducted in rice-rice-wheat system in the alkaline soil (pH
>8)of Bhairahawa since 1978 indicated sharp yield decline in the absence of
phosphorus particularly in early rice and yield came down to zero by5th year of the
experiment. In later years, potassium also became limiting and yield reduced in minus
K treatment to greater extent in all the three crops (Regmi et al. 2004).
Micro-nutrients Deficiency
Karki et al.(2005) reported that soil contained high amount of Mn, and Zn but low
amount of Cu, Fe and B in high Himalaya region of Nepal. In mid hills of western
region, all of these elements were except Fe. In inner Teari (Chitwan), B and Zn
contents were low, whereas Cu, Fe and Mn were high. In the Terai, Cu, Zn and Mn
contents were low to medium but Fe content was high. Boron in the eastern Terai has
been found creating sterility problem in wheat.
30
24-25 March 2015
In chitwan valley, deficiency of micro-nutrients (B, Mo, zn) were found in legume
crops (chickpea, lential and pigeon pea) and oil seed crop (mustard). Yield responses
were widespread but variable, but responses up to 560% in chickpea and 360% in
mustard were recorded. Responsiveness decreased with increasing soi organic matter
content (Srivastava et al. 2004).
Micronutrients particularly B and Mo deficiency were found in cauliflower. Adding 20
kg B ha-1 increased 45% higher yield of cauliflower (Regmi et al. 2004).
Nutrient status in mandarin growing pockets:
In the hills of Nepal, mandarin is cultivated in the form of kitchen garden as well as in
the form of orchards from 650 to 1400 m above sea level . It is successfully grown in
47 districts out of 75 districts of Nepal and every year there is increase in the cultivated
area and fruit production.
Survey of mandarin growing areas and leaves analysis result revealed that majority of
the trees had deficient content of N and adequate contents of P and K. Among
micronutrients, Fe and Cu were found medium to high and very high ranges. At almost
all sites, the trees had deficient content of B and Zn (Tripathi and Harding 2001).
Management of Soil Degradation
The followings are the different soil management options, which can be adopted by
farmers depending on the availability of the locally available resources:
• Soil erosion can be minimized by diverting rainwater to the streams by making
ditches.
• There is practice of diverting pre-monsoon rainwater in the rice fields to add
organic matter and nutrients, which are coming from the fertile uplands.
• Addition of Farm Yard manure (FYM)/ compost made from the waste
materials and forest leaf litters.The quality of FYM/compost can be eN hanced
by covering them with locally available materials for protecting them from
volatilization losses through direct exposure to sun and leaching losses. FYM
can be used for producing bio-gas as fuel and its slurry rich in nutrients can be
used as organic fertilizer to different crops.Vermi-composting is another way
of producing organic fertilizers, which is becoming popular in Nepal in recent
years.
• Integration of green manure crops in the cropping system adds organic matter
and other nutrients in soil.
• Planting hedge row in the uplands minimizes water runoff and biomass of
hedge row crops can be incorporated in the soil for adding organic matter.
• Mulching with locally available organic materials acts as barrier not
allowingrainwater to come to direct contact of soil and decreases soil loss
during raining season as well as slowly decomposes the mulching materials
and adds organic matter and other plant nutrients in the soil.
• Use of bio-fertilizers
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24-25 March 2015
•
•
•
•
•
•
•
Planting of cover crops
Strip cropping of maize and legume crops
Integration of legume crops in crop rotation/mixed cropping
Balanced use of Chemical fertilizers
Combination of organic and inorganic fertilizers
Use of agricultural lime in the acidic areas
Use of different micro-nutrient compounds for correcting micro-nutrients
deficiencies.
Conclusion
• Variation of soil loss due to soil erosion
• Losses of nutrients high in sediments (organic molecules)
• Leaching losses of nutrients more then runoff
• Macri-and micronutrients deficiencies in cereals, legumes, oilseed crops and
citrus trees
• Soil acidity is one of the major problem
• Farmers have good knowledge of soilloss assessment
• Different options of soil management practices recommended
References
Acharya GP, BP Tripathi, RM Gardner, KJ Mawdesley and MA McDonald. 2008.
Sustainability of sloping land cultivation systems in the mid-hills of Nepal.
Land Degrad. Develop. 19: 1-12 (2008).
Brady NC and Weill RR. 2002. The Nature and Properties of Soil (13 edn.). Prenticehall, New Jersey. 960 p.
Carson B. 1992. The land, the farmer and the future: a soil management strategy for
Nepal. ICIMOD Occasional Paper No. 21, ICIMOD, Kathmandu, Nepal.
CBS. 2004. Nepal Living Standards Survey Report, 2003/4. Volume 2. Central Bureau
of Statistics: Kathmandu, Nepal.
Gardner R, K Madewsley, BP Tripathi, SGaskin and S Adams. 2000. Soil erosion and
nutrient loss in the mid hills of Nepal (1996-1998). ARS Lumle, Soil Science
Division, NARC, Khumaltar and Quen Mary and Westfield College,
University of London, UK. 57 p.
Gardner RAM and AJ Gerrard. 2003. Runoff and soil erosion on cultivated rainfed
terraces in the Middle Hills of Nepal: Applied Gography 12: 23-45.
Gill GJ. 1991. Indigenous erosion control technquesin the Jhikhukhola watershed. In
Soil Fertility and Erosion Issues in the Middle Mountains of Nepal. PB Shah,
H Schreier, SJ Brown, KW Riley (eds.). ICIMOD: Kathmandu, Nepal. Pp.
152-164.
Joshi KD, JK Tuladhar and BR Sthapit. 1995. Indigenous soil classification systems
and their practical utility: a review: Pp. 36-42. In: Proc. of Workshop.
Formulating a strategy for soil fertility research in the hills of Nepal. Held at
Lumle. Joshi KD, AK Vaidya, BP Tripathi, B Pound (eds.). Agricultural
Research Centre, Nepal. 17-18 August.
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Joshy D.1997. Indigenous technical knowledge in Nepal. Indigenous technical
knowledge for land management in Asia. Paper presented at the assembly for
the Management of Soil Erosion Consortium, (Nan, Thailand, 28 January-2
February 1997). Bangkok, Thailand: IBSRAM, 1998. Issues in Sustainable
Land Management.
Karki KB, JK Tuladhar and SL Maskey.2005. Distribution of plant available
micronutrients in different ecological regions of Nepal. Pp. 17-29. In : Proc. of
an International Workshop. P Andersen, JK Tuladhar, KB Karki and SL
Maskey (eds.). Micronutrients in South and South East Asia. Held 8-11
September 2004, Kathmandu Nepal. ICIMOD/NARC/ Bergen University,
Norway.
Maskey RB. 2003. Options for sustainable land management in the mid-hills of Nepal:
Experiences of testing and demonstration of contour hedgerow intercropping
technology. In: Proc. of an International Symposium held from May 21 to 24,
2001 in Kathmandu, Nepal. Pp79-84. Tang Ya and Pradeep M. Tulachan (eds).
International Centre for Integrated Mountain Development (ICIMOD),Nepal.
Nakarmi G. 1995. Indigenous water management systems in the Andheri Khola subwatershed. In Challenges to Mountain Resources Management in Nepal:
Processes, Trends and Dynamics in the Middle Mountain Watersheds, Shreier
H, Shah PB, Brown S (eds). Workshop proceedings, JhikhuKhola watershed.
April 22-25, ICIMOD, Kathmandu, Nepal. Pp. 211-225.
Pilbeam CJ, PJ Gregory, RC Munankarmy and BP Tripathi. 2004.Leaching of nitrate
from cropped rainfed terraces in the mid-hills of Nepal. Nutrient Cycling in
Agroecosystem. 69: 221-232.
Regmi BD,C Paudel, BP Tripathi, S Schulz and BK Dhital 2004.Managing soil fertility
problems in marginal agricultural lands through integrated plant nutrient
management systems: experiences from the hills of Nepal. Pp. 109-119. In :
Proc. of an International Workshop. P Andersen, JK Tuladhar, KB Karki and
SL Maskey (eds.). Micronutrients in South and South East Asia. Held 8-11
September 2004, Kathmandu Nepal.). ICIMOD/NARC/ Bergen University,
Norway.
Scheierh H, PB Shah and S Brown. 1995. Challenges to mountain resource
management in Nepal: processes, trends and dynamics in the middle mountain
watersheds. Workshop Proceedings, JhikhuKhola watershed, April 22-25,
ICIMOD, Kathmandu, Nepal.
Shah PB. 1995. Indigenous agricultural and soil classification. In Challenges to
Mountain Resource Management in Nepal: Processes, Trends and Dynamics in
the Middle Mountain Watersheds. Pp. 203-210. In: Proc. of an international
Workshop. Scheier H, Shah PB, and Brown S (eds.). ICIMOD/UBCIDRC
Workshopproceedings, Kathmandu.
Sherchan DP and GB Gurung. 1992. Soil and nutrient losses under different crop
husbandry practices in the hills of East Nepal. Paper presented at the National
Workshop of watershed management, Bhopal, India from August 24-27, 1992.
Pakhribas Agricultural Centre, Dhankuta, Nepal.
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Sherchan DP and GB Gurung. 1996b.Sustainable soil management issues in the eastern
hills of Nepal. The experience of PAC. In: Proc. of the workshop on soil
fertility and Plant Nutrient Management held at Godawari Resort, Lalitpur,
Nepal from 19-20 December 1996.
Srivastava SP, C Johansen, RK Neupane and M Joshi. 2004.Severe boron deficiency
limiting grain legumes in the inner terai of Nepal. Pp. 67-76. In : Proc. of an
International Workshop. P Andersen, JK Tuladhar, KB Karki and SL Maskey
(eds.). Micronutrients in South and South East Asia. Held 8-11 September
2004, Kathmandu Nepal.). ICIMOD/NARC/ Bergen University, Norway.6776.
Subedi PP and DP Lohar. 1995. Methods of soil fertility management for perennial
fruit crops. In Formulating a strategy for Soil Fertility Research in the hills of
Nepal. KD Joshi, AK Vaidya, BP Tripathi (eds.). Pp. 30-35. In: Proc.of
Workshop held in Lumle Agricultural Research Centre, Nepal.17-18 August.
Tamang D. 1991. Indigenous erosion control technquesin the Jhikhukhola watershed.
Soil Fertility and Erosion Issues in the Middle Mountains of Nepal. Pp. 135151. In: Proc. of workshop. PB Shah, HSchreier, SJ Brown, KW Riley (eds.).
ICIMOD, Kathmandu, Nepal.
Tripathi BP. 1997. Present soil fertility research status and future research strategy in
the western hills of Nepal. LARC Seminar Paper No. 92/2, Lumle Agricultural
Research Centre, Kaski, Nepal.
Tripathi BP. 1999. Review on acid soil and its management in Nepal. Lumle Seminar
Paper No. 99/1. Kaski, Nepal. Agricultural Research Station, Lumle.
Tripathi BP and AH Harding. 2001. Nutrient status of mandarin trees in some
mandarin growing pockets in Lamjung and Gorkha districts of Nepal. J. of the
Ind. Soc. of Soil Sci.. Vol. 49 (3): 503-506.
Tripathi BP, GP Acharya, K Madesley, S Gaskin and and S Adams. 2001. Assessment
of soil and nutrient losses from rainfe uplands (Bariland)terraces in the
Western Hills of Nepal. Paper presented at the International Symposium on
Mountain Agriculture in the Hindu Kush-Himalaya Region, 21-25 May
2001.ICIMOD, Kathmandu, Nepal.
Turton C, GB Gurung and DP Sherchan 1995. Traditional farming systems of red soil
areas: the eastern hills of Nepal. PAC Technical Paper No. 164. Pakhribas
Agricultural Centre, Dhankuta, Nepal.
Turton CN, A Vaidya, JK Luladhar, KD Joshi. 1996. Towards sustainable soil fertility
management in the hills of Nepal.Published by Lumle Agricultural Research
Centre, P.O. Box 1, Pokhara, Nepal and Natural Resources Institute, Central
Avenue, Catham Maritime Kent, ME4 4TB, UK.
Turton C and Sherchan DP. 1996. The use of rural people’s knowledge as a research
tool for soil survey in the eastern hlls of Nepal. PAC Occasional Paper No.
21.Pakhribas Agricultural Centre, Dhankuta, Nepal.
Vaidya AK, C Turton, JK Tuladhar, KD Joshi. 1995. An investigation of soil fertility
issues in the hills of Nepal with system perspective. Pp. 83-103. In: Proc. of
Workshop. Formulating a strategy for Soil Fertility Research in the hills of
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Nepal. Joshi KD, Vaidya AK, TripathiBP and Pound Bary (eds.). Held at
Lumle Agricultural Research Centre, Kaski, Nepal. 17-18 August.
Young A. 1994. Land Degradation in South Asia: its severity, causes and effects upon
the people, World Soil Resource reports, United Nations Food and Agriculture
Organization,
Rome
(available
free
on-line
at
http:www.fao.oeg/docrep/v4360E/v4360E00.htm#contents).
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24-25 March 2015
TH-4
Healthy Soils for a Healthy Life: Research Efforts and its Challenges
Shree P Vista and Bishnu H Adhikary
Soil Science Division, Nepal Agricultural Research Council
Abstract
Soil and society are two inseparable entities on this planet Earth. Soil Science provides
eyes and ears to the society to translate dreams into reality. Without soil, there is no life
and without life, there is no soil. Soil is the foundation of all living entities and the
fertility of the soil corresponds to human health. Better the fertility of soil, healthier is the
society and healthy society always maintains fertility to attain higher production and
productivity. But the quality of soil in recent decades has been declining due to
haphazard use of agro-chemicals, erosion, increase in soil acidity and inadequate
remedial measures. Soil has been polluted with contaminants, high use of pesticides and
rapid urbanization. National policies on land act and phyto-sanitary measures are very
weak to address these problems. In order to detoxify all these toxic chemicals,
phytoremediation or bioremediation, which involves use of microorganisms in
association with plant host, soil amendments and agronomic techniques rendering soil
less contaminated should be the research priority in maintaining healthy soils. Soil
Science Division, NARC, with its limited resources has been facilitating researcher to
broaden their vision but the number of projects in soil science across the country are
diminishing with slight increment in budgets. However, recently the importance of soil
has been aptly addressed in Nepal by UN and honorable Prime Minister of India posing
considerable challenges to the Soil Scientists of Nepal. Future focus of research should
address micronutrient replenishment, nanotechnology and sustainable soil fertility
management.
Keywords: Agro-chemicals, bioremediation,healthy soils, pollution, toxic chemicals.
Overview
The soil is where food begins. Soil is the basis of all food production. The qualities of
food we consume are reflected to our health. Human health status corresponds to the
status of soil quality or fertility. Before 1400 BC, it was believed that for the well being
of the people fertile soil was essential. That is why soil was classified on the basis of
fertility status in earlier days.
Soil is a natural resource. A country is known by its resources. Value of soil was aptly
pointed out by Franklin D Roosevelt through the statement “A nation that destroys its
soil destroys itself”. Similarly, Mahatma Gandhi stated the importance of soil nurturing
through his statement “To forget how to dig the earth and to tend soil is to forget
ourselves” emphasizing more to keep our soil healthy for long run. Recently, the
importance of soil has been aptly addressed in Nepal by UN by declaring International
Year of Soils and Mr. Narendra Modi, honorable Prime Minister of India by his
statement on soil health card, posing considerable challenges to the soil scientists of
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24-25 March 2015
Nepal. The ultimate user of all natural resources is the human being. Soil entities will
dictate what society can do from it. A soil scientist has to understand both human made
and natural soil process and develop strategies for appropriate remedial action to meet
the need of the society.
Soil and Society
Soil science provides ears and eyes to the society in translating dreams into reality of
what nature will allow. Soil Scientist must understand the potential and limitation
about carrying capacity of the soil, its productivity, potential of soil and its constraints.
We must also get answers to soil related issues including land degradation and restore
its productivity. The relationship of soil, environment and society is intimate and
depends on soil quality and its management. Those who develop or manage soil often
control the fate of societal visionaries.
Soil is a living factory where millions of life is ceaselessly working day and night. Soil
is made favourable by living organisms. That is why without life, there is no soil and
without soil, there is no life in this planet earth. We are quite aware about the
importance of soil and life. Astronauts landing on moon or any other planet first take
soil samples for test for evidence of life on it.
Nepal has various agro ecological zones and depending on it there are variations in soil
types and characteristics. If properly explored, Nepal can be a museum of world soils.
We are exploiting it to make our living luxurious. Soils of Nepal have the potential to
harvest diamond from it. We can explore soils having similar or better quality as that of
Multani mitti which is sold freely everywhere. It is in the hand of soil scientists to
explore and discover it.
Current threat to soil
Soil and society are inseparable entities but human greed has reached such an extreme
that agrochemicals are excessively used to meet the needs. In recent years, pesticide
havoc has occupied every corners of newspaper. Due to excessive use of
agrochemicals, the soil health is deteriorated. Soil is bound to be sick.
Another major problem in the country is the mining of soil fertility due to inadequate
replenishment of nutrients due to high uptake of nutrients by HYVs and increase in
cropping intensity. There is a big gap between removal of plant nutrients and
replenishments.
Soil degradation is a major threat to our food and environmental security. Many
thriving civilizations have vanished in the past because of inadequate attention to land
care. Government has been characterizing soil resources for drawing up land use and
land developmental plans. More focus should also be given to control soil degradation.
Soil erosion is another form of land degradation that has been substantially increasing
every year in Nepal. Devastating earthquake of this year followed by landslide in many
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24-25 March 2015
areas has affected human life in Nepal. Proper precautionary policies should be
formulated in time to save thousands of human and animal life.
Soil acidity has emerged as another problem to soil management. Due to increase in
acidity, micronutrients especially Mo and B are not available to crops. Microbial
diversity ad population can’t flourish for proper decomposition and nitrification. The
harmful effect of soil acidity on leguminous plants seems to be caused by Mo
deficiency rather than Al toxicity. Degree of tolerance of crop species to acidity varies.
We can explore industrial waste as amendments for acid soils.
Climate change has serious effect on soils of Nepal. There is decline of population and
diversity of soil microorganisms. There are several reports on the losses of
biodiversity, which affect the soil health. This may be due to the combined effect of
climate change as well as use of toxic agrochemicals.
Decline in organic matter is another threat today. Soil is a natural resource and it needs
proper policies to manage it. Organic matter (OM) is what makes the soil a living,
dynamic system that supports all forms of life in this planet. SOM is the key to N
economy and soil quality. Arresting the fall in OM is the most important weapon to
fight soil degradation and to ensure sustenance of soil quality and agricultural
productivity.
Soil Science Research and Research Scientists in NARC
In earlier days, Soil Science Division, NARC focused more in soil survey. Till date
soils of 56 districts of Nepal has been surveyed and it is hoped that within few years all
districts will be covered. In recent years, research projects are more focused on soil
fertility and nutrient management. Most of the generated technologies are soil fertility
oriented. Till date more than 200 soil science related technologies has been generated
and very few technologies has reached the farmers and it is expected for its rapid
dissemination in future through outreach or through DoA. Most of the research
technologies are of soil fertility and nutrient management and very limited works on
soil physics could be browsed. In recent years, researches on micronutrients have also
been a focus. Analyzing five years soil science research projects in NARC (Figure 1),
it is clear that research is inadequate and there is declining trend of research projects.
One of the reasons for decreasing research project is inadequate budget and manpower.
Only 1.26% of the total research budget of NARC is allocated for soil science research.
38
24-25 March 2015
35
31
30
30
25
28
23
19
20
15
Project no.
10
5
0
66/67
67/68
68/69
69/70
70/71
Figure 1: Trend of Soil Science Research Projects in NARC.
Human resource is one of the big assets of any organization. Everywhere in the world,
there is 40% lack of soil scientists and Nepal cannot be an exception. There are only 30
Soil scientists in NARC (Figure2). With this limited manpower, high level research
covering all across Nepal cannot be expected, yet we are doing the best to generate
technologies and innovations.
Existing Manpower
10
9
8
7
6
5
4
3
2
1
0
9
8
8
4
Existing Manpower
1
CSS
SSS
SSc
STO
TO
Figure 2: Current status of human resources in soil science research.
In order to carry out soil science research, there must be good laboratory facilities.
NARC has ten soil science laboratories throughout the country but only three are
functional at the moment. Rest seven laboratories are not functional because of old and
damaged laboratory equipments and also due to lack of skilled laboratory staffs in the
research station. It is envisaged that in near future, more scientists will be recruited for
effective and smooth running of the soil laboratories.
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24-25 March 2015
Future Strategies
Strengthening soil laboratories and manpower
Strengthening laboratory is mandatory for research. Laboratories should be established
or strengthened with high quality automated equipments. Strengthening and
functioning of laboratory must start right from educational institutions. Students should
have the capacity to handle and run laboratory independently in academic institutions.
All laboratories of Research as well as Developmental sectors should have the facilities
to analyse micronutrients, heavy metals and soil pollutants. Analysis methodologies
should be homogenous throughout all laboratories of Nepal. Human resources should
also be strengthened and updated. At present, there is scarcity of soil scientist and
NARC should recruit enough soil scientists to carry out adequate research. Existing
Scientist should be trained, given opportunity for exposure at international arena.
Those scientists working in the laboratory should get proper incentive to boost his
morale and competency.
Future research strategies
At the beginning, research should address the existing problems of soils in Nepal such
as soil acidity, nutrient mining or increasing efficiency of nutrients, micronutrients,
organic nutrient sources, enhancing efficacy of biofertilizers, land degradation/erosion,
climate change, etc. Works on bioremediation, soil genomics, soil hybridization, soil
resilience, nanotechnology, etc. should be initiated immediately. Biofertilizer research
should be enhanced and promoted. Research must not be limited to Azolla, Rhizobium
and Azotobacter but also must explore Azospirillum, VAM, BGA, OM decomposers,
Frankia, PGPR, etc. Bioremediation is another aspect which research should promote.
In agricultural practices of crop production, many harmful chemicals are used to
control insects, pest, diseases and weeds. These chemicals are applied to plants and
soils. The micro-organisms in the soil detoxify the chemicals at certain time period.
Applications of such pesticides depress the microbial activities and sometimes reduce
the microbial population. Studies on soil genomics is another frontier we have to look
into for the effective bioremediation.
Coordination and linkages
There must be strong coordination between scientist, academician and development
workers for effective dissemination of identified technologies. Though researchers
have developed more than 200 soil science technologies, only few technologies are
found at farmers’ field. Therefore, strong coordination between research, extension and
education is the need of the day.
Development of National Soil Museum
Though Nepal is virtually a museum of world soil, till date a national level soil
museum has not been established. The importance of soil at policy level has been felt
this time with the declaration of International Year of Soils, 2015 by United Nation and
40
24-25 March 2015
at this moment a national soil museum should be developed to know more about soils
of Nepal.
Summary
Soil is a limited and non renewable resource. It is critical for agriculture, food security,
nutritional security, environmental safety and quality of life. Soil is habitat for
numerous living things and without soil, life cannot be expected. Proper policies and
guidelines should be formulated to keep it living for long run and it is the duty of all
citizens to contribute in making soils healthy for our healthy and wealthy living.
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2.
SF-1
Soil Fertility Status of Nepal: Report from Laboratory Analysis of Soil
Samples of Five Developmental Regions
Durga P Dawadi and Manita Thapa
Soil Management Directorate, Department of Agriculture, Hariharbhawan, Lalitpur, Nepal
Abstract
Soil Management Directorate along with Regional Soil Testing Laboratories
Region under Government of Nepal
to test soil sample across the
country. A report on soil fertility status of Nepal was prepared based on the result
obtained from seven soil testing laboratories in the fiscal year 2070/71. In this FY, a total
of 1700 soil samples were analyzed to determine the status of soil nitrogen (N),
phosphorus (P2O5), potash (K2O), Organic Matter (OM) and pH. The results revealed
that majority of the soil samples were found to be acidic (53%). Similarly, OM range
from low to medium and majority of the samples have low content of soil nitrogen,
phosphorus and potash. While comparing the soil fertility status of five development
Regions of Nepal, soil pH was found to be dominated by acidic condition except for FarWestern Developmental Region. The organic matter content of the majority of the
low.
sample from Eastern Development and Far-Western DevelopmentRegion was
While the OM content of other Region range from low to medium. The nitrogen results
also range from low to medium across all the Regions. The status of phosphorus and
potash is low in Eastern Region whereas low to high in other Regions. The paper also
explored the average status of soil fertility of 38 districts which were mapped by Soil
Management Directorate in coordination with respective District Agriculture
Development Office. The status of soil nutrient content is declining throughout the nation
but the rate of declining is higher in eastern part of Nepal. In this context the
fertility statusshould be disseminated throughout the nation.
technologies to manage
The Government should facilitate to develop its manpower and appropriate technologies.
Keywords:Acidic condition, organic matter, phosphorus and potash, soil fertility.
Introduction
Nepal’s economy largely depends on its agriculture as it contributes one third of Gross
Domestic Production. Farming in Nepal is characterized by a close relationship
between crop production, livestock and forestry. Nowadays the linkage between
forests, livestock, and cropping systems is becoming weak. Soil fertility is largely
maintained by the application of compost and farm yard manure, but in recent years a
decline in soil fertility has been reported. Historical trends of increasing crop
intensification, decreasing livestock numbers, increasing use of chemical fertilizers,
reduced labour availability, and change in the climate over the last few decades showed
decline in soil productivity as well.
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24-25 March 2015
There is a school of thought that food production can be increased by
expandingcultivable area. Out of the total land in Nepal, 21% is cultivated and there is
very little chance of expansion. So the food crisis in Nepal must be solved by raising
the productivity of existing arable land. Among the different means of increasing
productivity of crop, ‘soil fertility improvement' is one of the key factors.
In Nepal Soil Management Directorate under Ministry of Agriculture Development is
an authorized organization to implement overall soil management programs. Besides
five Regional Soil Testing Laboratories at five different development regions there is
one more Soil Testing Laboratory at the Surunga of Jhapa district mandated for the soil
sample analysis of industrial crops, especially for tea and cardamom. Staffs working
in this directorate or in different laboratories under this directorate assess problems
with the farmers regarding soil and then develop and carry out programs to solve them.
The major programs conducted through Soil Management Directorate include soil,
fertilizer and micronutrient analysis along with Integrated Plant Nutrient Management
System (IPNS), Nutrient Deficiencies Study, Soil Fertility Maps of Different Districts,
training related to soil management and laboratory procedures, FYM and Compost
Management Programs etc.
Nepal is facing a serious problem of soil quality decline.As a result of there have been
recent changes in agricultural practices and thereby increasing resource constraints.
Many researcher documented several constrains in soil fertility management in Nepal
because of deforestation and other land use changes. These changes include nonagricultural uses of fertile land, land fragmentation and cultivating marginalized areas,
cultivation on the steep slopes, overgrazing, burning of crop residues, imbalanced use
of agrochemicals, and decline in use of organic manure. In South and South-East Asia,
the principal soil degradation processes associated with land use changes include
accelerated erosion by water and wind, salinization, flooding, water logging, and soil
fertility. The pace of soil degradation issue is the highest in mountains because of the
fragile environment and the steep slopes cultivation. Moreover, due to rugged
mountainous topography, active tectonics and concentrated monsoon precipitation,
Nepal is naturally highly vulnerable to soil erosion in hill slopes and flooding in the
low-lands.
Increasing gap between soil management and soil fertility decline became a big
challenge for sustainable soil management program and great concern for agricultural
production. Due to lack of soil fertility information of the district or of a particular
area, fertilizer application is unscientific and overall soil fertility improvement attempts
have been unsuccessful. Therefore, to recover the deteriorated fertility status of the soil
and harness the maximum productivity, it is essential to know the existing soil fertility
status and manage them on the basis of soil test results. The practical way to know the
existing soil fertility status is the collection and analysis of soil samples in the
laboratories. However, farmers have been applying fertilizers randomly without their
soil test result because of limited soil testing facilities.
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Agriculture Perspective Plan (APP, 1995) and different periodic plan has put emphasis
on boosting up agriculture production through the use of chemical fertilizers and
irrigation in high production potential areas. Soil fertility management is an important
requirement for sustainable farming. Traditional agriculture is based on organic source
of input and largely depends upon the forest resources and livestock raising practices
for soil fertility management. Sustaining soil fertility is essential for agricultural
growth in Nepal. Fertility status of soil can be increased by judicious application of
both organic and inorganic fertilizers with other good soil management practices.
Nowadays, organic inputs are gradually being supplemented by inorganic sources.
Efforts have been made to develop research and development programs both by
government and non government institutions to address the problems related to soil
fertility, however, achievement is not up to the expected level.
In context of growing number of commercial farmers in Nepal, the demand for soil
testing and maintaining soil health is also increasing. To meet this demand there is
limited number of soil testing laboratories and technical manpower in the country.
Those technicians who are involved in laboratory analysis are not well trained and
equipped with the lab equipments. Besides these there is lack of sufficient laboratory
equipments to provide services.
Status of Soil Fertility in Nepal
The following data figure out the status of soil in Nepal based on the soil sample
analysis from the Soil Management Directorate and its laboratories. In the fiscal year
2070/71, 17000 samples (on an average) were tested.Result consist of analysis from
laboratories, soil campaign and the samples tested for mapping 5 districts namely
Lamjung, Kalikot, Jajarkot, Mustang and Myagdi.
Table 1: Result obtained from the tested samples in the FY 2013/14
Soil Condition
pH
Nitrogen
Phosphorus
Potash
OM
SMD
RSTL,
Hetauda
RSTL,
Jhumka
RSTL,
Pokhara
RSTL
,Khajura
RSTL,
Sundarpur
STL,
Surunga
Total
Acidic
541
2593
1308
2393
1516
439
242
8790
Neutral
513
586
846
1713
1218
681
124
5557
Alkaline
257
188
203
867
141
582
44
2238
Low
831
2323
1783
1766
1182
1309
280
9194
Medium
326
894
468
1568
1174
391
122
4821
High
207
206
109
1323
365
120
5
2330
Low
661
1782
1849
855
1088
695
205
6930
Medium
325
940
465
1320
988
532
156
4570
High
333
662
46
2738
793
523
36
5095
Low
681
1949
1747
1870
965
988
253
8200
Medium
420
965
427
1332
623
512
100
4279
High
221
470
186
1536
1211
299
47
3923
Low
162
581
453
634
374
339
153
2543
Medium
140
353
130
872
782
61
44
2338
High
22
64
17
584
139
11
0
837
Source: Annual report 2070/71, SMD
Laboratory and Soil Campaign Samples and Soil fertility Map Samples (Lab=3890, Campaign samples=
12000, Mapped Samples=1684)
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24-25 March 2015
Note:
Nitrogen: Low :< 0.1%; Medium: 0.1-0.2%; High: >0.2%; Phosphorus: Low:
<26kg/ha; Medium: 26-55kg/ha; High: >55kg/ha; Potash: Low: <110kg/ha; Medium:
110-180kg/ha; High: >280kg/ha (STL: Soil testing Laboratory, RSTL: Regional Soil
Testing Laboratories)
Status of soil pH
In fiscal year 2070/71 16585 soil sampleswere tested by SMD and its related
laboratories to determine pH level. About 53% of the samples were found to be acidic
followed by Neutral (33.51%) and alkaline (13.49%).
Status of Soil pH FY 2070/71
Sample Size: 16585
13.49%
Acidic
Neutral
Alkaline
33.51%
53.00%
Figure 1: status of soil pH in FY 2070/71 (2013/14).
Source: Annual report 2070/71, SMD, DoA.
On acid soils, the pH can be raised by adding lime (calcium carbonate). The amount to
add depends on the cation exchange capacity (nutrient-holding capacity) of the soil,
which is based on the soil’s clay content and its buffering capacity. Soil higher in clay
will have a higher cation exchange capacity and will require more materials to raise the
soil pH.
Status of Soil Organic Matter
Out of 5718 tested soil samples 44.47% of the soil sample contains low organic matter
followed by medium (40.89%) and high (14.64%). Soil organic matter includes all
living soil organisms together with the remains of dead organisms in their various
degrees of decomposition.Organic carbon content of a soil is made up of
heterogeneous mixtures of both simple and complex substances containing carbon. The
sources for organic matter are crop residues, animal and green manures, compost and
other organic materials. A decline in organic matter is caused by the reduced presence
45
24-25 March 2015
of decaying organisms, or an increased rate of decay as a result of changes in natural or
anthropogenic factivities. Organic matter is regarded as a vital component of a healthy
soil; its decline results in a soil that is degraded.
Status of Soil Organic Matter FY 2070/71
Sample Size: 5718
Percentage
50.00
40.00
30.00
44.47%
40.89%
20.00
14.64%
10.00
0.00
Low
Medium
High
Source: Annual report 2070/71, SMD
Note:Low :< 2.5%; Medium: 2.5-5%; High :> 5%
Figure 2: Status of Soil Organic Matter.
A good supply of soil organic matter is beneficial in crop production. Consider the
benefits of this valuable resource and how we can manage our operation to build, or at
least maintain, organic matter in our soil. Proper fertilization encourages growth of
plants, which increases root growth. Increased root growth can help build up or
maintain soil organic matter, even if we are removing above ground part of crops.
Status of Nitrogen, Phosphorus and Potash in Soil
Nitrogen, phosphorus and Potassium are the essential elements for growth and
development of plant. Nitrogen is an integral part of all proteins, and is one of the main
chemical elements required for plant growth and photosynthesis. Phosphorus is vital
for strong growth. Insufficient phosphorus in the soil will cause stunted, spindly crops.
Phosphorus, when combined with water, breaks in to separate ions that can be
absorbed by the plant’s root system. Potassium aids in water absorption and retention,
also encourages strong roots, sturdy stems, and healthy, full grown crops that have
longer shelf life.
While considering the result of 17000 sample analysis in the FY 2070/71 (2013/14),
nitrogen content in the soil ranges from low to medium. Similarly phosphorus and
potash content also ranges from low to medium. However, the percentage of sample
falling on higher range is declining year by year (source: Various report of SMD).
46
24-25 March 2015
60.00
Percentage
50.00
56.25%
Nitrogen
Status of Soil N,P,K FY 2070/71
Sample Size :17000
Phosphorus
49.99%
Potash
41.76%
40.00
29.50%
30.00
30.7%
27.54%
26.09%
20.00
23.92%
14.25%
10.00
0.00
Low
Note:
Medium
High
Nitrogen: Low :< 0.1%; Medium: 0.1-0.2%; High: >0.2%;
Phosphorus: Low: <26kg/ha; Medium: 26-55kg/ha; High: >55kg/ha;
Potash: Low: <110kg/ha; Medium: 110-180kg/ha; High: >280kg/ha
Figure 3: Status of soil NPK (Source: Annual report 2070/71, SMD).
Balanced fertilization with phosphorus and potassium, to replenish harvested nutrients and to
build up and sustain soil tests at optimum levels, it is a proven best management practice to
improve phosphorus and potassium status in soil thereby increasing nitrogen used efficiency.
Regional Distribution of Soil Analysis result (FY 2013/14)
Soil Management Directorate along with its five regional soil testing laboratories and a soil
testing laboratory has analyzed 17000 soil samples in the FY 2013/14. The test result is
tabulated according to five development regions.
Table 2: Soil test result of five developmental regions.
Soil Condition
pH
Nitrogen
Phosphorus
Potash
OM
Acidic
Neutral
Alkaline
Low
Medium
High
Low
Medium
High
Low
Medium
High
Low
Medium
High
Regional Distribution of Soil test Results of FY 2070/71
EDR
CDR
WDR
MWDR
Sample
Sample no:
Sample no:
Sample no:
no:2767
4787
4973
2875
No.
%
No.
%
No.
%
No.
%
1550
56.02 3134 66.99 2393 48.12 1516 52.73
970
35.06 1099 23.49 1713 34.45 1218 42.37
247
8.93
445
9.51
867
17.43
141
4.90
2063
74.56 3154 65.89 1766 37.92 1182 43.44
590
21.32 1220 25.49 1568 33.67 1174 43.15
114
4.12
413
8.63
1323 28.41
365
13.41
2054
74.50 2443 51.95
855
17.40 1088 37.92
621
22.52 1265 26.90 1320 26.87
988
34.44
82
2.97
995
21.16 2738 55.73
793
27.64
2000
72.46 2630 55.89 1870 39.47
965
34.48
527
19.09 1385 29.43 1332 28.11
623
22.26
233
8.44
691
14.68 1536 32.42 1211 43.27
606
76.04
743
56.20
634
30.33
374
28.88
174
21.83
493
37.29
872
41.72
782
60.39
17
2.13
86
6.51
584
27.94
139
10.73
47
FWDR
Sample no: 1800
No.
%
439
25.79
681
40.01
582
34.20
1309
71.92
391
21.48
120
6.59
695
39.71
532
30.40
523
29.89
988
54.92
512
28.46
299
16.62
339
82.48
61
14.84
11
2.68
24-25 March 2015
Note: EDR: Eastern Development Region; CDR: Central Development Region; WDR: Western
Development Region; MWDR: Mid Western Development Region; FWDR: Far
Western Development Region
Graphical Representation of Soil pH of different region
The following graph represents the pH condition of the soil at different region. The
graph clearly represent that the pH in majority of the sample from all the regions
except far western development region is found to be acidic followed by neutral.
Percentage
Regional Distribution of Soil pH (2070/71)
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
Acidic
Neutral
66.99
Alkaline
56.02
48.12
35.06
34.45
23.49
8.93
EDR
40.01
34.20
25.79
42.37
17.43
9.51
CDR
52.73
4.90
WDR
MWDR
FWDR
Note: EDR: Eastern Development Region; CDR: Central Development Region; WDR: Western
Development Region; MWDR: Mid Western Development Region; FWDR: Far
Western Development Region
Figure 4: Soil pH status at different Region.
Graphical Representation of Soil Organic Matter of different region
The organic matter content of the majority of samples from Eastern developmental
and far western development region was found to be criticallylow. While the OM
content of other region ranges from low to medium (Figure 5).
48
24-25 March 2015
Regional Distribution of Soil OM (FY 2070/71)
90.00
80.00
70.00
Percentage
82.48
76.04
Low
60.00
56.20
50.00
40.00
41.72
37.29
30.00
21.83
20.00
CDR
WDR
Medium
High
28.88
14.84
10.73
6.51
2.13
EDR
30.33
27.94
10.00
0.00
60.39
MWDR
2.68
FWDR
Note: EDR: Eastern Development Region; CDR: Central Development Region; WDR:
Western Development Region; MWDR: Mid Western Development Region; FWDR:
Far Western Development Region (OM: :< 2.5%; Medium: 2.5-5%; High :> 5% )
Figure 5: Soil OM status of different Region.
Graphical Representation of Soil Nitrogen of different region
Percetage
Regional Distribution of Soil Nitrogen (2070/71)
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
74.56
71.92
65.89
37.92
21.32
25.49 33.67
CDR
43.15
13.41
8.63
4.12
EDR
28.41
WDR
Low
Medium
High
43.44
MWDR
21.48
6.59
FWDR
Far Western Development Region (Nitrogen: Low :< 0.1%; Medium: 0.1-0.2%; High:
>0.2%;)
Figure 6: Soil nitrogen status of different Region.
Graphical Representation of Soil Phosphorus of Different Region
In majority of the sample from eastern part of Nepal the condition of phosphorus was
found to be very low.
49
24-25 March 2015
Regional Distribution of Soil Phosphorus
(2070/71)
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
Percent
agee
74.50
55.73
51.95
26.90
22.52
26.87
21.16
17.40
37.92 39.71
34.44
30.40
29.89
27.64
Low
Medium
High
2.97
EDR
CDR
WDR
MWDR
FWDR
Far Western Development Region (Phosphorus: Low: <26kg ha-1; Medium: 26-55 kg
ha-1; High: >55 kg ha-1)
Figure 7: Soil phosphorus status of different Region.
Graphical Representation of Soil Potash of different region
The following graph (Figure 8) shows that the potash condition is also low in eastern
Central and far western part of Nepal and the rest of the regions show mediumlevel.
Percentage
Regional Distribution of Soil Potash (2070/71)
80.00
70.00
60.00
50.00
40.00
30.00
20.00
10.00
0.00
Low
72.46
55.89
29.43
19.09
8.44
EDR
14.68
CDR
39.47
32.42
28.11
WDR
54.92
43.27
34.48
22.26
MWDR
Medium
High
28.46
16.62
FWDR
Far Western Development Region (Potash: Low: <11o kg ha-1; Medium: 110-180 kg ha1
; High: >280 kg ha-1)
Figure 8: Soil potash status of different Region.
50
24-25 March 2015
Soil fertility status of different district
Soil Management Directorate have prepared soil fertility map of the following listed 38
districts in coordination with its regional laboratories and respective District
Agriculture Development Office. The average soil fertility status is shown in the
following table.
Figure 9: Soil fertility mapped districts by SMD.
Conclusion
The status of soil nutrient content is declining throughout the nation but the rate of
declining is higher in eastern part of Nepal. Assessing soil fertility decline is difficult
because most soil chemical properties either change very slowly or have large seasonal
fluctuations; in both cases, it requires long-term research commitment. Soil fertility is
of fundamental importance for the development of agricultural production.
Deficiencies of plant nutrients are often limiting yields, and improved management of
plant nutrients is crucial for enhancing productivity.
In this context technologies to manage the fertility status of the soil should be
disseminated throughout the nation. The government should facilitate to develop its
manpower and appropriate technologies.
51
24-25 March 2015
Table 3 : Average fertility status of mapped districts of Nepal.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Jhapa
Sunsari
Nuwakot
Kanchanpur
Bardiya
Kailali
Parbat
Banke
Parsa
Syangja
Mahottari
Nawalparasi
Kavre
Chitwan
Okhaldhunga
Surkhet
Bhaktapur
Dhading
Gulmi
Rupandehi
Dolakha
Dang
Sindhuli
Baglung
Jumla
Arghakhanchi
Dadeldhura
Palpa
Panchthar
Soil test result
Nitrogen
–
Low-Medium
Medium
Low
Low
Low
Medium
Low
Low
Medium
Low
Low
Low – Medium
Low
Medium – High
Medium – High
–
Medium
Medium – High
Low
Very High
Very Low
Low
Medium
High
Medium
Medium
High
Medium
30
Ramechhap
Medium
31
32
33
Khotang
Dailekh
Jajarkot
Medium
Medium
Medium
34
Kalikot
Medium
35
36
37
38
Lamjung
Myagdi
Makwanpur
Mustang
Medium
High
Low – Medium
High
S.N.
District
Phosphorus
–
Low-High
Medium
Medium-High
Low
Medium
Medium
Low – Medium
Medium
Low – Medium
Low
Low
Low
Low
High
High
–
Medium
Medium
Low
Very High
Medium – High
Medium – High
Very High
Medium
Medium
Medium – High
Low
High
High – Very
High
High
High
Low
High – Very
High
Medium – High
Very High
Very High
High
Potash
–
Medium
Medium-High
Low
Medium
Medium
Medium – High
Medium
Low
Medium
Low
Low – Medium
Medium
Low
Medium
High
–
Medium
Medium
Medium – Low
Medium
Medium
Low – Medium
High – Medium
High
Medium
High
Medium
Very High
Organic Matter
–
Very Low-Low
Medium
Low
Low
Low
Medium
Low
Low
Medium
Low
Low
Low – Medium
Low
Medium
Medium
–
Medium
Medium
Low
Medium
Medium
Low
Medium
Medium
Medium
Low – Medium
Medium
Medium
pH
Acidic
Acidic
Acidic
Slightly Acidic
Neutral-Alkaline
Neutral-Alkaline
Acidic
Neutral
Slightly Acidic – Neutral
Acidic
Slightly Acidic
Acidic
Acidic
Neutral – Acidic
Neutral – Slightly Acidic
Slightly Acidic
Acidic
Neutral
Acidic
Slightly Acidic
Acidic
Slightly Acidic
Acidic
Neutral
Slightly Acidic
Acidic
Very High
Medium
Slightly Acidic
High
High
High
Medium
Medium
Medium
Slightly Acidic
Acidic
Acidic
High – Very High
Medium
Slightly Acidic
Medium
Medium
Medium
Very High
Medium
High
Low – Medium
High
Acidic
Slightly Acidic
Acidic – Slightly Acidic
Alkaline
References: (Not cited in the text).
52
24-25 March 2015
SF-2
Evaluation of Soil Properties and Wheat (Triticumaestivum L.)
Productivity Influenced y Nitrogen Levels and Sowing Dates under Zero
Tillage condition in Chitwan, Nepal
Ran B Mahato1, Keshab R Pande2and Anant P Regmi3
1
2
District Agriculture Development Office, Gulmi, Nepal
Department of Soil Science, Institue of Agriculture and Animal Sciences,(TU), Chitwan,
Nepal
3
Nepal Agriculture Research Council, Khumaltar, Lalitpur
Abstract
experiment was conducted on a farmer field at Torikhet Chitwan, Nepal, during
the soil properties and wheat productivity influenced by
2011/2012 in order to
nitrogen levels and sowing dates under zero tillage. The experiment consisted four
nitrogen levels (60, 100, 140 and 180 N kg ha-1) and three sowing dates (Nov. 25, Dec.
10 and Dec. 25) and laid out in split plot design. The plant characters, soil physical and
chemical properties, yield attributes and yields were significantly influenced by different
treatments. The result showed that the highest grain yields (4.84 t ha-1 and 4.97 t ha-1,
respectively) were obtained from the crop sown on Nov. 25 and from the application of
value was recorded on the crop sown on
140 N kg ha-1. The highest
and from the application of 140 N kg ha-1. Nitrogen dynamics including total
nitrogen uptake, total soil N, residual N and unaccountable N were found highest on the
crop sown on Nov. 25 and from the application of 180 N kg ha-1 but was the lowest
(30.59 N kg ha-1). The highest total phosphorus uptake, total soil phosphorus, residual
phosphorus and unaccountable phosphorus were observed on the crop sown on Nov. 25.
The net income were highest (NRs. 49,640 ha-1 and NRs. 52,510 ha-1, respectively) on
the crop sown on Nov. 25 and from 140 N kg ha-1.
Keywords: Chlorophyll value, grain yield nitrogen levels phosphorus uptake sowing
dates zero tillage.
Introduction
After rice and maize, wheat is the third important cereal crop of Nepal in terms of
cultivated area, production and productivity (MoAD 2012). It is grown in winter
season in Nepal and is cultivated from the Terai (66 masl) to high mountain (2300
masl). At present, wheat sown area in Nepal is 765,317 ha with a total production of
1,846,142 mt and productivity of 2.412 t ha-1. In Chitwan, wheat is cultivated on total
area of 8750 ha with the total production of 27,125 t ha-1 and productivity of 3.1 t ha-1
(MoAD 2012).
The concept of zero or reduced tillage isbecoming important as a part of tillage
management, which causes zero or minimal disturbance of soil. Zero tillage is one of
the alternatives for timely planting of wheat in traditional wheat areas (rice-fallow)
under the rice-wheat cropping system to increase wheat production. This method can
53
24-25 March 2015
eliminate yield reduction due to delay planting caused by depletion of moisture, poor
draft power, lack of mechanization, delay transplantation of rice and unavailability of
labor etc (Giri 1995).
Nitrogen (N) is the most yield-limiting nutrient for no-till wheat. Application of proper
amount of nitrogen is considered key to obtain bumper production of wheat. Nitrogen
supply favors the conversion of carbohydrates into proteins, which in turn promotes the
formation of protoplasm (Arnon 1972). Besidesits role in formation of proteins, it is an
integral part of chlorophyll, which is the primary absorber of light energy needed for
photosynthesis. An adequate supply of nitrogen is associated with high photosynthetic
activity, vigorous vegetative growth and a dark green color.
Sowing date of wheat is one of the limiting factors for the sustainable production of
wheat. Data from many experiments have shown that wheat yields decline by 0.7–
1.5% per day of delay from optimum planting time ( Randhawaet al. 1981 and OrtizMonasterioet al. 1994). Late sown wheat is exposed to low temperature during early
vegetative phases (Singh et al. 1999) and high temperature during the reproductive
phases (Nainwal and Singh 2000). Timely sowing also saves crop from high
temperature, high wind velocity and low humidity at grain filling stage and untimely
rains do not interfere with harvesting-threshing operations (Chaudhary et al. 1993).
Therefore, this study was conducted to evaluate the residual soil properties and wheat
productivity and also to address the optimum dose of nitrogen and sowing time of
wheat under resource conservation technology i.e. zero tillage.
Materials and methods
The experiment was carried out at Torikhet, Chitwan, Nepal, during 2011/2012. The
experiment consisted four nitrogen levels (60, 100, 140 and 180 kg N ha-1) and three
sowing dates (Nov. 25, Dec. 10 and Dec. 25) and was laid out in split plot design and
had twelve treatments. The combinations of sowing dates were put in mainplots and
nitrogen levels in subplots. Shallow furrows were made by using a pointed hoe where
seeds and fertilizers were placed continuously side by side. ‘Vijay’ variety of wheat
was used at the rate of 120 kg ha-1. Half dose of nitrogen and full dose of Phosphorus
@ 50 kg ha-1 and Potassium @ 50 kg ha-1 were applied as basal doses and remaining
half dose of nitrogen was applied at CRI stage before first irrigation (25 DAS). Soil
and plant samples were analyzed in the laboratory by required analyzing methods.
Biometrical observations yield and yield attributing observations and soil related data
were recorded. The collected data were compiled and analysis of the variance for all
the parameters was done by using the M-STAT computer software program. Ducan’s
Multiple Range Test (DMRT) was used to compare the means within the different
parameters at 5% level of significance.
54
24-25 March 2015
Results and discussions
Effect of sowing dates and nitrogen levels on yields of wheat
Grain yield
Grain yield was significantly influenced by the different sowing dates. Wheat crop
sown on Nov. 25 gave the highest (4.835 t ha-1) grain yield and it was consistent with
the crop sown on Dec. 10. The lowest grain yield (3.897 t ha-1) was obtained from the
crop sown on Dec. 25 (Table 1). The higher grain yield from early sown crop may be
attributed to better plant growth leading to significantly more plant height, tillers m-2,
grains spike-1, bold grains, higher test weight and better partitioning of photosynthates
compared to delayed sown crop (Sardana et al. 2002).
Effect of nitrogen on grain yield of wheat was highly significant. There was an
increasing trend of grain yield with the increasing levels of nitrogen to 140 kg ha-1 but
decreased after increased applications of nitrogen. The highest grain yield (4.973 t ha-1)
was obtained from the application of 140 kg N ha-1 followed by 180 kg N ha-1 (4.709
t ha-1) and 100kg N ha-1 (4.316 t ha-1). The lowest grain yield (3.753 t ha-1) was
obtained from the application of 60 kg N ha-1 (Table 1). Higher grain yield with
increasing nitrogen levels might be due to stimulation of growth and development of
root, carbohydrate utilization within plant and stimulation of utilization of other
nutrients (Brady and Weil 2005). Bhattarai (2012) also reported the similar results that
highest grain yield (3.103 t ha-1) was obtained from the application of 150 kg N ha-1.
Straw yield
As similar to grain yield, the straw yield was significantly influenced by the sowing
dates of wheat. Crop sown on Nov. 25 produced the highest straw yield (5.998 t ha-1)
and was similar with the crop sown on Dec. 10 whereas the lowest (5.114 t ha-1) was
on Dec. 25 sown crop (Table 1). Higher straw yield of the early sown crop might be
due to the effective and efficient utilization of soil moisture and nutrients. Wajid et al.
(2004) also reported similar results that early (Nov. 10 or Nov. 25) sowings
significantly increased straw yield than the late (Dec. 10) sowing. The highest straw
yield (6.076 t ha-1) was observed from the application of 180 kg N ha-1 and it was at par
with 140 kg N ha-1. The lowest straw yield (5.193 t ha-1) straw yield was obtained from
the application of 60 kg N ha-1 (Table 1). Increased straw yield with increasing levels
of nitrogen might be due to better vegetative growth and development of plant by
better utilization of nutrients and production of more tillers m-2, higher plant height and
increased biomass production.
Harvest index
There wasnon-significant effect on harvest index due to sowing dates but nitrogen
levels significantly influenced the harvest index (Table 1). There was an increasing
trend of harvest index with increasing levels of nitrogen up to 140 kg N ha-1 and it was
decreased at 180 kg N ha-1. The decrease in HI might be due to decrease in grain yield
at higher level of nitrogen application.
55
24-25 March 2015
Table 1: Effects of sowing dates and nitrogen levels on grain yield, straw yield and HI
of wheat under zero tillage at Torikhet, Chitwan, Nepal, 2011/2012.
Treatments
Yields
Grain yield, t ha-1 Straw yield, t ha-1
HI,%
Date of Sowing
Nov. 25
4.835a
5.998a
44.71
Dec. 10
4.581a
5.913a
43.66
Dec. 25
3.897b
5.114b
43.14
LSD (P=0.05)
0.3226
0.1802
0.03584
SEm ±
0.08216
0.04589
0.009129
N levels (kg ha-1)
N60
3.753d
5.139b
41.94c
4.316c
5.531ab
43.85b
N100
4.973a
5.90a
45.81a
N140
4.709b
6.076a
43.76b
N180
LSD (P=0.05)
0.1172
0.5287
0.0099
SEm ±
0.03994
0.1780
0.0033
Values given in a row followed by same letter(s) do not differ at 0.05 level of significance
according to DMRT.
Effect on nitrogen dynamics
Nitrogen uptake
Effect of sowing dates on N uptake by wheat grain and straw as well as total N uptake
was significant. The highest N uptake by grain (98.85 kg ha-1) and straw (13.55kg ha-1)
as well as total N uptake (112.4 kg ha-1) was observed from the crop sown on Nov. 25
and N uptake by grain and total N uptake were at par with the crop sown on Dec. 10
(Table 2). Effect of nitrogen on N uptake by wheat grain, straw and total N uptake was
highly significant. The highest N uptake by grain (106.0 kg ha-1), straw (16.08 kg ha-1)
and total N uptake (122.1 kg ha-1) was observed from the application of 180 kg N ha-1
(Table 2). The lowest N uptake by grain (81.97 kg ha-1), straw (6.642 kg ha-1) and total
(88.62 kg ha-1) was observed from 60 kg N ha-1. Mishra et al. (2011) also reported
similar results.
Residual nitrogen
Residual soil nitrogen after the harvest of the wheat was significantly different due to
different dates of sowing. The highest residual soil nitrogen (153.3 kg ha-1) was
observed from the wheat sown on Nov. 25 followed by Dec. 10 (146.8 kg ha-1) and the
lowest (139.3 kg ha-1) on Dec. 25 (Table 2). Higher residual soil N on early dates of
sowing might be due to sufficient nitrification and adequate soil moisture. Significantly
highest residual soil N (164.6 kg ha-1) was observed from the application of 180 kgN
ha-1) followed by 140 kg N ha-1 (153.6 kg ha-1). The lowest residual soil N (127.8 kg
ha-1) was observed from 60 kg N ha-1(Table 2). The highest residual soil N with the
application of 180 kg N ha-1 might be due to higher dose of nitrogen application.
56
24-25 March 2015
Unaccountable N
Unaccountable N with regard to sowing dates was significant. The highest
unaccountable N (89.30 kg ha-1) was observed from the crop sown on Dec. 25 followed
by Dec. 10 (75.15 kg ha-1) and the lowest (64.88 kg ha-1) was observed from the plot
sown on Nov. 25 (Table 2). The highest unaccountable N observed from the plot in
which wheat was sown on Dec. 25, might be due losses by de-nitrification and/or
volatilization. Effect of nitrogen on unaccountable Nwas highly significant. The
highest unaccountable N (103.0 kg ha-1) was observed from the application of 180 kg
Nha-1 followed by 140 kg N ha-1 (79.3 kg ha-1) and that of the lowest (53.39 kg ha-1)
was observed from 60 kg N ha-1 (Table 2). Higher unaccountable N with higher dose of
N application might be due inefficient utilization of applied nitrogen, reduced C:N
ratio and increased mineralization.
Nitrogen use efficiency (NUE)
There was a significant difference on nitrogen use efficiency due to sowing dates. The
highest NUE (34.79%) was recorded from the crop sown on Nov. 25 followed by Dec.
10 (33.48%). The lowest NUE (32.44%) was observed on the crop sown on Dec. 25
(Table 2). The highest NUE on Nov. 25 might be due to adequate soil moisture and
temperature which are the key factor for efficient utilization of applied nitrogen. Effect
of nitrogen on nitrogen use efficiency was highly significant. Nitrogen use efficiency
decreased with the increasing levels of nitrogen (Table 2). Significantly the highest
NUE (37.02%) was observed from the application of 60 kg Nha-1 followed by 100 kg
N ha-1 (34.69%). The lowest NUE (30.59)% was observed from the application of 180
kg Nha-1. The lowest NUE from the application of 180 kg Nha-1 might be due to high
loss via de-nitrification or volatilization as compared to low nitrogen application.
Rahman et al. (2011) also reported that with increasing rate of N application from 80 to
120 kg ha-1 there was decrease in NUE.
Table 2:Effects of different sowing dates and nitrogen levels on Nitrogen dynamics of
wheat under zero tillage at Torikhet, Chitwan , Nepal, 2011/2012.
Treatments
Grain
Straw
Nitrogen dynamics
N uptake (kgha-1)
Total soil N N residual,
Total
kgha-1kgha-1kgha-1
Unaccountable N NUE(%)
Dates of sowing
Nov. 25
98.85a 13.55a 112.4a 329.9a
153.3a
64.88c
34.79a
Dec. 10
96.50a 11.30b 107.8a 326.3b
146.8ab
75.15b
33.48b
Dec. 25
91.31b 9.85b 101.2b 324.1c
139.3b
89.30a
32.44b
LSD (P=0.05)
3.509 1.748
4.604
0.599
7.938
7.255
1.312
SEm ±
0.8937 0.4453 1.172
0.1525
2.022
1.848
0.3342
N levels (kg ha-1)
N60
81.97d 6.64d 88.62d 266.9d
127.8d
53.39d
37.02a
N100
90.84c 8.93c 99.77c 306.7c
139.9c
70.08c 34.69b
N140
103.4b 14.62b 118.0b 346.6b
153.6b
79.30b
31.98c
N180
106.0a 16.08a 122.1a 386.7a
164.6a
103.0a
30.59d
LSD (P=0.05)
1.090 1.297
1.873
0.7285
3.730
3.009
0.6193
SEm ±
0.367 0.4364 0.6303 0.2452
1.225
1.013
0.2084
Values given in a row followed by same letter(s) do not differ at 0.05 level of significance according to DMRT.
NUE= Nitrogen use efficiency
57
24-25 March 2015
Effect on phosphorus dynamics
Phosphorus uptake
Effects of sowing dates on phosphorus uptake by grain, straw and total uptake by
wheat crop was not significant. However, the highest phosphorus uptake by grain,
straw and total uptake (21.8, 4.76 and 26.56 kg ha-1, respectively) was observed from
the crop sown on Nov. 25 and the lowest (20.26, 3.76 and 24.01 kg ha-1, respectively)
from the crop sown on Dec. 25 (Table 3). Phosphorus uptake was significantly affected
by nitrogen levels. There was an increasing trend of phosphorus uptake with the
increasing level of nitrogen (Table 3). The total amount of phosphorus uptake by wheat
crop was 35.15, 31.34, 19.04 and 15.6 kg ha-1withthe application of 180, 140, 100 and
60 kgN ha-1, respectively. The highest phosphorus uptake by grain and straw (28.88
and 6.27 kg ha-1) was observed from the application of 180 kgN ha-1. The increasing
trend of P2O5 uptake with the increasing level of N might be the synergistic effect of
nitrogen. Khan et al. (2008) also reported that phosphorus uptake by wheat was eN
hanced with the increased dose of nitrogen from 90 to 180 kg ha-1.
Residual phosphorus
Residual soil phosphorus was not affected by sowing dates. Effect of nitrogen on
residual soil phosphorus was significant. The highest residual soil phosphorus (60.43
kg ha-1) was observed from 60 kg N ha-1 followed by 100 kgN ha-1 (57.78 kg ha-1). The
lowest residual soil phosphorus (44.10 kg ha-1) was observed from the application of
180 kg N ha-1 (Table 3). This might be due to synergistic effect of phosphorus with
nitrogen in which increasing levels of nitrogen influenced the better growth of crop and
removal of higher amount of phosphorus from the soil. Similar results were concluded
by Selles et al. (2011) that the residual phosphorus treatments fertilized with N and P
was smaller than for the only P fertilized treatments where yields were limited by lack
of nitrogen.
Table 3: Effects of different sowing dates and nitrogen levels on Phosphorus
dynamics of wheat under zero tillage at Torikhet, Chitwan , Nepal,
2011/2012.
Treatments
Phosphorus dynamics,kg ha-1
Phosphorus uptake
Total soil P2O5 Residua P2O5Unaccountable P2O5
Grain
Straw
Total
Dates of sowing
Nov. 25
21.80
4.76
26.56
93.53
52.66
10.32b
Dec. 10
21.19
4.09
25.28
93.42
52.29
10.58ab
Dec. 25
20.26
3.76
24.01
93.62
51.87
11.21a
LSD (P=0.05)
NS
NSNSNSNS
0.671
SEm ±
1.223
0.366
1.363
0.242
1.411
0.171
N levels (kg ha-1)
N60
13.37d
2.23d
15.60d
93.44
60.43a
11.91a
N100
15.91c
3.13c
19.04c
93.53
57.78b
11.34b
N140
26.16b
5.18b
31.34b
93.74
46.79c
9.97c
N180
28.88a
6.27a
35.15a
93.40
44.10d
9.60c
LSD (P=0.05)
1.878
0.491
1.771
NS
1.359
0.460
SEm ±
0.632
0.165
0.596
0.419
0.457
0.155
Values given in a row followed by same letter(s) do not differ at 0.05 level of significance according to DMRT.
58
24-25 March 2015
Unaccountable P2O5
There was a significant effect on unaccountable P2O5with regard to sowing dates. The
highest unaccountable P2O5 (11.21 kg ha-1) was from the crop sown on Dec. 25 and the
lowest (10.32 kg ha-1) was from the crop sown on Nov. 25 (Table 3). Higher
unaccountable P2O5 on late sown wheat might be due to adverse climatic conditions.
Effect of nitrogen on unaccountable P2O5 was also significant. The highest
unaccountable P2O5 (11.91 kg ha-1) was observed from 60 kg N ha-1 (Table 3). The
lowest unaccountable P2O5 (9.59 kg ha-1) was observed from the application of 180
kgN ha-1 and it was at par with 140 kg N ha-1. Lower unaccountable P2O5 with higher
levels of nitrogen might be efficient utilization of available soil phosphorus by the
wheat crop.
Economic analysis
Cost of cultivation
Significantly higher cost of cultivation (NRs. 57.54 thousand ha-1) regarding with the
sowing dates was recorded from the crop sown on Dec. 25 and the lowest (NRs. 55.55
thousand ha-1) on Nov. 25 (Table 4). Nitrogen levels had also significant effect on cost
of cultivation. The highest cost of cultivation (NRs. 61.72 thousand ha-1) was recorded
from the application of 180 kgN ha-1 and the lowest (NRs. 51.37 thousand ha-1) was
from 60 kgN ha-1.
Net income
Significantly highest net return (NRs. 49.64 thousand ha-1) was obtained from the crop
sown on Nov. 25 followed by crop sown on Dec. 10 (NRs. 44.09 thousand ha-1) and
the lowest (NRs. 30.58 thousand ha-1) was from the crop sown on Dec. 25. There was
an increasing trend of net return up to 140 kg N ha-1 and decreased when increased to
180 kg N ha-1. The highest net return (NRs. 52.51 thousand ha-1) was from the
application of 140 kgN ha-1 followed by 180 kg N ha-1 (NRs. 47.62 thousand ha-1) and
the lowest (NRs. 28.08 thousand ha-1) was from the application of 60 kg N ha-1 (Table
4). Higher net return associated with 140 kgN ha-1 and sowing date on Nov. 25 was due
to higher grain and lower cultivation cost.
Benefit cost ratio (B:C)
Significantly highest B:C ratio (2.11) was observed from the crop sown on Nov. 25
followed by Dec. 10 (2.02) and the lowest (1.741) was from the crop sown on Dec. 25.
Regarding the nitrogen levels, highest B:C ratio (2.31) was observed from the
application of 140 kg N ha-1 followed by 180 kg N ha-1 (2.19). The higher B:C ratio
associated with 140 kg N ha-1 and sowing date on Nov. 25 was due to increased grain
yield and lower cost of cultivation. Similar results were also revealed by Manandhar
(2008).
59
24-25 March 2015
Table 4:Economic analysis of wheat cultivation through the sowing dates and nitrogen
levels of wheat under zero tillage at Torikhet, Chitwan, Nepal, 2011/2012.
Treatments
Cultivation cost
(× 000 NRsha-1)
Gross income
(× 000 NRsha-1)
Net return
(× 000 NRsha-1)
B:C
Dates of sowing
Nov. 25
55.55c
104.9a
49.64a
2.139a
Dec. 10
56.56b
100.5b
44.09b
2.002b
Dec. 25
57.54a
88.21c
30.58c
1.741
LSD (P=0.05)
0.4149
2.901
2.901
0.1189
SEm ±
0.1057
0.7388
0.7388
0.0303
N levels (kg ha-1)
N60
51.37d
72.29c
28.08d
1.573d
54.79c
92.22b
37.53c
1.775c
N100
58.32b
110.7a
52.51a
2.308a
N140
N180
61.72a
109.3a
47.62b
2.186b
LSD (P=0.05)
0.1213
1.939
1.939
0.0626
SEm ±
0.0408
0.6527
0.6527
0.0211
Values given in a row followed by same letter(s) do not differ at 0.05 level of significance
according to DMRT.
Conclusions
The results obtained from the investigation indicated that November 25 is the optimum
sowing date and 140 kgN ha-1 is the optimum dose of nitrogen for maximum yield of
wheat. Further it is advised that zero tillage is the alternative tillage system and suitable
resource conservation technology (RCT) to minimize the production cost and increase
net income. Soil nutrient (NPK) content increasedand soil physicochemical properties
improved on zero tillage system in rice-wheat cropping system.
Acknowledgement
Cereal System Initiatives for South Asia (CSISA-NP), Rampur, Chitwan is highly
acknowledged for providing financial support for this research. I am greatful to Dr.
Keshab Raj Pande (Chairman of advisory committee), Dr. Anant Prasad Regmi and
Prof. Dr. Shree Chandra Shah (members of advisory committee). My special thanks go
to all who directly and indirectly helped during the research period.
References
Arnon I. 1972. Plant population and distribution patterns in crop production in dry
regions. Vol. 1. Islamabad, Pakistan: National Book Foundation. Pp. 359–456.
Bhattarai D. 2012. Soil properties and nutrient uptake by wheat as influenced by
tillage, residue and nitrogen. M. Sc. Thesis. Tribhuvan University, Institute of
Agriculture and Animal Sciences.Rampur, Chitwan, Nepal. 94p.
Brady NC and RR Weil. 2005. The nature and properties of soils. Pearson Education
(Singhapore) Pvt. Ltd., Indian branch, 482 F.I.C. Patpargunj, Delhi, India.976
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Chaudhary NK, RC Sharma, NK Mishra and FP Neupane. 1993. Yield performance of
wheat cultivars at different seeding dates in relation to rate of grain filling and
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grain filling period.Pp. 479-481. In: Proc. of Wheat Research Report.
Neupane, FP (ed.). National winter crops technology workshop held on Sept.
7-10, 1995. NWRP, Bhairahawa. NARC and CIMMYT publications.
Giri GS. 1995. The response of surface seeded wheat to nitrogen at different growth
stages of the crop. Pp. 479-483.In: Proc. of Wheat Research Reports. RN
Devkota and EE Soari (eds.). National winter crops research workshop (1995).
NWRP, Bhairahawa, Pbl. NARC and CIMMYT.
Khan P, M Imtiaz, M Aslam, SKH Shah, MY Memon and S Siddiqui. 2008. Effect of
different nitrogen and phosphorus ratios on the performance of wheat
cultivar.Sarhad J. Agric. 24(2):233-240.
Manandhar S. 2008. Response of wheat cultivars to nitrogen management in Chitwan.
M. Sc. Thesis. Tribhuvan University, Institute of Agriculture and Animal
Sciences.Rampur, Chitwan, Nepal. 113p.
Mishra SK, DK Tripathi, NK Shrivastava, MZ Bed and CSingh. 2011. Effect of
different level of nitrogen on wheat (Triticumaestivum) after rice under zero
tillage. Ind. J. Sci. Res. 2(3):97-100.
MoAD.2012.Statistical Information on Nepalese Agriculture.Government of Nepal,
Ministry of Agriculture Development.Agri-Business Promotion and Statistical
Division.Singha Durbar, Kathmandu Nepal.
Nainwal K and M Singh. 2000. Varietal behaviour of wheat (Triticumaestivum. L) to
dates of sowing under terai region of Uttar Pradesh. Indian J. Agron. 45:107113.
Ortiz-Monasterio JI, Dhillon SS, Fischer RA. 1994. Date of sowing effects on grain
yield and yield components of irrigated spring wheat cultivars and
relationships with radiation and temperature in Ludhiana, India. Field Crops
Res. 37:169–184.
Rahman MA, MAZ Sarker, MFAmin, AHS Jahan and MM Akhter. 2011. Yield
response and nitrogen use efficiency of wheat under different doses and split
application of nitrogen fertilizer. Bangladesh J. Agric. Res. 36(2) : 231-240.
Randhawa AS, SS Dhillon, D Singh 1981. Productivity of wheat varieties as
influenced by time of sowing. J. Res. Punjab Agric. Univ. 18:227-233.
Sardana V, SK Sharma and AS Randhawa. 2002. Response of wheat varieties under
different dates and nitrogen levels in the sub- montane region of Punjab.
Indian J. Agron. 47(3):372-377.
Selles F, CA Campbell, RP Zentner, D Curtin, DC James and P Basnyat. 2011.
Phosphorus use efficiency and long term trends in soil available phosphorus in
wheat production systems with and without nitrogen fertilizer .Canadian J.
Soil Sci. 91(1):39-52.
Singh AK, K Pandey, SS Singh and SS Thakur. 1999. Agronomic management for
maximizing the productivity of late sown wheat (Triticumaestivum. L). Indian
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Wajid A, A Hussain, A Ahmad, AR Goheer, M Ibrahim and M Mussaddique. 2004.
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24-25 March 2015
SF-3
Response of Soybean to Boron and Molybdenum Application Under
Rampur ondition
Rita Amgain1 and Renuka Shrestha2
1
National Grain Legumes Research Programme (NARC), Nepalgunj, Banke
2
Agronomy Division (NARC), Khumaltar, Lalitpur
Abstract
Micronutrient deficiency is one of the major constraints in producing pulse crop
in Nepal. Field experiments were conducted in light textured soil to assess the
effect of Boron and Molybdenum on grain yield and yield components of
soybean during summer season of 2012 and 2013 at the field of Grain Legumes
Research Program, Rampur Chitwan. The experiment was laid out in ompletely
andomized lock esign with four replications. The fertilizer treatments were
control, 20:40:20 N P2O5 K2O ofkg ha-1 (recommended dose), 20:40:20
N P2O5 K2O of kg ha-1+1 kg ha-1 ofBoron soil application, 20:40:20 N P2O5 K2O
of kg ha-1 + 1% Borax as foliar spray at pre flowering stage, 20:40:20
N P2O5 K2O of kg ha-1 + 500 g Molybdenum ha-1, 20:40:20 N P2O5 K2O of kg
ha-1 + 1 kg ha-1 of Boron + 500 g Molybdenum ha-1, 20:40:20 N P2O5 K2O of kg
ha-1 +1 kg ha-1 of Boron +500 g Molybdenum ha-1+ 5 t ha-1 of FYMand 5 t ha-1
of FYM. The results showed that the year effect was non-significant on grain
yield, whereas the effects of different fertilizers and the interactions effect of
year and fertilizers were
significant. The grain yield and hundred seed
weight was significantly affected by treatments. Application of Boron increased
21 to 30% grain yield and increased seed size by13 to 18% over control.
Application of 20:40:20 N P2O5 K2O of kg ha-1 + Boron 1 kg + Molybdenum
500 gm ha-1+5 t ha-1 of FYM produced highest grain yield (2753kgha-1) in
comparison to other treatments. The application of the combinations of these
fertilizers
substantially increase the yield of soybean.
Keywords: Effect of boron and molybdenum, randomized complete black
design, yield component of soybean.
Introduction
Soybean is an important legume of mid hill, grown as intercrop with maize or in paddy
bund. In terai and inner terai, soybean cultivation as a sole crop is gaining popularity
due to high demand of soya meal in poultry industry and its diversified use of grains in
terms of livestock feeds and human food.
Being legume, soybean cultivation improves soil health through addition of fixed
nitrogen and organic matter. However, for optimal growth and development 17
essential nutrients are required by crop plants. While micronutrients are required in
relatively smaller quantities for plant growth, they are as important as macronutrients
as they are involved in the key physiological processes of photosynthesis and
62
24-25 March 2015
respiration (Marschner 1995, Mengelet al.2001) and their deficiency can impede these
vital physiological processes thus limiting yield gain. Boron (B) is one of the essential
micronutrients for soybean plant; it has good effect on the yield and yield quality of
soybean. Oplinger et al.(1993) reported soybean yield increase of 13 %t by spraying
0.28 kg B per hectare in soils with low B content. Molybdenum (Mo) is also important
micronutrients, involved in nitrogen nutrition and assimilation. In legumes, Mo serves
an additional function: to help root nodule bacteria to fix atmospheric N (Campo et
al.2000). Mo deficiency symptoms are often similar to N deficiency. In legumes, the
nitrogen-fixing ability of soil micro-organisms is severely hampered by Mo deficiency,
rendering them N-deficient. Soil analysis conducted by Khatri- Chhetri (1982)
indicated wide occurrence of micronutrient deficiencies in the Chitwan valley in the
inner Terai; a region of acid soils. Hence an experiment was conducted to study the
response of soybean to the application of Boron and Molybdenum on the yield and
yield components.
Field experiments were conducted to study the effect of Boron and Molybdenum on
the yield and yield components of soybean at National Grain Legume Research
Program(NGLRP), Rampur Chitwan, during summer season for two consecutive years
2012 and 2013. The soil of experimental site was sandy loam with slightly acidic
reaction (pH 6.1-6.2), organic matter content 1.69%-2.14%, Nitrogen content 0.09%0.10%, Phosphorus content 124.30-220.03 kg ha-1 and Potassium content 268-316 kg
ha-1 before planting. There were eight treatments comprised of control, 20:40:20 kg
NP2O5K2O ha-1 (recommended dose), 20:40:20 kg N:P2O5:K2O ha-1+1 kg Boron ha-1
soil application, 20:40:20 kg N:P2O5:K2O ha-1 + 1% Borax as foliar spray at pre
flowering stage, 20:40:20 kg N:P2O5:K2O ha-1 + 500 g Molybdenum ha-1 , 20:40:20
kgN:P2O5:K2O ha-1 + 1 kg Boron ha-1 + 500 g Molybdenum ha-1, 20:40:20
kgN:P2O5:K2O ha-1 +1 kg Boron ha-1 +500 g Molybdenum ha-1 + 5 t FYM ha-1 and 5 t
FYM ha-1. The treatments were tested in Completely Randomized Block Design
(RCBD) with four replications keeping gross plot size as 4 m x 3 m and net harvest
area was 8m2 per plot. Soybean variety Puja was sown on 28th June 2012 in first year
and on 30th June 2013 in second year at spacing of 50cm x 10cm. All fertilizer
combinations were applied as basal dose except treatment with foliar spray in which
1% borax was sprayed at pre flowering stage of soybean. Weeding, hoeing and
pesticide application were done when needed.
Five plants were randomly selected from each plot to measure plant height, number of
pods per plant and seed per pod. Seeds were sun dried and grain yield was recorded.
Data were analyzed using Genstat Discovery Edition.
Results and Discussion
Plant height
Effect of treatments on plant height was not significant in both years (Table 1).
However, the highest plant height of 59 cm was recorded from treatment 6 (20:40:20
63
24-25 March 2015
N: P2O5:K2O kg ha-1+ 1 kg Boron ha-1 +500 g Molybdenum ha-1) followed by
treatment 4 (20:40:20 NP2O5K2O kg ha-1 + 1% Borax as foliar spray at pre flowering
stage) 58 cm in 2012. In the second year, highest plant height 73 cm was recorded from
treatment 6 (20:40:20 N: P2O5:K2O kg ha-1+ 1 kg Boron ha-1 +500 g Molybdenum ha-1)
followed by treatment 4 (71 cm). On combined analysis, the treatments effect were
significant (p = 0.01). Treatment 6 produced the highest plant height of 66 cm.
Interaction between treatments and year was not significant.
Pods per plant
Number of pods per plant was affected significantly (p = 0.01) in first year (Table 1).
The highest number of pods per plant (124) was recorded from the treatment 3
(20:40:20 kg NP2O5K2O ha-1+1 kg Boron ha-1 soil application). Application of Boron
increased 20 to 32% in pod number as compare to control. In second year, there was
not significant effect on number of pods per plant. On combined analysis, the highest
number of pods per plant (110) was observed in plot treated with Boron with NPK
(treatment 3). interaction between treatment and year was not affected significantly.
Nodulation
Treatments effect on nodulation was not found significant in both years. Availability of
Molybdenum was one factor considered, since the soils are acidic but no response was
observed on nodulation. On combined analysis, application of molybdenum increased
slightly on nodulation but not affected significantly. The highest number of nodule per
plant (40) was observed in treatment 6 (20:40:20 kg N:P2O5:K2O ha-1 + 1 kg Boron ha-1
+ 500 g Molybdenum ha-1) and 7(20:40:20 kg N:P2O5:K2O ha-1 +1 kg Boron ha-1 +500
g Molybdenum ha-1 + 5 ton FYM ha-1) (Figure 1).
Table 1:Effect on plant height and pods per plant with application of different fertilizer
combination.
SN
Treatments
1
2
Control
20:40:20 N:P2O5:K2O kg ha-1
20:40:20 N:P2O5:K2O kg ha-1 + Boron
one kg ha-1 soil application
20:40:20 N:P2O5:K2O kg ha-1 + Boron
foliar spray
20:40:20 N:P2O5:K2O kg ha-1 +
Molybdenum 500 gha-1
20:40:20 N:P2O5:K2O kg ha-1 +
Boron+ Molybdenum
20:40: 20kg N:P2O5:K2O kg ha-1 +
Boron 1 kg ha-1 + Molybdenum 500
kg ha-1 soil application+ 5t ha-1 FYM
Compost 5 t ha-1
Mean
F value
LSD (<0.05)
CV, %
YxT
3
4
5
6
7
8
Plant height, cm
2012
2013
55
67
55
58
61
56
Pods plant-1, nos.
2012
2013
94
82
103
66
Mean
Mean
90
87
58
65
61
124
92
110
58
71
64
123
71
100
52
63
58
113
77
97
59
73
66
121
88
107
53
70
62
112
80
99
53
55
0.249
66
67
0.217
11.5
9.8
59
61
0.017
5.5
8.8
ns
113
113
0.011
16.2
8.7
102
82
0.742
45.5
31.6
ns
109
100
0.13
18.8
18.5
ns
8
64
24-25 March 2015
Nod per plant
40
Nodule per plant
35
30
25
20
15
10
5
0
1
2
3
4
5
6
7
8
Treatments
Figure 1: Nodule per plant for different treatments.
Grain yield
There was positive response of soybean to Boron in terms of yield increase in both
years. Similar effects on grain yield have been reported by Malla et al. (2007) and
Adhikari et al. (2008). In first year, highest grain yield (2620 kg ha-1) was observed
when the crop was treated with Boron with NPK from treatment 4 (20:40:20
N:P2O5:K2Okg ha-1 + 1% Borax as foliar spray at pre flowering stage) followed by
treatment 6 (2604 kg ha-1) when crop was treated with Boron and Molybdenum with
NPK. Treatments effect on grain yield was highly significant over control (Table 2). In
second year, the highest grain yield of 2912 kg ha-1was recorded when the crop was
treated with Boron and Molybdenum with NPK plus FYM (treatment 7) followed by
treatment 4 (2798 kg ha-1). On combined analysis, effect of treatment on grain yield
was observed highly significant. The highest mean grain yield of 2753 kg ha-1 was
recorded from the plot treated with Boron and Molybdenum with NPK plus FYM
(treatment 7).
Hundred seed weight
There was significant effect of treatment on hundred grain weight in both years (Table
2). In the first year, treatment 3 (20:40:20 kg N:P2O5:K2O ha-1 + 1 kg Boron ha-1 soil
application) produced the highest hundred seed weight (15.68 g) followed by treatment
6 (15.25 g). On combined analysis, the highest hundred seed weight was recorded from
treatment 3 (15.98 g) followed by treatment 4 (15.60 g). Application of Boron
increased seed size from 13 to 18% (two years mean data) as compared to control.
Similar findings have been reported by Adhikari et al. (2008).
65
24-25 March 2015
Table 2:Effect on grain yield and hundred seed weight with application of different
fertilizer combination.
SN
Treatments
1
2
Control
20:40:20 NP2O5K2O kg ha-1
Grain yield,
kg ha-1
Mean
100 seed
weight, g
Mean, g
2012
1840
2529
2013
2371
2202
2116
2376
2012
12.4
14.8
2013
14.4
14.4
13.4
14.6
3
20:40:20 NP2O5K2O kg ha-1
+ Boron one kg ha-1 soil
application
2557
2547
2562
15.7
16.2
16.0
4
20:40:20 NP2O5K2O kg ha-1
+ Boron foliar spray
2620
2798
2719
15.2
16.2
15.6
5
20:40:20 NP2O5K2O kg ha-1
+ Molybdenum 500 gm/ha
2316
2275
2306
13.9
14.5
14.2
2604
2682
2653
15.3
15.6
15.5
2572
2912
2753
14.9
15.3
15.1
2397
2429
2293
2510
2356
2480
14.6
14.6
15.2
15.2
14.9
14.9
0.056
< 0.001
0.002
493.1
11.2
252.6
10
0.04
1.4
1.7
6
7
8
20:40:20 NP2O5K2O kg ha-1
+ Boron+ Molybdenum
20:40: 20kgNP2O5K2O kg
ha-1 + Boron 1 kg ha-1 +
Molybdenum 500 kg ha-1 soil
application+ 5t ha-1 FYM
Compost 5 ton ha-1
Mean
F value
Treatment
LSD (<0.05)
CV, %
YxT
<
0.001
330.0
3.1
0.05
4
1.4
5.3
<0.001
0.9
6.1
ns
Conclusion
The result showed that grain yield and seed size were affected significantly by the
application of Boron at Rampur condition. The highest grain yield (2753 kg ha-1) was
observed from the crop treated with 20:40:20 kgN:P2O5:K2O ha-1 + Boron 1 kg +
Molybdenum 500 g ha-1+ 5 t FYM ha-1. Judicious use of chemical fertilizers (macro
and micro nutrients) in combination with Farm Yard Manure performed better crop
growth and increased production in sustainable way.
Acknowledgements
The authors thank to Mr DB Gharti, Co-coordinator GLRP, and Rampur for his
valuable suggestions and guidance during research period. Technical officers; Mr BP
Wagle and Mr Surendra Yadav, and all staff of GLRP, Rampur are highly
acknowledged for their untiring support during the experiment.
66
24-25 March 2015
References
Adhikari BH and G Sunar. 2008. Response of Boron to yield and yield components in
Mungbean at Rampur. In: Annual Report 2008/09, National Grain Legume
Research Program, Rampur Chitwan.
Campo RJ, UB Albino and M Hungria. 2000. Importance of molybdenum and cobalt
to the biological nitrogen ixation. Nitrogen Fixation: From Molecules to Crop
Productivity. FO Pedrosa, M Hungria, G Yates and WE Newton (eds.).
Springer, Netherlands. Pp. 597–598.
Khatri-Chhetri TB. 1982. Assessment of soil test procedures for available Boron and
Zinc in the soil of Chitwan valley. Ph. D. Thesis. University of Wisconsin,
Madison, USA.
Marschner H. 1995. Mineral Nutrition of Higher Plants, 2nd ed. Academic Press,
London, UK.
Mengel K, EA Kirkby, H Kosegarten and T Appel. 2001. Principles of Plant Nutrition.
Kluwer Academic Publishers, Dordrecht, The Netherlands.
Oplinger ES, RG Hoeft, JW Johnson and PW Tracy. 1993. Boron fertilization of
soybeans: A Regional summary Pp. 7–16.
67
24-25 March 2015
SF-4
On-Farm Monitoring of Improved Management of Farmyard Manure and
Soil Nutrient Fertility in the Middle Hills of Nepal
Bishnu K Bishwakarma1, Richard Allen1, Juerg Merz2, Bishnu K Dhital,
Niranjan P Rajbhandari1,Shiva K Shrestha1 and Ian C Baillie3
1
Sustainable Soil Management Programme (SSMP), HELVETAS Swiss Intercooperation,
Kathmandu, Nepal,
2
HELVETAS Swiss Intercooperation Nepal,
3
National Soil Resources Institute, Cranfield University, Cranfield, Bedford, UK
Abstract
Programmes to improve traditional soil management on the very small farms in
the mid-hills of Nepal have previously recommended inorganic fertilizers as the
main means of eN hancing soil fertility. Farmyard manure (FYM)
mainly to improve soil physical properties. Since 2000, the Sustainable
Soil Management Programme has promoted sustainable soil management
practices giving greater prominence to FYM as a nutrient fertilizer by promoting
improvements in its management and quality. FYM improvement involves:
careful collection, layering, turning and moistening of the manure; shading heaps
from sunlight to minimize N-volatilization; protecting heaps from rainfall to
reduce nutrient loss through leaching; and the systematic collection and
admixture of cattle and buffalo urine. The technologies have been adopted by
more than 100,000 farmers in the middle hills. Nitrogen content in FYM and
available nutrients in topsoil have been monitored on farms over periods of one
to three years. Results from 327 farms showed that FYM quality was
significantly but inconsistently improved, with mean N content increased from
0.89 % to 1.13 %. There were significant increases of 3.32 % to 3.77 % and 0.17
to 0.19 % in topsoil contents of organic matter and total N,
after the
adoption of SSM practices. Topsoil content of available P also increased but the
effect was inconsistent. There were no significant changes in topsoil pH. Topsoil
available K showed a significant decrease of about 10% overall. The practices
have been investigated under farm conditions, and the most positive and
important feature of the study was that participation by farmers and field level
extension workers imparted a sense of ownership in the implementation of the
research as well as the results.
Keywords: Farm yard manure (FYM), nutrient loss through leaching, organic
matter, soil- nitrogen, topsoil.
68
24-25 March 2015
Introduction
The farming systems in the Middle Hills of Nepal are characterized by close
integration of crop, livestock, forestry and grassland management. The traditional
farming systems included crop rotation, fallows, grazing of crop residues, stall feeding
and cut and carry systems, and the application of the resultant farmyard manure
(FYM). Part of the livestock fodder came from browsing or lopping of woodland, and
some off-site nutrients were imported via the FYM. In recent years arable cropping has
extended into more marginal lands but farm sizes have decreased, fallows have
shortened, and cropping has intensified. Woodlots have shrunk and water sources are
now further away, and the quantities of FYM and its imported nutrients have decreased
relative to the enlarged arable areas (Shah 1996). Although an integral part of the
traditional system, the FYM was haphazardly managed, with bedding casually laid,
FYM stored in the open, and spread when convenient. This style of management
resulted in deterioration in the FYM and nutrient losses by erosion, N-volatilisation,
and leaching. As a result of these pressures on land resources, soil fertility has declined
and become a national issue (Joshi et al. 1995). Jaishy and Subedi (2000) found that
total nitrogen to be low in about half of 9800 topsoil samples from across the country.
Organic matter levels were low in about two thirds of the samples, and available
phosphorous and available potassium in about one third. Further, more recent data
from SMD (2014) found low organic matter in 60% and acidic pH in 69% of 2100
topsoil samples from across the country.
Since 2000 the Swiss-funded Sustainable Soil Management Programme (SSMP) has
promoted a flexible package of environmentally and socially appropriate sustainable
soil management (SSM) techniques to farmers in the Middle Hills (SSMP 2009). The
package for the rainfed arable lands includes: improved FYM management, integrated
plant nutrient and pest management; integration of legumes, forage, fodder and
vegetable cash crops into traditional cropping systems; and better use of crop residues.
SSMP puts particular emphasis on improving the quality of FYM as an effective way
of maintaining soil fertility. SSMP (2009) recommendations to eN hance FYM quality
include: improved design and management of cattle sheds to facilitate the handling of
FYM; collection systems for cattle and buffalo urine; urine mixture into FYM;
systematic laying and turning of bedding materials so as to adsorb the added urine;
shading of FYM from direct sunlight at all stages - in the shed, pile, pit and field - so as
to minimise N volatilisation and prevent desiccation; shelter against direct rainfall and
runoff to minimise erosion and leaching; and moderate moistening of heaps when
necessary.
In order to monitor the uptake and effects of its recommendations, SSMP established
from the outset a network of benchmark farms, on which FYM and soils are
periodically sampled and analysed. The data are aimed at facilitating management and
planning, and also at motivating extension workers and farmers (SSMP 2010). This
study uses these data to examine the effects of SSM practices on FYM quality and soil
nutrient fertility.
69
24-25 March 2015
Study area and farming systems
In the past fifteen years SSMP has worked in 20 districts throughout the Middle Hills
of Nepal. The data used in this study come from 11 districts (Figure 1). Most SSMP
farms lie between 800 m to 2000 m asl, although some are as high as 2,400 masl. The
climate is warm temperate, with temperatures ranging from mean minima of 12.5 0C to
mean maxima of 25.5 0C (Gautam et al. 2004). Three quarters of theaverage annual
precipitation of about 2000 mm falls during the summer monsoon in June – September.
Pre- and early monsoon rainfall can be intense and erosive. The topography is rugged,
with local relief of up to 1000 m and most slopes steeper than 30%. Combined with
high intensity rainfall, the steep gradients make slopes prone to surface erosion and
mass movements (Shrestha 1992, Pariyar 2008). The soils are mostly freely drained,
stony, shallow to moderately deep, residual or colluvial Dystrudepts. Textures ranges
from sandy loam to clay loam and many soils have high contents of silt and fine sand.
FYM and soil analyses
SSM practices have been adopted by over 150,000 farming households since 2000.
About 2,500 of the SSM participant farms have been selected for monitoring. Resource
constraints preclude sampling and analysis on non-SSM farms as controls. This study
is based on the data from about 350 monitored farms on which SSMP practices have
been fully adopted. Data from farms with procedural errors, gaps or inconsistencies
were excised.The FYM and soils were sampled and analysed before the start of SSM to
establish baselines, and to indicate FYM and soil conditions under traditional practices.
The farms were re-sampled and analysed after one, two or three years of SSM. FYM
heaps were sampled at about six randomised points, thoroughly mixed, and bulked. A
subsample was analysed for moisture content by oven drying at 1050C, and was then
air-dried, pestle-ground, and analysed for Total N by Kjeldhal (Subedi et al. 2008,
Bajracharya 2009). Topsoils (0 – 15 cm) were hoe sampled on a randomised ‘W’
pattern of 5–10 points and bulked (Subedi 2000, Jaishy and Subedi 2000). An air-dried
and ground pestle-subsample was analysed for: pH in a 1:2.5 suspension in water;
organic matter by Walkley–Black; total nitrogen by Kjeldahl; available phosphorus
was extracted with sodium bicarbonate (Olsen) and assayed colorimetrically with
molybdenum blue; and available potassium was extracted with ammonium acetate and
assayed by flame photometry (Bajracharya 2009).
Statistical analyses
Inter-annual differences in the pre-SSM contents of N in the FYM and pre-SSM
nutrient contents of the soils were examined by one-way analysis of variance
(ANOVA). Pre- and post-SSM comparisons were by‘t’ tests for dependent samples.
Associations between variables were examined by Pearson correlations. Because some
data have somewhat non-normal distributions, effects were retested using Wilcoxon for
comparison of dependent samples, and Spearman for rank correlations. All statistical
analyses used Statistica Version 9.
70
24-25 March 2015
Results and discussion
FYM and soilnutrients
Preliminary indications of temporal drift in some baseline variables were tested by oneway ANOVA of the pre-SSM data. There were highly significant (p < 0.001)
differences between the pre-SSM N contents of FYM sampled in different years with
markedly lower pre-SSM values for 2000. There are also significant (p < 0.01) interannual differences in 2001-2006 pre-SSM data, but these appear to be more stochastic
than clinal. ANOVA of pre-SSM topsoil pH, organic matter, N and P showed no
significant inter-annual variations, but pre-SSM contents of K in soils sampled in 2000
were significantly higher than for other years (Table 1). The inter-annual difference in
pre-SSM K between topsoils sampled 2002 and 2003 was not significant.
Figure 1: Location of study areas, highlighting districts where topsoil monitoring was
undertaken between 2000–2006.
71
24-25 March 2015
Table 1: Inter-annual variation in pre-SSM baseline Total N in FYM and Available K
in monitored topsoils.
FYM-N
Topsoil Available K (K2O)
Year
2000
2001
2002
2003
2006
Significance of
inter-annual
ANOVA
n
161
15
41
22
p< 0.001**
Mean, %
0.795a
1.124b
1.018b
1.339c
n
261
16
50
p< 0.01**
Mean, mgkg-1
474b
363a
334a
-
Values with different letter superscripts are significantly different at p < 0.05
N contents of FYM increased substantially and significantly in three of the five series
and also in aggregate (Table 2). The most marked increase was for the series starting in
2000, and this may be exaggerated by unduly low pre-SSM values. The SSM effects in
the series starting in 2003 and 2006 were smaller and non-significant.
There were marked increases in topsoil contents of organic matter (SOM), total N and,
to a lesser extent, available P after SSM (Table 3). The largest and most consistent
effect was for topsoil SOM, which increased in all series and in aggregate. In four of
the six data sets the increases were significant (p<0.05), as confirmed by Wilcoxon.
The pattern for topsoil total N was similar but slightly less consistent, with significant
increases in aggregate and in three series, a non-significant increase in one series, and a
small but significant decrease in the fifth. The effects on topsoil available P were
inconsistent, with significant increases in aggregate and in two series and insignificant
decreases in the other three.
Table 2: Increases in total N in FYM after SSM.
Series
Interval N of Total N, %
(y)
sites
Start
End
mean
mean
2000 – 1
1
129 0.761
0.994
Increase % and % sites with
significance
increase
31***
69
2000 – 3
65***
2003 – 6
2006 – 7
All
3
3
1
1–3
32
41
22
225
0.976
1.018
1.339
0.895
1.610
1.094
1.348
1.138
‘t’ test significance of differences between means
7
ns
ns
<1
27***
** p < 0.001
81
51
50
67
ns p > 0.05
Soil pH values varied little, with no significant SSM effects (Table 4). This was
expected, as the addition of high quality FYM is likely to increase SOM respiration,
72
24-25 March 2015
and the associated acidity will tend to offset the addition of bases. Also pH is measured
on a logarithmic scale, and is intrinsically less variable than the other variables
(Bakeret al. 1981). There were significant decreases in soil K in three series and in
aggregate, a non-significant decrease in the fourth, and a small but significant increase
in the fifth (Table 4). The decreases may be exaggerated by inflated pre-SSM values in
2000 (Table 1). However, the decreases in the other series were similar to those for
2000, suggesting that the differences are real.
Soil physical properties
Nutrient availability and uptake are affected by the physical structure of the soil, which
can thus modify fertiliser benefits. The farmers were asked whether they noticed
differences in soil physical characteristics after adopting SSM practices. About two
thirds reported easier tillage, increased moisture availability, better soil aggregation,
and decreased crusting and clodding. Some particularly mentioned improved crops in
drier periods.
Discussion
This study exemplifies some recurrent methodological features of on-farm research in
developing countries. The most positive and important is that participation by farmers
and field level extension workers imparts a sense of ownership in the implementation
and the results. Another positive feature is that the practices are investigated under
farm conditions and with the resources available in everyday life. As most field
operations are done by the farmer, the research is relatively cheap, enabling large
numbers of cases. The improved confidence imparted by large ‘n’ values helps offset
the inevitably high inter-operator variability.
One of the disadvantages is the skewing of participation towards better educated and
more successful farmers. Even if the group is initially representative, it often ends up
weighted towards the more accessible, enterprising, aware, and wealthy farmers,
because poorly-resourced farmers are disproportionately affected by logistical
problems and are more likely to drop out. The wastage means that the researcher has
limited control of the statistical and spatial distributions in the final data set. The other
disadvantage particular to this study is the lack of samples from non-SSM farms as
controls. We use the pre-SSM data for comparison, but this is less satisfactory than
synchronous controls. Another concern in this study is the possible drift in the
laboratory analyses of N in FYM and K in soils. The inter-annual variability of preSSM N contents in FYM and particularly the low values for samples collected in 2000
may reflect fluctuations in climate, crop growth and the litter quality of crop residues
from preceding years, but there may be some methodological drift. This may also
contribute to the elevation of the 2000 pre-SSM topsoil K values for 2000. Despite
these caveats, our results show convincing responses to SSM. The protection of the
FYM heaps may reduce losses and slightly increase the volume of FYM, but the
substantial effects observed are attributed mainly to improved FYM management and
quality. Total N in the FYM is improved by SSM but the effect is erratic when
73
24-25 March 2015
allowance is made for the low baseline levels in 2000. The clearest SSM effect in
topsoils is for SOM but the increases for topsoil total N are almost as high and
consistent, as is to be expected from the strong and long-known association between
these attributes (Bishwakarma et al. 2014, Jenkinson 1990). SSM has a positive effect
on topsoil concentrations of available P overall, but the effect is erratic. The small but
significant and more or less consistent decrease in soil K after SSM was unexpected, as
the FYM contains K, and its incorporation should result in an enlargement of the K
pool in the soil. K is readily adsorbed on to organic matter (Krauss and Johnson 2002),
and the elevated SOM may adsorb some of the existing K as well as that added in the
FYM. However, this explanation is not corroborated by the positive correlation
between SOM and available K. The high positive correlation between SOM and N
confirms expectations that N status is largely determined by the organic matter. The
lower but still significant correlations of P and K with SOM suggest that these
nutrients benefit from the improved quality of the FYM as well as from its quantity.
74
24-25 March 2015
Table3:Increases in topsoil OM, N and P after SSM.
Interval
(y)
Series
2000
1
2000
2
2000
3
2002
5
2003
6
–
–
–
–
–
Overall
nos.
of
sites
Soil organic matter,%
Available P205, mg kg-1
Total N, %
Start
mean
end
mean
Increase %
and
significance
% sites
with
increase
start
mean
end
mean
Increase %
and
significance
% sites
with
increase
start
mean
end
mean
Increase %
and
significance
% sites
with
increase
1
88
2.82
3.44
22***
65
0.143
0.179
25***
59
26.21
39.02
49***
66
2
130
3.65
3.91
7ns
56
0.194
0.201
4ns
54
35.37
36.21
2ns
55
3
43
3.04
3.86
27***
72
0.157
0.225
43*
63
21.59
17.64
–18ns
53
3
16
3.34
3.39
1ns
62
0.179
0.169
– 6*
25
26.88
24.46
– 9ns
31
3
50
3.59
4.05
13*
66
0.181
0.202
12**
70
28.73
37.51
31**
62
1–3
327
3.32
3.77
14***
63
0.172
0.197
16***
62
29.77
34.16
15*
56
’ test significance of differences between means
*** p < 0.001
75
** p < 0.01
* p < 0.05
ns p > 0.05
24-25 March 2015
Table 4: Changes in top-soil pH and available K after SSM.
Series
Span
(years)
nos. of
sites
Available K20, mg kg-1
pH (1:2.5 water)
Start
mean
End
mean
2000–2001
2000 – 2002
2000 – 2003
2002 –2005
2003 – 2006
1
2
3
3
3
88
130
43
16
50
5.99
5.94
5.41
5.87
5.77
5.94
6.04
5.94
5.74
5.67
Increase
%
and
significance
– 1ns
2*
10***
– 2 ns
– 2 ns
All
1–3
327
5.85
5.93
1ns
t’ test significance of difference between means
%
sites
with
increase
51
57
86
25
48
Start
mean
End mean
Increase % and
significance
%
sites
increase
481
472
468
363
334
388
501
373
309
235
– 19**
6ns
– 20*
– 15ns
– 30**
30
51
28
56
30
56
448
404
– 10*
38
*** p < 0.001
76
** p < 0.01
* p < 0.05
with
ns p > 0.05
24-25 March 2015
Conclusion
Despite their limitations, large on-farm studies can contribute to our understanding of
the effects of changes in soil management. In the Middle Hills of Nepal, this study
indicates that management of FYM to improve its quality has beneficial effects on
topsoil contents of organic matter, total N and possibly available P.
Acknowledgements
We would like to thank staff of local NGOs and the Sustainable Soil Management
Programme for field sampling, the Agricultural Technology Centre Laboratory for
chemical analyses; the Swiss Agency for Development and Cooperation (SDC) for
long term funding, and HELVETAS Swiss Intercooperation for management support
and guidance; and of course the farmers with whom we work.
References
Bajracharya DL. 2009. Soil Analysis Manual. Agricultural Technology Centre,
Lalitpur.
Baker AS, S Kuo, and YM Chae. 1981. Comparison of arithmetic average soil pH
values with pH values of composite samples. Soil Science Society of America
Journal. 45: 828 – 829.
Bishwakarma BK, NR Dahal, R Allen, NP Rajbhandari, BK Dhital, DB Gurung, RM
Bajracharya and IC Baillie. 2014. Effects of improved management and quality
of farmyard manure on soil organic carbon contents in small-holder farming
systems of the Middle Hills of Nepal. Climate and Development. Accessed in 5
March 2014 from http://dx.doi.org/10.1080/17565529.2014.966045.
Gautam RP, S Vaidya and HB Sharma. 2004. District Development Profile of Nepal
2004. Informal Sector Research and Study Center, Kathmandu.
Jaishy SN and TB Subedi. 2000. Procedures for Soil Sampling and Analysis. Soil
Testing and Service Section, Lalitpur.
Jenkinson DS. 1990. Turnover of organic matter and nitrogen in soil. Philosophical
Transactions of the Royal Society, London, B 329. Pp. 361–368.
Joshi KD, A Vaidya, PP Subedi, SP Bhattarai, KD Subedi, DP Rasali, MRS Suwal, JK
Tuladhar, U Phuyal, and CN Floyd. 1995. Soil fertility system analysis in
relation to temperate fruit crops in high hills and inner Himalayan region of
Western Nepal. Working Paper 94/50, Agricultural Research Centre, Lumle.
Krauss A and AE Johnston. 2002. Assessing soil potassium, can we do better? 9th
International Congress of Soil Science, Faisalabad.
Pariyar D. 2008. Country Pasture and Forage Resource Profile. FAO, Kathmandu.
Accessed
in
26
February
201
4
from
http://www.fao.org/ag/agp/AGPC/doc/Counprof/PDF%20files/ Nepal.pdf
Shah PB. 1996. Soil fertility and erosion based unsustainability concerns in Nepal. In:
Proc. of soil fertility and plant nutrition management workshop. Soil Science
Division, Kathmandu.
SSMP. 2009. Farmer profiles from the Mid-hills of Nepal. Volume 1. Sustainable Soil
Management Programme, Khumaltar, Lalitpur.
77
24-25 March 2015
SSMP. 2010. Farmer profiles from the Mid-hills of Nepal.Volume 2. Sustainable Soil
Management Programme, Kathmandu.
Shrestha RK. 1992. Agro-ecosystem of the Mid-Hills. In:Sustainable livestock
production in the mountain agro-ecosystem of Nepal. Animal Production and
Health Paper 105. JB Abington (ed.). FAO, Kathmandu. Accessed in 26
February
2014
from
http://www.fao.org/docrep/004/t0706e/T0706E00.htm#TOC.
Subedi K, S Jaisi, TB Subedi, SN Mandal and BK Dhital. 2008. Sampling techniques
of farmyard manure and compost manure. Soil Management Directorate,
Agriculture Department, Kathmandu.
Subedi K. 2000. Soil sampling techniques. Sustainable Soil Management Training
Manual. Sustainable Soil Management Programme, Kathmandu.
SMD. 2014. Annual Report 2070/71 (2013/014). Soil Management Directorate,
Department of Agriculture, Harihar Bhawan, Lalitpur, Nepal.
78
24-25 March 2015
SF-5
Use of Optical Sensor for In-Season Nitrogen Management and Grain
Yield Prediction in Maize
Bandhu R B
and Parbati A
National Maize Research Program (NARC), Rampur, Chitwan
Abstract
Precision agriculture technologies have developed optical sensors which can
determine plant’s normalized difference vegetation index (NDVI).To evaluate
the relationship between maize grain yield and early season NDVI readings, an
experiment was conducted at farm land of National Maize Research Program,
Rampur, Chitwan during winter season of 2012. Eight different levels of N 0,
30, 60, 90, 120, 150, 180 and 210 N kg ha-1 were applied for hybrid maize
RML 32 X RML 17 to study grain yield response and NDVI measurement.
Periodic NDVI was measured at 10 days interval from 55 days after sowing
(DAS) to 115 DAS by using Green seeker hand held crop sensor. Periodic
NDVI measurement taken at a range of growing degree days (GDD) was
critical for predicting grain yield potential. Poor exponential relationship
existed between NDVI from early reading measured before 208 GDD (55
DAS) and grain yield. At the 261GDD (65DAS) a strong relationship (R2 =
0.70) was observed between NDVI and grain yield. Later sensor measurements
after 571 GDD (95DAS) failed to distinguish variation in green biomass as a
result of canopy closure. N
level had significantly influenced on NDVI
reading, measured grain yield, calculated in season estimated yield (INSEY),
predicted yield with added N (YPN), response index (RI) and grain N demand.
Measuring NDVI reading by GDD (261–571 GDD) allow a practical window
of opportunity for side dress N applications. This study showed that yield
potential in maize could be accurately predicted in season with NDVI
measured with the Green Seeker Crop Sensor.
Key ord :GDD grain N demand INSEY NDVI, response index.
Introduction
Nitrogen is the most limiting nutrient for crop production and has the greatest effect on
grain yield. Crop response to applied N is an important criterion for evaluating crop N
requirement for maximum economic yield (Fageria et al. 2005). The management of N
plays a key role in improving crop quality (Campbell et al. 1995) and optimal N
management will be influenced by crop type and crop rotation (Grant et al. 2002).
Previous research has shown that nitrogen (N) availability depends on seasonal
changes in soil water content, temperature, soil structure, and organic matter
distribution (Ranells and Wagger 1992). Fageria et al. (2005) stated that improving
nitrogen use efficiency is desirable to improve crop yields, reduce cost of production,
79
24-25 March 2015
and maintain environmental quality. Determination of the extent to which the crop will
respond to additional N can help the farmers to apply only what is needed. There have
been numerous studies that showed high correlations between certain vegetation
indices developed from spectral observations and plant stand parameters such as plant
height, percent ground cover by vegetation, and plant population (Raun et al. 2005 and
Stone et al. 1996). NDVI (Normalized Difference Vegetation Index) is used widely for
mapping plant growth. NDVI is defined as (NIR - Red) / (NIR + Red). The Red and
NIR values represent the reflectance in the Red and NIR bands, respectively.
Researchers at Oklahoma State University have developed an algorithm for maize
nitrogen fertilization based on optical sensors. The N fertilizer rates depends on
making an in-season estimate of the potential or predicted yield, determining the yield
response to additional nitrogen fertilizer, and finally calculating N required obtaining
that additional yield (Raun et al. 2005).
The experiment was conducted at the farm land of National Maize Research Program
(NMRP), Rampur, Chitwan. NMRP is located in between 27⁰40’ N latitude and 84⁰19’
E longitude and an altitude of 228 m above mean sea level in the inner terai (Siwalik
Dun Valley). The experiment was carried out during the September to February of
2013. The experiment was laid out in Randomized Complete Block Design (RCBD)
with three replications. Eight different levels of N (0, 30, 60, 90, 120, 150, 180 and 210
kg N ha-1) were applied for grain yield and NDVI measurement. Hybrid maize RML32 X RML-17 was planted in 12 sq. m plot with the row to row spacing 60 cm and 25
cm plant to plant spacing. Soil sampling was done before sowing and analyzed for total
N, available P, available K, Soil Organic matter and pH. The soil type was Ustic
Psamments (USDA classification) and was alluvial sandy loam in texture. The initial
total N content was low (0.052%), available P was high (254 kg ha-1), available K was
medium (155 kg ha-1), soil organic matter was low (1.57%) and very strongly acidic in
pH (5.2).
Plant Normalized Difference Vegetation Index (NDVI) was measured in each plot
using a Green Seeker hand held Crop Sensor (NTech Industries, USA). Previous
research showed that NDVI is an excellent measure of plant growth and N
requirements (Raun et al.2005). In order to generate the algorithm, planting and
emergence dates were recorded and used to compute the number of days from planting
to sensing in each zone. For this method, we eliminated those days where Growing
Degree Days (GDD) were equal or less than zero. The GDD values were calculated as:
GDD = [(Tmin + Tmax)/2] – 10°C; where, Tmin and Tmax are the minimum and
maximum temperatures, respectively. In Season Estimated Yield (INSEY), which is
the yield with no added N, was calculated by dividing the plant NDVI by the number
of days from planting to sensing (where GDD > 0). The Response Index (RI) was
calculated by dividing the average NDVI readings from the high N plots by the average
NDVI readings in the plots without N application. The predicted yield with added
nitrogen (YPN) and grain N demand was calculated as described by Raun et al. (2002).
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24-25 March 2015
Linear and nonlinear regression models were used to determine the relationships
between grain yield and NDVI using Genstat.
N level, NDVI and grain yield
Grain yield was significantly increased with applied N fertilizer (Table 2). Maximum
grain yield was produced with 180 kg N ha-1 which indicated that increased in more
than 180 kg N ha-1 had no yield benefit. The grain yield and NDVI measured in
periodic interval showed a good correlation with grain yield and NDVI reading
measured (Table 1 and Figure 1a). The NDVI reading was higher with increased N
applied treatment (Figure 1b). The sensor reading taken at different date from planting
to sensing date were calculated and described here as GDD. The NDVI measured at
261 GDD (65 DAS) showed a better fit among different GDD with r2 =0.78 (Figure 2).
Measured higher NDVI reading to a limit had increased grain yield in RML-32 X
RML-17 hybrid variety of maize at Chitwan condition. High correlations of early
season NDVI readings with the plant biomass were also shown in the research
conducted by Stone et al. (1996). Growth stage was a major factor in predicting yield
potential. Regression analysis showed that weak exponential relationships occurred
between NDVI and grain yield when sensor measurements were taken too early or too
late (Table 1). This was probably a result of the failure in distinguishing the NDVI
reading. However, a strong relationship between yield and NDVI was achieved at 261
GDD (Figure1a) with an r2 value of 0.70. Later sensor measurement (at 571 GDD and
later) relationships with grain yield were similar to earlier (before 208 GDD)
comparisons, where yield potential was not accurately determined (Table 2). Due to
canopy closure influence on the sensor field of view, the later NDVI readings were
unable to distinguish variation, similar to research findings for other remote sensing
techniques measuring NDVI (Vinã et al. 2004).
81
24-25 March 2015
7
y = 12.43x1.228
R² = 0.70
6
Grain yield (t ha-1)
5
4
3
2
1
0
0.00
0.10
0.20
0.30
0.40
0.50
0.60
NDVI
Figure: 1(a): Relationship between NDVI and grain yield
y = -7E-06x2 + 0.002x + 0.291
R² = 0.61
0.6
0.5
NDVI
0.4
0.3
0.2
0.1
0
0
30
60
90
120
N kg ha-1 applied
Fig. 1(b): nitrogen doses applied and NDVI
82
150
180
210
24-25 March 2015
Table 1: Correlation between NDVI measured at different days after sowing and
otherParameters.
GY
NDVI
-115
NDVI
-105
NDVI
-95
NDVI
-85
NDVI
-75
NDVI
-65
NDVI
-55
DM105
DM75
0.17
0.48
0.03
GY
NDVI-115
0.39
NDVI-105
0.71
0.12
NDVI-95
0.60
-0.10
0.65
NDVI-85
0.78
0.07
0.52
0.43
NDVI-75
0.74
-0.08
0.78
0.75
0.63
NDVI-65
0.78
0.05
0.56
0.60
0.54
0.70
NDVI-55
0.42
-0.09
0.41
0.60
0.27
0.62
0.56
DM-105
0.73
0.40
0.51
0.42
0.14
0.60
0.57
0.31
DM-75
0.10
-0.12
0.15
0.31
-0.15
0.07
0.17
0.17
SY
0.74
0.26
0.30
0.43
0.51
0.37
0.59
0.38
Predicted grain yield, response index and grain N demand
The predicted grain yields, INSEY, response index and grain N demand were
significantly varied with N levels. The established relationship between the harvested
grain yields and calculated INSEY showed a high correlation between yields and
INSEY in this study (Figure 2).The INSEY index estimates the plant biomass produced
per day when growth was possible. Furthermore, Raun et al. (2002) showed that the
plant NDVI readings and calculated INSEY can be used to predict grain yields. The
INSEY was increased with increased N doses upto 120 kg N ha-1 after that not much
varied (Table 3). The highest INSEY was recorded at 447 GDD which revealed that
maximum greenness was obtained during that growth period. At early stage and later
stage (before 261 GDD and after 571 GDD) the INSEYs were low and not much
varied with N levels. This might be due to poor canopy cover and low chlorophyll
content in leaves. The response index is the ratio of NDVI to without N and N rich
plot. The RI indicates the fertilizer response to added N fertilizer and was explained by
Johnson and Raun (2003). The RI was significantly affected with the N level and
maximum RI was recorded at 120 kg N ha-1 applied and followed by 180 kg N ha-1
applied treatment. The maximum RI value of 1.84 indicated that 84% more grain yield
can be obtained in comparison to without N fertilizer treatment with 120 kg N ha-1 with
NDVI reading prediction (Table 2). The predicted grain yield was calculated with the
RI. The Predicted grain yield was consistent only up to 120 kg N ha-1 after that
inconsistent with applied N to the soil which indicates that the N applied was not used
83
24-25 March 2015
efficiently or poor N use efficiency which indicated that major applied N lost to the
environment and we should improve N application in time or methods or rate. The
grain production N demand was significantly affected with N level; however, it was
based on predicted grain yield production. This results showed that for the maximum
grain yield of 4.75 ton ha-1 production requires 59.8 kg N ha-1 available during in
season. That amount was only for grain N demand but not for stover.
Table 2: Nitrogen level, measured grain yield, predicted grain yield, response index
and grain N Demand.
S.N N level, Measured
Predicted grain Response
GrainN demand,
kg ha-1
grain yield,
yield (YPN),
index (RI)
kg ha-1
-1
-1
t ha
t ha
1
0
2.21
2.61
0.00
2
30
3.43
3.23
1.25
17.32
3
60
4.47
4.29
1.65
47.00
4
90
4.24
3.70
1.42
30.51
5
120
5.04
4.75
1.84
59.80
6
150
5.24
4.07
1.58
40.66
7
180
5.55
4.70
1.80
58.35
8
210
F-test
5.45
**
4.57
*
1.77
*
54.65
**
LSD
1.00
0.85
0.37
23.9
CV,%
12.8
12.2
12.1
35.5
**=Highly significant, *= significant and ns= non-significant.
84
24-25 March 2015
8
Grain yield (t ha-1)
6
y = 598.6x0.935
R² = 0.21
y = 1730.x1.230 y = 4E+12x5.951
R² = 0.61
y = 4107.x1.397 R² = 0.70
R² = 0.52
340GDD
4
261GDD
2
208GDD
y = 3E+08x3.853
R² = 0.42
571GDD
0
0.003
0.005
0.007
0.009
0.011
INSEY
Figure 2: Relationship between in season estimated yield (INSEY) calculated at
different GDD and grain yield.
Table 3: Effect of nitrogen level on in-season estimated yield (INSEY) measured at
different GDD.
S.N. N
INSEY
level,
kg ha-1
208
261
340
447
571
696
840
GDD
GDD
GDD
GDD
GDD
GDD
GDD
1
0
0.0042 0.0050 0.0054 0.0092 0.0079 0.0076 0.0068
2
30
0.0048 0.0063 0.0066 0.0096 0.0086 0.0079 0.0066
3
60
0.0055 0.0083 0.0075 0.0100 0.0090 0.0081 0.0068
4
90
0.0051 0.0071 0.0074 0.0097 0.0091 0.0081 0.0068
5
120
0.0059 0.0092 0.0076 0.0102 0.0091 0.0081 0.0068
6
150
0.0044 0.0079 0.0075 0.0100 0.0089 0.0082 0.0071
7
180
0.0052 0.0091 0.0087 0.0103 0.0091 0.0083 0.0068
8
210
0.0060 0.0094 0.0087 0.0101 0.0090 0.0081 0.0068
F**
*
*
*
*
*
ns
test
LSD 0.0012 0.0016 0.0010 0.0005 0.0005 0.0002
CV, 12.4
12.3
8.4
2.9
5.3
1.7
3.3
**=Highly significant, *= significant and ns= non-significant.
85
24-25 March 2015
Conclusion
Measuring NDVI reading by GDD (261–571 GDD) allow a practical window of
opportunity for side dress N applications. This study showed that yield potential in
maize could be predicted in season with NDVI measured with the Green Seeker crop
sensor.
References
Campbell CA, RJK Myers and D Curtin. 1995. Managing nitrogen for sustainable crop
production. Fert. Res. 42: 277–296.
Fageria NK, VC Baligar and BA Bailey. 2005. Role of cover crops in improving soil
and row crop productivity. Comm. Soil Sci. Plant Anal. 36:2733-2757.
Grant CA, GA Peterson and CA Campbell. 2002. Nutrient considerations for
diversified cropping systems in the Northern Great Plains. Agron. J. 94:
186-198.
Johnson GV and WR Raun. 2003. Nitrogen response index as a guide to fertilizer
management. J. Plant Nutr. 26: 249–262.
Ranells NN and MG Wagger. 1992. Nitrogen release from crimson clover in relation to
plant growth stage and composition. Agron. J. 84:424-430.
Raun WR, JB Solie, GV Johnson, ML Stone, RW Mullen, KW Freeman, WE
Thomason and EV Lukina.2002. Improving nitrogen use efficiency in
cereal grain production with optical sensing and variable rate application.
Agron. J. 94 (4): 815-820.
Raun WR, JB Solie, ML Stone, KL Martin, KW Freeman, RW Mullen, H Zhang, JS
Schepers, and GV Johnson. 2005. Optical sensor based algorithm for crop
nitrogen fertilization. Commun. Soil Sci. Plant Anal. 36: 2759-2781.
Stone ML, JB Solie, WR Raun, RW Whitney, SL Taylor and JD Ringer 1996. Use of
spectral radiance for correcting in-season fertilizer nitrogen deficiencies in
winter wheat. Trans. ASAE . 39 (5): 1623–1631.
Vinã A, AA Gitelson, DC Rundquist, G Keydan, B Leavitt and J Schepers.2004.
Monitoring maize (Zea mays L.) phenology with remote sensing. Agric. J.
96: 1139– 1147.
86
24-25 March 2015
SF-6
Effect of Long-term Application of Organic Manures and Inorganic
Fertilizers on Soil Properties and Yield of Rice and Wheat under RiceWheat System
Narayan Khatri, Ram D Yadav, Nawal K Yadav, Surya N Sah and Kulananda Mishra
NARC,
Abstract
A long-term fertility experiment in rice-wheat system was initiated in 1997/98 to
study the effects of application of different combinations of organic and
inorganic sources of nutrients on soil properties and crop yield of rice and wheat
in at National Rice Research Program, Hardinath, Dhanusha. The experiment
was laid out in randomized complete block design with twelve treatments
replicated three times. Recent two years statistical analysis revealed that the use
of 100:30:30 kg ha-1of N:P2O5:K2O produced significantly higher grain yield of
rice (3.02 t ha-1) followed by 150:45:45 N:P2O5:K2O of kg ha-1 (3.00 t ha-1) and
100:30:30 kg N:P2O5:K2O +25 kg ZnSo4 (2.99 t ha-1). But, in case of wheat
significantly higher grain yield was found with the application of FYM @10
t ha-1 (2.59 t ha-1) followed by 100:50:30 kg ha-1 of N:P2O5:K2O (2.02 t ha-1)
and 150:75:45kg ha-1 of N:P2O5:K2O (1.99 t ha-1). A sharp decline in rice and
wheat yields was noted in
minus Nand P
K treatments during recent
years. The findings showed that the productivity of the rice and wheat can be
increased and sustained by improving nutrient through the judicious use of
organic and inorganic manures in long
in Nepal.
Keywords: Judicious use of organic manures, long-term soil fertility, rice and
wheat, yield.
Introduction
Rice-wheat system is one of the major cropping systems in Nepal whereas rice and
wheat occupy 1.5 and 0.76 Million ha, respectively and are grown in succession on
more than 0.56 Million ha which accounts 37 % of the rice and 85 % of wheat area in
Nepal (Tripathi et al. 2002). Rice – wheat system occupies one fourth of the total
cropped area and provides food, income and employment to Nepalese people. Wheat is
the third important food grain crop in Nepal after rice and maize. Since fertilizer is an
expensive and precious input, determination of an appropriate dose of application that
would be both economical and appropriate to enhance crop productivity, soil health
and consequent profit of the grower under given situation needs intensive study.
Farmers use chemical fertilizer in different doses in different methods. The application
of fertilizer either in excess or in less than optimum rate affects soil health, yield and
quality of crop to remarkable extent, hence proper management of both organic and
inorganic fertilizer is of immense importance (Meena et al. 2003). In most long-term
87
24-25 March 2015
experiments, a combination of mineral fertilizers and farmyard manure has generally
given the best crop yield and soil quality (Wang et al.2004, Chalk et al. 2003). Since,
the beneficial effects of long run use of organic manure incorporation and detrimental
effects of imbalance fertilizers have been reported by several workers, elsewhere.
Therefore, one of the most promising means for increasing yield and improving soil
quality in the rice-wheat system is to develop alternative nutrient management
practices. Keeping in the view of above facts, this long-term fertility trial in Ricewheat system was initiated to assess the effect of long-term application of organic
manures and inorganic fertilizers on grain yield of rice and wheat under rice-wheat
system.
Materials and Methods
A long-term fertility trial under rice-wheat-fallow cropping pattern has been carrying
out since 1997/98 at Research Farm of NRRP, Hardinath. In this paper, the record of
recent two year data are presented and interpreted. The experiment was carried out in a
Randomized Complete Block Design (RCBD) consisting of twelve treatments with
three replication in each year. Details of treatment are given in Table 1. Urea, DAP,
MOP and ZnSo4 as inorganic fertilizer were taken for study whereas sources of
organic manures was FYM only. Varieties used in rice and wheat were Sabitri and
Bhrikuti respectively. As regards to the fertilizers use, whole dose of P2O5, K2O, ZnSo4
and half dose of N2 were applied as basal dose and remaining half N was top dressed at
30-35 days after planting crops whereas FYM was applied about two weeks before
planting. Rice was planted at a spacing of 20 cm X 20 cm while wheat was sown in
rows of 25 cm apart. Each individual plot size was of 25 m2. All the required cultural
practices i.e. irrigation, weeding, and plant protection measures were adopted as per
need. The plant height, tillers no/m2, grain yield and straw yield of each treatment were
recorded. After recording data, data were put in Microsoft excel and analyzed by using
Genstat program.
Table 1:Treatment details of long-term fertility experiment.
Treatments
Rice
Wheat
T1
T2
T3
T4
T5
T6
T7
T8
T9
T10
T11
T12
00:00:00 N:P2O5:K2O kg ha-1
100:00:00 N:P2O5:K2O kg ha-1
100:30:00 N:P2O5:K2O kg ha-1
100:00:30 N:P2O5:K2O kg ha-1
100:30:30 N:P2O5:K2O kg ha-1
100:30:30 N:P2O5:K2O kg ha-1
50:15:15 N:P2O5:K2O kg ha-1
150:45:45 N:P2O5:K2O kg ha-1
FYM @ 10 t ha-1
100:30:30 +25 kg ZnSO4ha-1
FYM @ 10 t ha-1+50 kg Nha-1
Wheat stubble (15 cm) +50 kg
ha-1
88
00:00:00 N:P2O5:K2O kg ha-1
100:00:00 N:P2O5:K2O kg ha-1
100:50:00 N:P2O5:K2O kg ha-1
100:00:30 N:P2O5:K2O kg ha-1
100:00:30 N:P2O5:K2O kg ha-1
100:50:30 N:P2O5:K2O kg ha-1
50:25:15 N:P2O5:K2O kg ha-1
150:75:45 N:P2O5:K2O kg ha-1
FYM @ 10t ha-1
100:50:30 N:P2O5:K2O kg ha-1
100:50:30 N:P2O5:K2O kg ha-1
100:50:30 N:P2O5:K2O kg ha-1
24-25 March 2015
Analysis of two mean year data showed (Table 2) that tillers number m-1, grain yield
and straw yield except plant height were significantly differed with different treatments
in rice. The highest tillers number m-1 (174) was recorded in treatment T8 (150:45:45
N:P2O5:K2O kg ha-1), T5 (100:30:30 N:P2O5:K2O kg ha-1) which was at par with T6
(100:30:30 kg N:P2O5:K2O kg ha-1).
Table 2: Plant height, tillers no/m2, grain yield and straw yield of rice in a long term
fertility experiment conducted at NRRP, Hardinath (Mean of 2013/14 and
2014/15).
Grain yield,
Treatments Plant height, cm Tillers no sq.m-1
Straw yield,t ha-1
t ha-1
T1
159
143
1.71
2.37
T2
177
154
2.25
3.59
T3
215
152
2.53
3.91
T4
148
164
2.45
3.71
T5
176
174
2.81
4.11
T6
207
173
3.02
4.20
T7
167
142
2.34
3.01
T8
192
174
3.00
3.61
T9
152
143
2.77
3.51
T10
192
159
2.99
3.48
T11
167
162
2.88
3.49
T12
165
143
2.08
2.78
F test
ns
**
**
**
LSD 0.05
61.68
4.01
0.41
0.65
CV, %
20.5
1.5
9.3
11.7
Grand mean
176
157
2.57
3.49
Statistical analysis showed that the highest grain yield of rice (3.02 t ha-1) was
produced with the application of 100:30:30 N:P2O5:K2O kg ha-1(T6), which was
differed significantly over many treatments, having imbalance fertilizers. The grain
yield obtained from treatment T6 was found at par with the yield of T8 (3.00 t ha-1) and
T10 (2.99 t ha-1). Significantly, highest straw yield was recorded with the application
of 100:30:30 N:P2O5:K2O kg ha-1in rice.
In case of wheat, heading days, maturity days, grain yield and straw yield were
significantly influenced due to different treatments (Table 3). Heading days was found
significantly earlier of 90 days in treatments T6 (100:50:30 N:P2O5:K2O kg ha-1) and
T9 (FYM @ 10 t ha-1) but maturity days was found significantly longer of 122 days in
treatment T9 (FYM @ 10 t ha-1). Significantly the highest grain yield of (2.59 t ha-1)
was produced with the application of FYM @ 10 t ha-1 followed by 100:50:30
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24-25 March 2015
N:P2O5:K2O kg ha-1 (2.04 t ha-1). Highest straw yield of 2.81 t/ha was also recorded
with the application of 10 t ha-1FYM.
Table 3: Heading days, maturity days, plant height, tillers no/m2, grain yield and
straw yield of wheat in a long term fertility experiment conducted at NRRP,
Hardinath (Mean of 2012/13 and 2013/14).
Treatments
Heading,
days
Maturity,
days
Plant
height, cm
Tillers
nos. m-1
Grainyield,
t ha-1
Straw
yield,t ha-1
T1
91
120
78
171
0.9
1.33
T2
91
120
80
183
1.19
1.50
T3
93
121
84
181
1.37
1.69
T4
91
119
83
193
1.66
2.25
T5
91
120
84
174
1.34
1.88
T6
90
121
94
193
2.02
2.18
T7
92
121
87
171
1.75
2.05
T8
92
121
97
213
1.99
2.14
T9
90
122
95
212
2.59
2.81
T10
91
121
88
225
2.04
2.50
T11
T12
92
120
88
177
1.78
2.01
F test
LSD 0.05
CV, %
Grand mean
91
121
85
178
1.38
1.83
*
**
ns
ns
**
**
1.88
1.25
0.54
0.55
1.20
0.70
17.2
16.2
91
121
1.67
2.01
7.8
15
87
189
-1
-1
The lowest yield of rice (1.71 t ha ) and wheat (0.9 t ha ) were produced in the control
plot (no fertilizer). Combined effect of NPK was highly significant over N, N+P and
N+K in both rice and wheat. However, nitrogen alone yielded at par with N+P and
N+K treated plots.
Conclusion
In Baniniya, Hardinath conditon, application of fertilizers @100:30:30 N:P2O5:K2O
kgha-1 produced significantly highest grain yield of rice but highest grain yield of
wheat was obtained with the application of FYM @ 10 t ha-1in rice-wheat system.
Aknowledgement
We would like to express our deep sense of gratitude to Mr. N.K. Yadav, coordinator
of NRRP, Hardinath for his guidance and providing technical input for conducting this
experiment. The contributions made by all related scientists and personnels in carrying
out the experiments are highly acknowledged.
90
24-25 March 2015
Reference
Chalk PM, LK Heng and P Moutonnet.2003. Nitrogen fertilization and its
environmental impact. In: Proc.of 12th International World Fertilizer
Congress. Beijing, China. Pp. 1-15.
Meena SL, SSurendra, YS Shivay and S Singh. 2003. Response of hybrid rice (Oryza
sativa) to nitrogen and potassium application in sandy clay loam soils. Indian
J. Agric. Sci. 73(1): 8- 11.
Tripathi J, D Bhandari, Scott Justice, NK Shakya, TP Kharel and R Sishodia. 2002.
Resource Conservation Technologies for Wheat Production in Rice-Wheat
System. In: Proc. of 25th National Winter Crops Workshop.
Wang KR, Liu X, Zhou WJ, Xie XL, Buresh RJ.2004. Effects of nutrient recycling on
soil fertility and sustainable rice production. J. of Agro-Environ. Sci. 23: 10411045.
91
24-25 March 2015
SF-7
Nutrient management experiment in wheat – common bean system
at high hills condition in Nepal
Laxman Lal Shrestha1, Gautam Shrestha2
1
NARC, Agricultural Research Station, Vijayanagar, `Jumla
2
Regional Agricultural Research Station, Khajura, Banke
Abstract
The long-term experiment in wheat (Triticum aestivum) – common bean
(Phaseolus vulgaris) cropping system was initiated in Vijayanagar, Jumla since
2010. With six different doses of nutrient and three replications, research was
designed in randomized complete blocks. Results showed that there was no
significant change in soil chemical properties due to different nutrient treatments
during the four years period. Plant height (p value <0.02) and grain yield (p value
<0.001) were significantly different among the treatments in both wheat and
common bean. Number of tillers per square meter was significant (p value =
0.000) in wheat crop. Pods per plant and pod length (cm) was significant (p value
= 0.000) in common bean crop. Trend analysis results showed that there was
significant (p value <0.01) decline (slope > – 0.50) of soil organic matter content
from soil in all treatments except treatment with application of farmyard manure
30 t ha-1. There was significant (p value <0.01) decline (slope > – 250.0) in wheat
grain yield in all treatments. Regression analysis revealed there was significant (p
value = 0.000) decrease (slope = – 57.3) in soil available phosphorus with increase
in soil pH. Increase in soil organic matter content caused significant increase (p
value = 0.004, slope = 18.40) in soil available phosphorus but significant decrease
(p value = 0.022, slope = – 26.30) in soil available potassium. From the results, a
sustainable option from soil productivity perspective was application of farmyard
manure 30 t ha-1.
Keywords: high hills domain, soil fertility, integrated nutrient management
experiment.
Introduction
Long term experiments are continued in different ecological domains of Nepal.
Different fertiliser doses for wheat crop were revealed to be not a sustainable increase
in grain yield and maintaining soil fertility (Regmi et al. 2002, Gami et al. 2001,
Shrestha and Chaudhary 2015).
Common bean (Phaseolus vulgaris) is known by different names such as Rajma or
French bean or Green bean or Kidney bean or Snap bean or Haricot bean or Navy
bean. It is a staple grain legume crop in Karnali region, Nepal (Bhujel et al. 2014)used
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for soup (daal) purpose. Rajma bean is a summer crop in high hills cultivated after
wheat harvest.
As both crops are staple food crops in high hills, increase in productivity of both crops
can contribute in the food security in the Karnali region.
This experiment was conducted in Jumla to get optimum grain yield from wheat and
common bean cropping system in long-term. Though, Jumla is regulated as organic
district – knowledge of different nutrient requirements will help in combining different
organic manures to fulfil the crop demand to get optimum yield.
Research domain
This research was conducted in Agriculture Research Station, Vijayanagar, Jumla
which is located in the mid-western development region. It represents high hill region,
and located at an altitude of 2290 meters above sea level (masl) in the country and use
to get snowfall during the winter. With temperate climate, there was total annual
rainfall of 650 mm in 2014 (Tutiempo-Network, 2015). Maximum temperature of
28.5°C occurred in the month of June and minimum temperature of -1.9°C happened in
the month of February. There was highest amount of rainfall (201.17 mm) in the month
of July and no raindrop in the month of November. Similarly, highest humidity was in
the month of July (75.3%) and minimum humidity occurred in the month of December
(36.2%).
Experimental setup
With six treatments (Table 1) and three replications, research layout design was
randomized complete block (RCB). The plot size was 5 m x 2 m. In wheat (Triticum
aestivum) – common bean (Phaseolus vulgaris) cropping system, wheat variety;
Annapurna-1 was sown during the month of Kartik at the row to row distance of 25
cm. Due to snowfall wheat remained dormant during months of Poush and Magh. It
took on an average 150 days to initiate heading and 180 days to get ready for harvest.
Wheat was harvested during the month of Asar.
Common bean (Phaseolus vulgaris) variety PB0001 was sown during the month of
Asar. The crop geometry was maintained 50 cm x 10 cm. Common bean was harvested
in the month of Aashwin. It started flowering within 60 days of sowing and was ready
for harvesting on an average 100 days after sowing.
Farmyard manure was prepared locally collecting crop residue and application of
effective micro-organisms (EM) solution to quicken the composting process. For
wheat, half amount of nitrogen and full dose of phosphorus and potassium was applied
as a basal dose and half amount of nitrogen was top dressed in the mid – tillering stage.
In the case of common bean, half amount of nitrogen and full dose of phosphorus and
potassium were applied as a basal dose and half dose of nitrogen during flowering
period.
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24-25 March 2015
Soil texture of the experimental site was sandy loam. Initial soil chemical analysis in
2010 revealed soil pH 5.5, organic matter content 3.103%, soil available phosphorus
102 kg P2O5 per hectare and soil available potassium 175 kg K2O per hectare.
Table 1:Fertiliser dose for wheat and french bean at ARS, Vijayanagar, Jumla.
Treatment
1
2
3
4
5
6
Fertiliser dose (nutrient kg ha-1)
Wheat
N
P2O5 K2O FYM t ha-1
----100 50
25
6
120 55
30
6
130 60
35
6
140 65
40
6
---30
Common bean
N
P2O5
--100
60
120
65
130
70
140
75
---
K2O
-40
45
50
55
--
FYM t ha-1
-6
6
6
6
30
Data collection
Data on agromonic parameters were collected for each crop. Parameters like days to
heading/flowering, days to maturity, plant height (cm), plant per m2, panicle/pod length
(cm), thousand/hundred grain weight (g) and grain yield (kg ha-1) were common for
both wheat and common bean. Additionally, data on grains per panicle was collected
for wheat and pods per plant and grains per pod were collected for common bean.
The Soil samples were analysed to determine soil pH (1:1 soil:water solution), soil
organic matter content (modified walkley black method), soil available phosphorus
(spectrophotometer) and soil available potassium (ammonium acetate method).
Data analysis
Data were analysed using statistical software Rstudio version 0.98.1102. One way
analysis of variance was conducted to determine effect of different treatments in
agronomic parameters and soil characteristics. For significant results, posthoc analysis
was done using highly significant difference (HSD) at 0.05 level of significance.
Agronomic parameters and soil analysis results were performed trend analysis.
Regression analysis was conducted to determine the role of soil parameters in grain
yield. Similarly, regression analysis was performed to determine the role of soil
organic matter in soil pH, soil available phosphorus and soil available potassium. Role
of soil pH in soil available phosphorus and soil available potassium were also
determined. Graphs were plotted using Sigmaplot version 12.2.0.45.
Soil properties
There was no significant effect of treatments in the soil properties during 2011 to 2014
(Table 2). Compared with initial soil properties, soil pH, soil organic matter content
and soil available potassium were increased in all treatments whereas soil available
phosphorus was declined in all treatments. These results were on par with Rai and
Khadka (2009), which revealed no significant effect of treatments in soil chemical
properties except soil organic matter content (%) in the long-term experiment in paddy
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24-25 March 2015
– wheat cropping system at Khumaltar, Lalitpur initiated in 1993, data analysed from
1998 – 2002.
Table 2: Soil properties in the wheat – common bean cropping system at ARS,
Vijayanagar, Jumla during 2012 to 2014.
6.3±0.1
Soil
organic
matter, %
3.23±0.21
Soil
available
P2O5, kg ha-1
59.3±8.2
Soil available K2O, kg
ha-1
263.4±20.8
6.3±0.1
3.42±0.21
90.6±14.1
274.2±30.9
6.2±0.2
3.52±0.18
83.2±15.3
253.4±17.8
6.3±0.1
3.19±0.17
79.5±11.3
294.0±23.3
6.2±0.1
3.65±0.22
86.5±12.9
242.3±17.6
6.4±0.2
3.95±0.17
72.7±12.2
263.3±20.5
0.94
-8.3
0.074
-21.5
0.54
-61.4
0.68
-32.2
Treatment
Soil pH
00-00-00
*100-(50,60)(25,40) + FYM 6 t
ha-1
120-(55,65)-(30,45)
+ FYM 6 t ha-1
130-(60,70)-(35,50)
+ FYM 6 t ha-1
140-(65,75)-(40,55)
+ FYM 6 t ha-1
FYM 30 t ha-1
p value
HSD value
CV%
*N-(P,P)-(K,K) in the nutrient dose, nitrogen amount is common for wheat and common bean;
numbers in bold is for wheat crop and numbers in normal format is for common bean.
Agronomic performance
Wheat
Among treatments, the highest dose of chemical fertiliser (140-65-40 kg N-P2O5-K2O
+ FYM t t ha-1) application produced highest grain yield of 2490 kg ha-1 which was
60% higher than control (Table 3). From application of FYM 30 t ha-1, mean grain
yield of 2250 kg ha-1 was obtained compared to the highest chemical fertiliser dose. In
Khumaltar, Lalitpur condition, for wheat variety Annapurna-2,Rai and Khadka
(2009)revealed significant high grain yield of 2929 kg ha-1 with the application of 10040-30 kg N-P2O5-K2O ha-1. In Pakhribas, Dhankuta condition, Annapurna-1 variety
produced 5010 kg ha-1 with the application of 60-30-30 kg N-P2O5-K2O + FYM 15 t
ha-1 (Sherchan et al. 1999).
Common bean
There was a significantly higher grain yield (1490 kg ha-1) in the treatment with the
highest chemical fertiliser dose (140-75-55 kg + FYM 6 t ha-1) and comparable yield
with application of FYM 30 t ha-1(1250 kg ha-1). In contrast to these results Deibert
(1995) found no significant difference in common bean variety 'C-20' grain yield due
to phosphorus fertiliser application of either 0 or 90 kg ha-1 at Fargo, North Dakota,
USA condition in different years.
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24-25 March 2015
In Rampur, Chitwan condition, Shrestha et al. (2015) found common bean variety
PDR-14 produced grain yield of 662 kg ha-1 with the application of 120-40-40 kg NP2O5-K2O ha-1.
Table 3: Wheat agronomic characteristics in wheat - common bean cropping system
at ARS, Vijayanagar, Jumla during 2011 to 2014.
Treatment
Number m-1,
nos.
Panicle
length,
cm
Grains
panicle-1
1000
grains wt,
g
Grain
Yield,kg ha-1
62.0±1.8b
214.4±19.1b
7.2±0.4
33.1±2.7
38.9±2.2
1515.1±161.6b
64.7±1.9ab
255.7±5.4ab
8.0±0.3
34.1±2.4
37.7±2.7
2308.0±229.0a
Plant
cm
00-00-00
100-50-25 + FYM 6 t ha
-1
-1
ht,
68.0±1.6ab
265.3±10.7ab
8.1±0.3
36.6±2.2
37.1±2.5
2366.3±208.6a
130- 60-35 + FYM 6 t ha-1
65.7±1.7ab
297.8±17.3a
8.2±0.3
40.0±2.7
33.0±2.3
2363.5±180.5a
140-65-40 + FYM 6 t ha-1
67.9±1.7ab
297.8±11.1a
8.5±0.3
39.8±2.0
34.7±2.5
2489.5±153.3a
69.9±1.3a
267.9±11.3a
7.6±0.2
33.5±3.1
37.8±2.2
2251.7±130.6a
p-value
0.024
0.000
0.069
0.2
0.51
0.003
HSD value
7.0
51.3
--
--
--
728.7
CV, %
9.4
19.77
14.8
24.83
22.7
30.86
120-55-30 + FYM 6 t ha
FYM 30 t ha
-1
Table 4: Common bean agronomic characteristics in wheat – french bean cropping
system at ARS, Vijayanagar, Jumla during 2010 – 2013.
Treatments
00-00-00
100-60-40 + FYM 6 t ha-1
120-65-45 + FYM 6 t ha-1
130-70-50 + FYM 6 t ha-1
140-75-55 + FYM 6 t ha-1
FYM 30 t ha-1
Plants,
m-1
28.5±3.3
27.6±3.3
29.1±3.5
28.2±2.6
28.6±4.0
28.8±3.5
Plant ht,
cm
28.1±1.6b
39.3±1.9a
39.3±1.9a
44.1±1.6a
42.9±1.8a
37.4±1.9a
Pods
plant-1
5.2±0.2b
8.8±0.9a
10.0±1.1a
11.8±0.9a
11.8±0.5a
9.5±0.8a
Pod
length, cm
10.7±0.2b
11.1±0.3a
10.8±0.4a
11.7±0.3a
11.4±0.2a
10.9±0.3a
Grains
pod-1
3.8±0.2
4.1±0.1
4.1±0.1
4.3±0.1
4.1±0.1
4.2±0.2
100 grain
wt, g
39.6±0.8
40.8±1.6
42.2±1.5
39.1±0.7
39.6±0.8
40.1±0.6
Grain yield,
kg ha-1
759.2±140.9b
953.5±124.3ab
1220.7±124.3ab
1229.2±114.4ab
1490.0±155.7a
1252.9±124.4ab
p - value
1
0.000
0.000
0.000
0.330
0.380
0.005
HSD value
--
7.4
3.3
1.3
--
--
551.2
CV,%
39.8
20.400
36.800
9.800
13.000
9.100
42.900
Trend analysis
Soil properties
Among soil properties, there was significant soil organic matter content decrease
during 2010 to 2014 in all treatments (Table 5). Soil organic matter decline rate was
highest in the treatment with application of 100:50:25 kg N:P2O5:K2O + FYM 6 t ha-1 in
wheat and 100:60:40 kg N:P2O5:K2O + FYM 6 t ha-1 in common bean. It was maybe
due to with availability of phosphorus and potassium, microbial activities had
accelerated in the soil and required extra nitrogen was fulfilled from breakdown of soil
organic matter content. It was supported by results that with increased nitrogen supply,
soil organic matter decline rate has decreased (Table 5).
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24-25 March 2015
Soil available potassium content trend line was inclined in all treatments while the
effect was significant in control and the treatment with application of 100:50:25 kg kg
N:P2O5:K2O + FYM 6 t ha-1 in wheat and 100:60:40 kg N:P2O5:K2O + FYM 6 t ha-1 in
common bean (Table 5).
Table 5: Regression results of fertiliser treatments in soil characteristics in wheat –
common bean cropping system at NARC, ARS, Vijayanagar, Jumla during
2012 to 2014.
00-0000
*100-(50,60)(25,40)
+
FYM 6 t ha-1
120-(55,65)(30,45)
+
FYM 6 t ha-1
130-(60,70)(35,50)
+
FYM 6 t ha-1
140-(65,75)(40,55)
+
FYM 6 t ha-1
FYM
t ha-1
Adjusted R2 value
-0.045
-0.061
-0.076
-0.071
-0.051
0.002
slope
-0.136
-0.069
0.026
-0.0548
-0.105
-0.0794
p value
0.538
0.669
0.903
0.787
0.58
0.281
0.513
0.455
0.360
0.308
0.087
-0.790
-0.636
-0.539
-0.650
-0.339
0.002
0.004
0.011
0.019
0.151
Adjusted R2 value
-0.002
Slope
-6.04
p value
0.377
Soil available potassium
-0.071
5.1
0.797
-0.027
-16.4
0.443
-0.016
13.5
0.392
-0.041
-11.8
0.514
0.007
-17.0
0.314
Adjusted R2 value
0.183
0.329
0.194
-0.043
-0.032
0.127
Slope
50.2
95.1
44.7
20.6
18.1
41.9
p value
0.063
0.015
0.057
0.528
0.463
0.000
Soil characteristics
30
Soil pH
Soil organic matter
Adjusted R2 value
0.293
Slope
p value
-0.568
0.000
Soil available phosphorus
Crop yield
Treatments had significant negative effect in the wheat grain yield (Table 6). In the
case of wheat, fertiliser dose of 100:13:25 kg N:P2O5:K2O ha-1(Gami et al. 2001) or
100:18:25 kg N:P2O5:K2O ha-1 or FYM 4 t ha-1 on dry matter basis (Regmi et al. 2002)
or 100:30:30 kg N:P2O5:K2O ha-1 or FYM 10 t ha-1(Shrestha and Chaudhary 2015) or
120:35:33 kg N:P2O5:K2O ha-1(Yadav et al. 1998) were revealed to be not a sustainable
practice. Regmi et al. (2002) revealed yield decline of 50 kg ha-1 in Bhairahawa,
Rupendehi condition and Yadav et al. (1998) found 62 kg ha-1 in Masodha, Uttar
Pradesh, India condition. At Khajura, Banke condition Shrestha and Chaudhary (2015)
showed 60 kg ha-1 yield decline in treatment with 10 t ha-1 and with the application of
100:30:30 kg N:P2O5:K2O ha-1 yield decline of 71 kg ha-1.In high hills area, Nepal,
wheat grain yield decline rate exceeded 350 kg year-1 even with the application of
140:65:40 kg N:P2O5:K2O + FYM 6 t ha-1. The decline rate was least (373 kg ha-1) in
FYM application of 30 t ha-1 treatments among nutrient treatments (Table 6) with
comparable yield of 2250 kg ha-1 (Table 3).
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24-25 March 2015
Table 6: Regression results of crop grain yield in wheat – common bean cropping
system at NARC, ARS, Vijayanagar, Jumla during 2010 to 2014.
Wheat grain yield
00-0000
*100-(50,60)(25,40) + FYM
6 t ha-1
120-(55,65)(30,45)
+
FYM 6 t ha-1
130-(60,70)(35,50)
+
FYM 6 t ha-1
140-(65,75)(40,55) + FYM
6 t ha-1
FYM 30
t ha-1
Adjusted R2 value
0.429
0.453
0.390
0.467
0.713
0.057
slope
-268.7
-482.0
-413.0
-384.0
-390.9
-373.4
p value
0.012
0.010
0.018
0.009
0.000
0.003
Adjusted R2 value
0.232
-0.040
-0.080
-0.088
-0.099
0.126
slope
-202.7
-86.1
-49.4
-36.1
-16.7
190.0
p value
0.064
0.465
0.678
0.742
0.911
0.139
Common bean
Regression analysis
Role of soil pH
In high hills condition, increase in soil alkalinity caused significant (p value = 0.000,
slope = – 57.306) decline in soil available phosphorus (Figure 1). It was maybe due to
less rainfall in the research site, basic cations (e.g. Ca2+, Mg2+) are not leached down
from the surface. With increase in soil pH these cations rapidly fixed soil available
phosphorus into unavailable form.
There was no significant effect of soil pH in soil available potassium in high hills
condition.
Figure 1: Regression relation between soil pH and soil available
phosphorus) in wheat – common bean cropping system at
NARC, ARS, Vijayanagar, Jumla.
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24-25 March 2015
Role of soil organic matter content
From Figure 2.a, soil organic matter content had acidifying effect in the soil. Hence,
with increase in soil organic matter content, soil available phosphorus content
increased (Fig 2.b) whereas soil available potassium decreased (2.c).
(a)
(b)
(c)
Figure 2: Regression relation between soil organic matter content and soil pH (a),
soil available phosphorus (b) and soil available potassium content (c) in wheat
– common bean cropping system at NARC, ARS, Vijayanagar, Jumla.
Conclusions
Decline in soil organic matter content maybe the reason for decline in wheat grain
yield. However, at this stage of experiment – there were no significant regression effect
of soil organic matter content in wheat grain yield was found. Application of FYM 30
t ha-1 has caused no significant decline in the soil organic matter content. Additionally,
this treatment produced comparable wheat (2250 kg ha-1) and common bean (1250 kg
ha-1) grain yield to that of highest chemical fertiliser dose treatment. Furthermore, yield
decline rate was least (-373 kg ha-1) in the treatment with FYM 30 t ha-1. Hence, in
high hills condition increasing available quantity of organic manure and improving the
quality of organic manure can be the sustainable nutrient management option for wheat
– common bean cropping system.
Acknowledgements
Authors are indebt to Nepal Agricultural Research Council for providing fund support
to the project. Authors acknowledge the moral support provided by station chief, Ram
Chandrika Prasad, for this research project. Authors are also grateful to Agricultural
Research Station (ARS), Vijayanagar, Jumla personnel for logistic support.
References
Bhujel RB, CB Rana, PM Mahat, S Subedi andLL Shrestha. 2014. Evaluation of bean
(Phaseolous vulgaris) as an important pulse and cash crop in Jumla and similar
high hill region of Nepal. In: Proc. of 27th national summer crops workshop.
National Maize Research Program (NARC), Rampur, Chitwan.
Deibert E J. 1995. Dry bean production with various tillage and residue management
systems. Soil and Tillage Research. 36: 97-109.
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Gami S, J Ladha, H Pathak, M Shah, E Pasuquin, S Pandey, P Hobbs, D Joshy and R
Mishra . 2001. Long-term changes in yield and soil fertility in a twenty-year
rice-wheat experiment in Nepal. Biology and Fertility of Soil. 34: 73-78.
Rai SK and YG Khadka. 2009. Wheat production under long-term application of
inorganic and organic fertilisers in rice-wheat system under rainfed conditions.
Nepal Agricultural Research Journal. 9: 40-48.
Regmi A, J Ladha, H Pathak, E Pasuquin, C Bueno, D Dawe, P Hobbs, D Joshy, S
Maskey, and S Pandey. 2002. Yield and soil fertility trends in a 20-year rice–
rice–wheat experiment in Nepal. Soil Science Society of America Journal. 66:
857-867.
Sherchan D, C Pilbeam and P Gregory. 1999. Response of wheat–rice and maize/millet
systems to fertilizer and manure applications in the mid-hills of Nepal.
Experimental Agriculture. 35: 1-13.
Shrestha G and RD Chaudhary. 2015. Agronomic performance of paddy-wheat system
under long term soil fertility trial: a guide-line for fertilizer recommendation in
mid-western terai region. In: Proc.of 28th summer crops workshop. National
Rice Research Programme (NRRP): Nepal Agricultural Research Council.
Shrestha R, R Shrestha and BN Adhikari. 2015. Potential of Rajma (var. PDR 14) as
post rainy season crop in central terai of Nepal. In: Proc. of 28th Summer
Crops Workshop. National Rice Research Program, Hardinath, Dhanusha:
Nepal Agricultural Research Council.
Tutiempo-Network 2015. Climate Jumla. Tutiempo Network, S.L.
Yadav R, D Yadav, R Singh and A Kumar. 1998. Long term effects of inorganic
fertilizer inputs on crop productivity in a rice-wheat cropping system. Nutrient
Cycling in Agroecosystem. 51: 193-200.
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SF-8
Utilizing nvasive lant pecies, Eupatorium for Increasing and
roductivity Through Making iochar in Nepal
Naba R Pandit , Bishnu H Pandit and Hans-Peter Schmidt
NMBU, Norway,
Landell Mills Limited,
thaka nstitute for arbon ntelligence
Abstract
The majorities of poor people in Nepal rely mostly on agriculture for employment and
spend a high proportion of their income on food. Population densities continue to increase
and resource available for maintaining people’s livelihood is becoming increasingly
scarce. The available lands have decreased their productivity, which has not been able to
address livelihoods and food security issues. Thus sustainable increase in land productivity
in agriculture, through effective use of underutilized resources such as crop residues, rice
husk, animal left over and biomass of invasive plant species (such as Eupatorium)
continue to be crucial means through which both poverty reduction and economic growth
are sought. In order to address this issue, ADB funded project, Sustainable Rural Ecology
for Green Growth has tested the feasibility of using biomass of Eupatorium species for
making biochar that refers to materials produced through Pyrolysis. It means exposing
biomass to high temperatures with little or no oxygen. A total of 500 kg dried Eupatorium
produced 100 kg of biochar through kon-tiki kiln. Farmers of Dhading district are selling
biochar @ NRs. 20 kg-1, which means NRs. 2000 can be earned from 500kg of dried
Eupatorium. The result of cost benefit analysis shows that the net benefit from biochar
production is 50% through raw biochar sale. When used in agricultural land, the result
with the application of biochar in acidic soil
showed that maize production was
(pH <4.5). This land was completely barren or abandon prior to biochar application. In
the second years of application, maize yield increased significantly with the increase of
biochar dose.
Keywords: Biochar application, cost benefit analysis, invasive plant species, pyrolysis,
sustainable rural ecology for green growth.
Introduction
Biochar is an agricultural grade charcoal rich in carbon product produced when
biomass is heated in low oxygen environment or absence of oxygen commonly known
as “pyrolysis” (Lehmann 2007). Biohcar application has received a growing interest as
a sustainable technology to improve sandy acidic, highly weathered marginal lands
(Singh et al. 2010). A key physical feature of most biochars is their highly porous
structure and large surface area providing a habitat for beneficial soil microorganism
(mycorrhizae and bacteria) and moreover, helps in binding essential nutrient cations
and anions (Atkinson et al. 2010). Biochar quality depends on various types of
feedstocks being used and the processing circumstances under which they were
generated(Downieaet al. 2011). The research findings put forward that biochar
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24-25 March 2015
(biomass-derived black carbon) influence microbial populations and soil
biogeochemistry. Both biochar and microbial associations are potentially important in
various terrestrial ecosystem for improving soil leading to sustainable plant production
and soil carbon sequestration (Warnocket al.2007).
Black carbon considerably increase nutrient retention and CEC in soil (Liang et al.
2006) and in addition, increase water holding capacity through its physical
features(Lehmann and Rondon 2006). Conservation farming practice carried out with
4 t ha-1 of biochar in maize field of Kaoma, Zambia characterized with sandy acidic
soils results in strong increases in crop yield. This was attributed to an increased base
saturation (from <50% to 60%–100%), CEC (from 2–3 to 5–9 cmol/kg), increased
plant-available water (from 17% to 21%) (Cornelissen et al. 2013). Application of
biochar (Acacia bark charcoal) at 10 l per sq.m.along with NPK mineral fertilizers (50g
sq.m-1) in maize, cowpea and peanut field showed a significant yield almost doubled
compared with control plot (without biochar and NPK) in South Sumatra, Indonesia
(Yamato et al. 2006).
A single application of 0, 8 and 20 t per hectare of biochar for four years (2003-2006)
under maize-soyabean rotation did not result in significant increase in maize yield in
the first year but increases of 28, 30 and 140% for the application rate of 20 t per ha in
2004, 2005 and 2006, respectively. In addition, increase in soil pH, Ca and Mg as well
as reduction of exchangeable acidity has been observed in the soil where biochar was
applied (Majoret al. 2010). Large volume application of biochar (30 t ha-1and 60 t ha-1)
in cereal crop (wheat) field resulted yield of 32.1% and 23.6% larger than the control
plot (Vaccari et al. 2011).
In Nepal, soils are often acidic and have low C, N, P and exchangeable bases
(Schreieret al. 1994). Biochar is a potential method for increasing soil fertility, farm
production and sequestering carbon (Steiner et al. 2007). Moreover, biochar
application in soil encompasses biomass waste management, bio-energy generation,
soil health and productivity benefits (Chanet al. 2008). Nepal is an interesting case for
trying the concept since the country contains large variation of soil, crop and land use
types. The aim of the research was to assess the characteristics of biochar produced
from the invasive species “Eupatorium” and eventually explores its effect on naturally
grown field crops and livelihood economy.
Study area
The experimental sites (Research field trials) are located in Dhading and Rasuwa
district highlighted with red colour in the map (Figure 1) with an altitude of 1300 m
and 1378 m above sea level. Dhading is 74 km south west from capital city
Kathmandu valley comprising an area of 1926 sq.km. Likewise Rasuwa is 115 sq. km
north from Kathmandu covering an area of 1512 sq.km. The study area receives 2121.2
mm and 1850 mm average annual rainfall in Dhaiding and Rasuwa, respectively
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receiving highest precipitation in June/July and lowest in November/December. More
than 75% annual precipitation occurs during monsoon followed by remaining during
post monsoon, winter and pre monsoon season. Likewise, mean annual temperature in
Dhading and Rasuwa is 20o C and 15.4 o C.
Both district lies in central development region, a part of Bagmati zone, where
common agronomic cereal and legume crops encompasses maize, millet, black gram
and wheat. Under this study, agronomic effect of biocharon legume and cereal crop
(maize) was assessed via research field trials.
Feedstocks and Biochar production
Raw feedstock was selected based on their natural occurrence, growth habit and
importance from economical and environmental point of view. Eupatorium species was
identified as one of the most effective feedstock for the preparation of biochar in
context of Nepal. Eupatorium species with local name “Banmara” is an invasive plant
species (forest killer) commonly found in forest provinces, farm uplands/lowlands and
bank of the river. Moreover, Eupatorium species is naturally regenerated; hence,
biochar can be produced continuingly every year in a sustainable way. In general,
biochar production through effective use of invasive plant species “Eupatorium” could
be an outstanding approach for increasing soil fertility, farm production and carbon
sequestration.
For this study, Eupatorium feedstock was collected from the bank of the Trisuli river
and community forestry provinces in Dhading and Rasuwa district respectively.
Euaptorium was harvested during its maturity phase, hence, already in dry conditions;
however, still kept for sun drying for two days to reduce its moisture content. In single
run, 100 kg of dry Eupatorium was burnt in 1cu.m hole and the hole was covered with
corrugated tin plate without letting oxygen to pass inside the hole. This allows the
burnt eupatorium to undergo thermo-chemical decomposition at elevated temperatures
in absence of oxygen for 12 hours. In one run, 20 kg of black solid biochar was
harvested next day i.e. 20 % dry biochar generated from traditional hole method with
dry Eupatorium feedstock.
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Figure 1: Map showing study district.
Figure 2: Dry Eupatorium (upper left), burning Eupatroium in hole (upper middle),
hole covered with corrugated tin plate (upper Right), Biochar harvested
(lower right), Biochar yield and stored in Sacs (lower middle) and biochar
application in research field trials (lower left).
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24-25 March 2015
Research field trials design
Research farmer trials were established in Dhading and Rasuwa with various biochar
doses deployed in completely randomized block design (RCBD) and completely
randomized design (CRD), respectively. Composite soil sample from top soil (0-15cm)
and sub soil (15-30 cm) was collected and analyzed in the laboratory to identify the
preliminary soil status (pH, CEC, C, N, and P) of the study site. Soil with low pH, CEC
and reduced fertility was selected for biochar research field trials. Research field
comprised legumes (blackgram) and cereal crop (maize) in Dhading and Rasuwa,
respectively. There were sixteen treatment plot in Dhading district with the application
of 0, 5, 10, 15 ton/ha of biochar in four farmer blocks (replications). In Rasuwa district,
two more treatment with high (25 t ha-1) and very high dose biochar (40 t ha-1) was
included keeping other treatment similar to Dhading with four replications. Each plot
occupies 10 sq. meters consisting 16 treatment plots in Dhading and 24 plots in
Rasuwa. Thus the prepared biochar was applied on marginal/degraded sandy acidic
soils in Dhading and Rasuwa to assess the agronomic effect of biochar on legume and
cereal crop.
Biochar and FYM (farm yard manure) were broadcasted during land preparation phase
following tillage and harrowing practices in individual plot. FYM was added 8 t ha-1 in
Dhading soil for legume and 30 t ha-1 in Rasuwa for maize crop (Arun variety) based
on farmers traditional maize farming practices. Likewise, biochar was applied at the
rate of 0, 5, 10, 15 t ha-1 in Dhading and 0, 5, 10, 15, 25 and t ha-1 in Rasuwa soils.
Moreover, mineral fertilizer (Urea) was applied @ 1 teaspoonfulplant-1 during 1st
weeding time (30 DAS) of maize crop. On the contrary, FYM and only biochar was
applied in legume field without nitrogen fertilizer (Urea) as legume plant is meant to
fix nitrogen in soil from air. All other agronomical practices and plant protection
measures were applied uniformly to all treatments during the course of study.
Assessment of Biochar influence on maize crop yield was investigated under this
study. Maize and legume was harvested manually with harvesting equipment (sickle)
from the whole plots of respective block. After harvesting, all the aboveground
biomass was removed and measured for grain and biomass yield with the help of
digital weighing machine.
Biochar characterization
Biochar sample was collected and analyzed in the laboratory of Norwegian university
of life sciences (NMBU), Norway. pH of unwashed biochar was extracted with H2O
and CaCl2. Likewise CEC was measured with the extraction of 1 M NH4NO4.
Statistical analysis
Research field trials was arranged in randomized complete block design (one block
refers one replication) and completely randomized design (CRD) in Dhading and
Rasuwa respectively. Two tailed t-test (less than 30 observations) was performed for
the analysis of agronomic effect of various doses of biochar deployment in Dhading
and Rasuwa field trials.
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Biochar characterization
Biochar produced from traditional hole method was found highly alkaline in nature
with pH 10.4 (extraction with H2O) and pH 9.30 (extracted with CaCl2 ). Likewise,
total carbon (53.6%) and nitrogen (0.47%) content along with exchangeable cations
(Ca: 21C mol kg-1, Mg: 14C mol kg-1, Na: 0.17C mol kg-1, K: 41C mol kg-1) was also
found significantly higher as shown in table 1 below. On the contrary, acid cation (H+)
was null. Cation exchange capacity (CEC) ranged from 180-210 as which is a good
index in enhancing soil fertility. Thus, it can be concluded that the acidic soils blended
with biochar results in increased soil pH and CEC of the particular sites thereby
increasing farm productivity.
Table 1: Characterization of produced biohcar.
Run
1
2
3
pH
H2O
CaCl2
10.37
10.37
10.38
9.29
9.29
9.30
TC,%
TN,%
53.68
53.36
53.67
0.46
0.46
0.47
CEC 1 M NH4NO3unwashed biochar
mg l-1
Cmol kg-1
Ca K
Mg
Na
Ca K
22
91 9.2
0.13
18
39
23
84 9.3
0.13
19
36
25
97 10
0.23
21
41
CEC
Mg
13
13
14
Na
0.094
0.094
0.17
H+
0
0
0
192.11
184.20
208.23
Note:TC (total carbon), TN (total nitrogen), CEC (Cation Exchange Capacity), Ca, K, Mg, Na
and H+ are the ions of Calcium, Potassium, Magnesium, Sodium and hydrogen
respectively.
Crop yield
Legume and maize yield with various treatments of biochar, FYM, and mineral
fertilizer was assessed in Dhading and Rasuwa field trials respectively. Hence, the
agronomic effect of biochar both on legumes and cereals was investigated under this
study.
Legume yield
Application of higher dose (15 t ha-1) of biochar showed tremendous effect on legume
yield in sandy acidic soils of Dhading field trials even in absence of mineral fertilizer.
Average Legume yield increased gradually with increasing amount of biochar in all the
plots within a block as shown in table 2 below. Moreover, Average yield of legumes
grain was found significantly higher in high dose of biochar treatment (2.06 t ha-1) that
was almost doubled compared with control plot (1.38 t ha-1) that was calculated with ttest (two tailed t-Test, P<0.05). In addition, average legume biomass yield was
observed significantly higher in 15 ton/ha plot (two tailed t-Test, P<0.01 compared to
control plot.
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24-25 March 2015
Table 2: Legume yield with different amount of biochar treatment in Dhading soils
Treatments and yield
Block
Control
Biochar 5 t ha-1
Biochar 10 t ha-1
biochar 15 t ha-1
GY
BY
GY
BY
GY
BY
GY
BY
Block 1
1.32
1.83
1.35
1.68
1.65
2.3
1.98
2.34
Block 2
0.85
1.87
1.14
1.54
1.34
1.73
1.76
2.26
Block 3
1.64
2.26
1.65
2.45
1.97
2.75
2.13
2.52
Block 4
1.69
1.85
1.85
2.26
1.97
2.49
2.38
2.73
N=
4
Average=
1.38
4
1.95
1.50
4
1.98
1.73
4
2.32
2.06**
2.46***
** Significant at P < 0.05 level of significance with reference to control plot
*** Significant at P < 0.01 level of significance with reference to control plot
Note: GY: Legume grain yield t ha-1and BY: Legume Biomass Yield t ha-1, N: Number
of plot/observation in each block
Significant effect of biochar on legume yield may be that the legume fixes nitrogen,
one of the scarce nutrients from air that boost up soil nutrient and fertility in the soil.
Moreover, biochar binds this nutrient and water thus preventing nutrient and water
leaching from the soil that helps in plant available water and nutrient for longer time.
Thus, the result revealed that biochar was observed to be a strong fertility booster for
legume plants.
Maize Yield
A strong effect of biochar (higher dose) was observed on maize yield about the same
that of legumes (almost doubling of yield) in Rasuwa soils. Average maize yield
increased progressively with increasing amount of biochar dose however, in some plot
decline in yield was observed even in high dose compared with lower due to shade
effect of the respective plot. Shade effect was observed in 25 t ha-1 treatment plot (2
plots) and 5 t ha-1 plot (one plot). Other plots (21 plots) within one farmer block are
uniform, not affected with shade.
Average maize grain yield was observed significantly higher (two tailed t-Test,
P<0.01) in high dose of biochar treatment (5.9 t ha-1) that was almost doubled
compared with control plot (3.46 t ha-1). Likewise, biomass yield was also higher at
0.01 significance level (two tailed t-Test, P<0.01) for higher biochar treatment plots
(40 t ha-1).
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Table 3: Maize yield with different amount of biochar treatment in Rasuwa soils.
Treatments and yield
Control (no
biochar)
Block 1
Biochar 10
t ha-1
Biochar 15
t ha-1
Biochar 25
t ha-1
Biochar 40
t ha-1
GY
BY
GY
BY
GY
BY
GY
BY
GY
BY
GY
BY
3.19
9.2
4.19
11
4.9
11.9
6.55
14.5
4.82
13
5.79
12
4.1
10.4
1.99
9.5
3.97
9.8
4.15
11.3
5.9
13.7
6.1
14.9
2.74
8.5
4.79
5
4.49
11.3
5.08
12
2.03
7
6.42
15
3.81
9
4.13
7
3.61
8.5
3.95
12
2.72
13.8
5.6
12
N=
Average
=
Biochar (5
t ha-1)
4
3.46
4
9.27
4.5
4
8.2
4.25
4
10.3
5.0
4
12.4**
3.9
4
11.9
5.9**
*
13.5*
**
** Significant at 0.05 level with reference to control plot yield
*** Significant at 0.01 level with reference to control plot yield
Note: GY: Maize grain yield t ha-1 and BY: Maize Biomass Yield t ha-1, N: Number of
plot/observation in each block
Biochar farming economy
Traditional hole method is one of the low cost technology to produce biochar at local
farm level. Beside application of Biochar in their own private farmland, some farmers
in Dhading are selling raw biochar to nearby community people and cooperatives.
Farmers want to sustain their livelihood economy and sell the surplus biochar.
Thousand kilogram of Eupatorium (below 12% moisture content) was burnt with hole
method (1cu.m) in five run (200 kg biomass per run) to produce approx. 200 kg dry
biochar (20% biochar yield). After each batch, biochar was harvested quenching with
soil and continued next run. Total production cost incurred for this five run was NRs.
2600 (labour charge and packaging in containers). Biochar was sold @ Rs 20 per kg
fetching the benefit of Rs. 4000 for the produced biochar (200 kg) making a net
profit/margin of Rs. 1400. Hence, the benefit cost analysis showed that biochar
enterprise can make 35 % net benefit through sale of 200 kg biochar generated
from1000 kg dry eupatorium per day with simple/low cost biochar production
technology. Since the B:C ratio is positive (1.53) and greater than one, it can be
concluded that biochar production and marketing is economically viable in rural areas
with dry eupatorium feedstocks.
Conclusion
Biochar is a gaining popularity as a sustainable technology worldwide boosting soil
fertility to enhance crop production, sequestering carbon for addressing climate change
issues, reducing use of mineral fertilizer, improving water quality etc. Biochar is most
effective in sandy acidic, highly weathered and low CEC soils where yield is enhanced
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with increase amount of biochar. In Nepal, the sustainable increase in farm production
and soil fertility impacted from effective use of natural underutilized invasive forest
species “Eupatorium” producing quality biochar continue to be a crucial means to
combat poverty, hunger and food insecurity issues. Furthermore, agronomic effect of
biochar on various soils needs to be explored to be able to provide an overall
assessment of effectiveness of biochar in diverse Nepal soils. As biochar farming
proved to be environmentally and economically viable, supplementary feedstocks in
addition to Eupatorium such as corn cobs, crop residues, rice husk, and animal left over
and other locally available organic waste is necessary to consider for generating
sufficient amount of biochar. Biochar farming, as such, should probably be kept in an
important area to alleviate poverty/hunger by increasing yield as well as raising some
monetary income by selling the surplus biochar. This research concluded in prioritizing
biochar production/farming; hence, more experimental research on biochar and its
quality assessment from various academic institutions, I/NGOs, government body need
to be undertaken in developing countries like, Nepal.
Acknowledgements
This research study was conducted with the financial support from NGI (Norweigien
Geotechnical Institute), Norway as a part of PhD study under the collaborative
agreement between NGI and NAF Nepal. I am grateful to NGI, NAF and ADB (Asian
development Bank) team for the financial and technical assistance for this study. As
such, I would like to thank Dr. Gerard Cornelissen (Ph.D Supervisor), Dr. Sarah Hale,
Dr. Schimdt Hans-Peter, Dr. Bishnu Hari Pandit, Miss Shova Shrestha (NARC) for
their technical contribution under this study. Last but not the least; I am equally
thankful to the research farmer of Dhading and Rasuwa without whom the study would
not has been possible!
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Warnock DD, J Lehmann, TW Kuyper, and MC Rillig. 2007. Mycorrhizal responses to
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Yamato M, Y Okimori, IF Wibowo, S Anshori and M Ogawa. 2006. Effects of the
application of charred bark of Acacia mangium on the yield of maize, cowpea
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SF-9
Potential Options for Sustainable Land Management and Intensified
Agriculture
Bajracharya RM1, K Atreya1, N Raut1, BM Dahal1, HL Shrestha1, NR Dahal1, DK
Gautam2 and P Karmacharya1
1
Department of Environmental Science and Engineering, School of Science, Kathmandu
University
2
Nepal Agroforestry Foundation, Gwarko, Lalitpur
Abstract
The soil and land resources play a vital role in the local livelihoods of rural communities
as well as in the national economy. With much of the arable land already under cultivation
and the ever-increasing demands for food and fiber, agriculture has already moved
towards intensification. Yet, producing greater numbers of crops and quantities of food,
fibre and other materials on the same parcel of land often leads to soil fertility and
productivity decline with overall degradation of soil quality. Therefore, ways and means
to intensify agriculture to eN hance productivity without degrading the soil and land
resource base have become imperative. To this end, agro-forestry, agro-slivi-pastoral
systems, and the adoption of a variety of crop, soil and water management and
conservation practices offer potential to deliver multiple benefits without sacrificing the
very resource upon which the human population depends. This paper presents findings on
approaches to sustainable land management and intensification of agriculture related to
soil OM management and C sequestration for multiple benefits, and, agro-forestry as a
crop diversification strategy with both livelihood, and climate mitigation/ adaptation
benefits. Results of various studies indicated that sustainable soil management practices
could lead to significant C accumulations (4-8 t ha-1 over 6 yrs). SOC and soil C stocks
tend to increase with elevation due to cooler climate and slow decomposition rates.
Carbon stocks for the 3 LU types was in the order CF>AF/LH>AG, suggesting that
diversified cropping practices such as agro-forestry has good potential sequester C while
providing livelihood opportunities and climate adaptive capacity to local farmers. Biochar
amendment increased growth of both coffee plants and radish with mixed grass/weed
biochar being most effective. Biochar application also decreased emission of GHGs,
especially N2O.
Keywords: Agro-forestry, biochar, carbon sequestration, crop diversification, soil
quality.
Introduction
Soil and land resources have been the backbone of human civilization ever since prehistoric communities established permanent settlements and began settled agriculture
some 10,000 years ago (Darlington 1969). Historical records show that past
civilizations (such as the ancient settlements of the Tigris-Euphrates and Nile River
valleys), flourished because of access to fertile soils and likewise they declined as a
result of land degradation and loss of fertility of agricultural lands (Hillel 1992). Yet
over the millennia, through traditional practices handed down over the generations,
previous human communities learned to manage soils and cultivate their lands, even in
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harsh climates and terrains like the arid region of Egypt and mountainous regions of
South Asia (Hillel 2007).
Following the industrial revolution in the 1800s the world population has grown
tremendously, surpassing 7 billion and growth is still rapid in LDCs of Asia, Africa
and the Middle East. Arable land has essentially reached the limits of expansion but
pressures on land resource base continue to increase, with ever-greater demands for
settlements, food and fibre production. Clearly then, the need for producing more food
on the same amount of land has fuelled agricultural intensification. Moreover, the
impending climate change poses major challenges to production and human wellbeing. Hence there is an urgent need for “sustainable” intensification of agriculture as
well as land management.
Agricultural intensification is regarded as any change in the cropping or livestockrearing practices that makes use of a fixed area of land more frequently or intensely
than previous traditional or conventional practices. Therefore, an increase in the
number of crops grown per annual cropping cycle, increase in the stocking rates of
livestock grazed on a parcel of land, or change in types or sequences of crops grown
(for example intercropped or relayed) are all forms of agricultural intensification
(Boserup 1965, Carswell, 1997, Dahal et al. 2008). Agricultural intensification can
have both beneficial and adverse impacts on the environment and human societies.
While intensified production systems provide higher yields, and therefore, returns, it is
often achieved through the use of chemical fertilizers and synthetic pesticides, which
have far-reaching and long-term consequences for ecological balance and human
health. But with proper balance of inputs and an integrated, holistic approach to
farming and land management, it is possible to achieve production goals with while
minimizing adverse impacts to the environment and human health (Brookfield 2001,
Linquist et al. 2007, Dahal et al. 2009).
Soil is an essentially non-renewable resource upon which natural ecosystems and
agriculture depend. It forms the interface and acts as a buffer between terrestrial
systems and aquatic systems as well as the atmosphere. Soil organic matter (SOM) can
be regarded as a bio-physical property of soil and perhaps the single most important
constituent determining soil quality. It has a profound influence on many soil
properties and is a dynamic and complex entity having major implications for soils.
Soil degradation is known to have major consequences for environmental quality along
with food security (Lal 2007, Lal et al. 2011).
Sustainable land management and intensified agriculture involves three key
components, namely, sustainable soil management practices, crop improvement and
diversification, and, water and runoff management. Sustainable soil management
revolves around organic matter management and integrated nutrient/fertility
management. Crop management includes improved hybrid varieties as well as
diversified cropping patterns. Water or runoff management involves water harvesting
and recharge, careful disposal of excess water, and, water conservation along with
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24-25 March 2015
micro-irrigation.
This study presents a few approaches to sustainable land
management and intensification of agriculture focusing on: SOM management and C
sequestration for multiple benefits; and, agro-forestry as a crop diversification strategy
with both livelihood and climate mitigation/adaptation benefits.
Sustainable soil management (SSM) practices were introduced by Helvetas of the SDC
in 15 mid-hill districts of Nepal. These SSM are centered on SOM management and
integrated fertility management. They include farmer practices such as: Improved
cattle sheds for separate collection of urine and manure; improved composting with
protection from sun light and rain leaching (roof or cover); application of cattle/human
urine as N source; legumes, fodder plants, vegetables and cash crops (Bajracharya and
Atreya 2007).
Agro-forestry along with diversified cropping has potential as a sustainable land use
practice, particularly in hilly regions that do not support intensive food crop
production. Such practices offer opportunities for poor rural communities to generate
income from high value crops such as medicinal and aromatic plants (MAPs) and fruit
tree under unpredictable climate conditions and hence are good climate change
adaptive strategies. Moreover, permaculture can, over time, lead to increased carbon
capture and storage over conventional agriculture, thus also serving as a climate
mitigative approach. Studies have shown these systems to be well suited to hill regions
with marginal and steeply sloping land and can lead to improvement of farmers’
livelihoods and adaptive capacity (Tacio 1993, Zhu et al. 2000, Pandit et al. 2012 and
2014).
Biochar as a soil amendment has numerous benefits that could eN hance soil quality
and productivity, especially on marginal lands. Biochar is a pyrolysis product of
vegetative biomass combusted under low oxygen conditions. It has the potential to eN
hance the carbon storage and longevity in soils while simultaneously increases soil
productive capacity (IBI 2012). It has been known to be used by ancient civilizations
in the Amazon, North West Europe and the Andes (Sombroeck et al. 1993, Sandor and
Eash 1995, Downie et al. 2011). The unique structural, porosity, and nutrient retention
characteristics of biochar enables it to acts as a catalyst for microbial activity. Highly
stabile and resistance to microbial breakdown biochar acts as sites for increased water
and nutrient retention (Sohi 2012).
Study conducted on farmer fields under SSMP Programme of SDC
This study was conducted in order to estimation of the total SOC sequestration
potential in SSMP farm areas (Bajracharya and Atreya 2007). Four replicate farm
fields in 4 districts with SSMP interventions were selected, namely, Baglung, Syangja,
Kavrepalanchok and Sindhupalchowk. Comparison of SOC in farm fields over 6 years
of SSM practices (mainly improved compost/FYM) were conducted by sampling 4
replicate farms in each district and comparing values with baseline soil organic C data.
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The soils on upland farms in each of the districts were sampled in four depth
increments: 0-15, 15-30, 30-60 and 60-100 cm to determine total soil C stocks.
Calculation of the SOC stocks were done as follows:
Total SOC stock (t ha-1), Doc = SOC x Bd (i) x H x (104 m-2 ha-1) ----------- (1)
Where,
Doc = Soil organic carbon density (t ha-1)
SOC = Average soil organic carbon content of soil (%)
Bd = Average bulk density of soil samples (t m-3)
H = Thickness of the plow layer = 0.15 m
Further, the determination of the SOC increase rate (t ha-1 y-1) was done using the
following equation:
SOC = βY + C ------- (2)
Where,
β = Slope of the regression line
Y = Year (independent variable)
C = Regression constant
Finally, estimation of the total SOC sequestration potential in SSMP farm areas across
the Nepal hills (in millions of tons) was done by extrapolation of average SOC increase
over the period in the four districts to the entire area in all 15 SSMP districts.
Moreover, the hypothetical payments to farmers for eN hancing soil C accumulation
under a carbon trading scheme was determined. The calculation of total monetary
benefits under carbon trading as per the Kyoto Protocol using nominal payments of
$2.50 and $5.00 per ton of C sequestered in soil were presented.
Study on land management impacts on SOC & soil quality
Three districts in central Nepal representing 3 agro-ecological zones: Chitwan (200300 m); Gorkha (1000-1100 m); and, Rasuwa (1600-1700 m) were selected for the
study. In each district, plots were chosen on three land management regimes, namely,
community forests (CF), Agro-forestry or leasehold forests (AF/LH), and upland
agriculture (AG). Four replicate plots in each LM type for each location (500m2 forest
plots; farm fields) were randomly chosen for quantification of total C stocks. The
above-ground biomass carbon (AGB-C) was calculated by measuring diameter at
breast height (DBH) and tree height and applying the allometric equation by Chave et
al. (1985). The below-ground biomass carbon (BGB-C) was estimated as 20% of the
AGB-C. The leaf-litter, herbs and grass carbon (LHG-C) was determined by
destructive sampling and dry-ashing in a muffle furnace at 550 ⁰C. The soil organic
carbon (SOC) stocks was derived from the soil organic matter content by loss on
ignition and the dry bulk density (BD) of the soil. Baseline soil properties such as soil
texture, pH, BD, SOC, and total nitrogen (TN) were determined by standard methods
according to the USDA-ASA Monograph No. 9, Parts 1 and 2 (Page et al. 1982, Klute
1986).
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24-25 March 2015
Effects of biochar on growth of coffee/vegetable plants and GHG emissions from
soil.
Field trials to examine the effect of biochar application on coffee plant growth and the
growth performance of vegetables were established at two locations during 2013 and
2014. At Panchkhal in Kavre district, a coffee nursery trial with different rates and
types of biochar was conducted to determine the effect of different combinations and
rates of application of biochar on coffee plant growth. Biochar made from coffee
pulp/husk or grass/weeds were applied at 2 t ha-1 and 4 t ha-1 with and without cattle
urine addition. In a separate field trial at Saraswatikhel, Bhaktapur, an agroforestry
trial using coffee planted in rows with vegetables (radish) planted between the rows
was established. Here a constant rate of 4 t ha-1 of biochar made from grass/weed
feedstock was applied to both the coffee and radish plants. In both trials, the growth
rate (height of plants) was monitored over a period of several months.
The key findings and notable results of each of the studies are summarized in the tables
and figures below and discussed in light of sustainable management of soils for eN
hancing productive capacity of the land.
Effect of sustainable soil management practices on SOC accumulation
This study revealed that in the fours study districts, the average soil organic matter
contents, and hence SOC amounts, increased significantly compared to baseline values
at each of the farm fields where SSM practices, such as improved composting and
application of cattle urine, were adopted by the local farmers (Table 1). The mean
SOC contents at the SSM farms in the four districts ranged from two to three times the
baseline amounts over a period of six years. The results clearly indicated that total
carbon accumulation in soils and the corresponding amounts of carbon sequestered in
agricultural lands in the mid-hills region of Nepal could be significantly increased
through the use of such SSM practices. This has beneficial implications for the fertility
and productivity of these hill soils as well as for climate change mitigation through
carbon capture and sequestration.
Table 1: Mean SOC contents (%) of upland soil before and after 6 years of SSMP in
four districts of Nepal.
District
Baseline
3-year mean
6-year mean
Baglung
Kavre
Sindhupalchowk
Syangja
Mean ±Std.Dev.
1.60
0.68
1.19
2.29
1.44 ± 0.86
3.72
1.36
1.31
2.97
2.34 ± 1.20
4.96
2.99
2.45
6.37
4.19 ± 1.81
Using low and high carbon accumulation scenarios based on Table 1, the SOC increase
trends for each case are depicted in Figure 1. The mean SOC accumulation over 6
years for the low carbon accumulation scenario was 2.72 % SOC, while that for the
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24-25 March 2015
high C accumulation scenario was 4.19% SOC. Based on these C accumulation rates,
the total carbon stocks accumulated over the 6-year period for each case over the entire
agricultural land area (67,000 ha) of the 15 SSMP districts would be 2.7 million tons of
carbon (low scenario) and 4.6 million tons carbon (high scenario), respectively (Table
2). Upland agricultural soils have considerable potential to accumulate carbon in cool
climates at higher elevations where farmers apply high amounts of farmyard manure as
reported by other researchers (Shrestha and Singh 2008, Dahal and Bajracharya 2012,
Dahal and Kafle 2013).
Then, taking nominal carbon trading values of $ 2.50 t-1 C in the low scenario case and
$ 5.00 t-1 C in the high scenario case, the value of SOC accumulated in 6 years over
the 15 SSMP districts of the Nepal mid-hills would range from about USD 2 million to
a high of USD 13.5 million. Or on average, a total of USD 6.6 million could be
received as compensation for carbon accumulated due to farmers adopting SSM
practices in the mid-hills over a period of 6 years (Table 2). Such returns for climate
mitigative actions by local farmers would offer good incentives for them to conserve
their soils through adopting sustainable farming practices for improving the fertility
and productivity of their lands.
Table 2: Estimated C stocks, annual accumulation, and potential C-trading benefits
due to SSMP.
Scenario
Baseline
Low scenario
High scenario
Average
increase
Avg.
SOC,
%
1.44
2.72
4.19
1.83
Bulk density,
g cm-3
C density,
t ha-1
SOC stock*,
million t
1.43
1.18
1.18
1.18
30.9
41.4
74.2
57.8
1.9
2.7
4.6
3.65
C-trade
value,
millions $
2.0§
13.5†
6.6‡
*Extrapolated across total area of agricultural land (67,000 ha) in 15 SSMP districts of midhills Nepal.
§C-trade valued at US$ 2.50 t-1; †C-trade at US$ 5.00 t-1; ‡C-trade at US$ 3.75 t-1 of carbon
accumulated.
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24-25 March 2015
Low C accumulation scenario
3.50
3.00
y = 0.2975x + 0.7708
R2 = 0.8414
SOC%
2.50
2.00
1.50
1.00
0.50
0.00
0
1
2
3
4
5
6
7
6
7
Years
High C accumulation scenario
7.00
6.00
y = 0.4592x + 1.279
R2 = 0.4852
SOC %
5.00
4.00
3.00
2.00
1.00
0.00
0
1
2
3
4
5
Years
Figure 1.
Soil organic carbon increase for low and high carbon accumulation
scenarios compared to baseline SOC contents over a 6-year period.
Land management impacts on SOC and soil quality
As shown in Figures 2 and 3, land use type had an effect on the total SOC contents,
soil pH and total nitrogen. The one-way analysis of variance (Table 3) indicated,
however, that soil bulk density did not differ according to land use and that SOC
differed significantly only in Gorkha district, total N differed significantly only in
Chitwan, while soil pH was significantly different among land uses in Chitwan and
Gorkha. For Rasuwa district all soil quality parameters did not differ significantly
among the land use types. The SOC contents and total N were highest for all land uses
in Rasuwa district owing to the cool climate located at elevations of 1700 to 1800 m
asl. Under these conditions, the soil organic matter decomposition rates are slow and a
net accumulation of SOM tends to occur. Moreover, it was noted that farmers relied
more on organic manures and compost in Rasuwa compared to Chitwan and Gorkha
where chemical fertilizers are more readily available. The soils were more acidic in
Rasuwa compared to Chitwan or Gorkha, which likely reflects the nature of the
geology and rocks/parent material from which the soil was derived. Contrary to
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24-25 March 2015
expectations, however, in both Chitwan and Gorkha, soil pH was higher in agricultural
soils compared to community or leasehold forests. This may be due to the use of
agricultural lime by farmers to ameliorate soil acidity (Atreya et al. 2008, Bajracharya
and Sherchan 2009).
4
SOC %; BD (Mg m-3)
3.5
3
2.5
2
Chitwan
1.5
Gorkha
1
Rasuwa
0.5
0
CF
LHF
AG
CF
Soil Organic Carbon
LHF
AG
Bulk Density
Land Use
Figure 2:Soil organic carbon contents and bulk densities under different land uses (CF
= community forest, LHF = Leasehold forest, and AG = agriculture) at the
three study districts.
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24-25 March 2015
Soil pH; Total N (g kg-1)
8
7
6
5
4
3
Chitwan
2
Gorkha
Rasuwa
1
0
CF
LHF
AG
CF
Soil pH
LHF
AG
Total Nitrogen
Land Use
Figure 3: Soil pH and total nitrogen under different land uses (CF = community forest,
LHF =Leasehold forest, and AG = agriculture) at the three study districts.
Table 3:One-way ANOVA of soil properties by land use for each location
(Agroecological Zone).
Soil Property
Chitwan
F-test value
Signif.
Gorkha
F-test value
Signif.
Rasuwa
F-test value
Signif.
SOC %
0.89
ns
12.92
***
1.66
ns
Bulk density
1.32
ns
0.81
ns
0.01
ns
Soil pH
11.86
***
6.85
**
2.41
ns
Total N
4.12
*
0.24
ns
0.72
ns
C-Stock
0.59
ns
15.28
***
1.63
ns
Note: *, **, *** indicate significance at 0.05, 0.01 and 0.001 level of P, respectively.
As expected, the total carbon stock in soils of the three study districts were highly
correlated with the SOC content of the soils as shown in Table 4. Soil organic carbon
content was also highly correlated with total nitrogen and negatively correlated with
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24-25 March 2015
soil pH. Similarly, soil carbon stock was positively correlated with total nitrogen and
negatively correlated with soil pH (Table 4). Bulk density plays a crucial role in total
soil C stocks as higher density leads to greater total carbon amounts per unit volume of
soil. Thus, soil of relatively low SOC content may have significant total C stocks
when considering the entire soil profile to depths of 1 m as reported by other workers
(Bajracharya et al. 2004, Shrestha et al. 2004).
Table 4: Pearson’s correlation matrix for soil properties across land uses and locations.
Soil property
BD
C-stock
pH
TN
SOC
-0.77
0.96***
-0.39**
0.75***
BD
0.16
0.24*
0.05
C-stock
-0.34**
0.77***
pH
-0.14
TN
1
*, **, *** indicate significance at the 5%, 1%, 0.1% levels of probability, respectively.
Calculation of the total carbon stocks under each land use in each of the three study
districts (Figure 4) revealed that, expectantly, community forests had the highest total
C stock due to the presence of trees, resulting in a high above-ground biomass carbon
(AGB-C). However, it should be noted that the below-ground (root) biomass and soil
organic carbon components were also high and contributed significantly to the total C
stocks in forests. Moreover, with the exception of Gorkha, leasehold agroforests
(LHAF) also had comparatively high total carbon stocks. In agricultural land use, it is
only the soil OC that contributed to the total C stocks as above ground biomass (crops)
are harvested annually and cannot be counted in the total carbon stock. Hence,
leasehold or agroforestry systems offer potentially sustainable options for meeting the
production and income needs of farm households while simultaneously contributing to
sequester carbon. Forest type, tree density, age and climatic factors all affect the total
AGB-C as pointed out by numerous researchers (Ranabhat et al. 2000, Shrestha and
Singh 2008, Bhattarai et al. 2012).
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24-25 March 2015
Chitwan Site
200
SOC
150
LHG-C
100
BGB-C
AGB-C
50
0
CF
LHAF
AG
Land Use Category
Gorkha Site
400
350
C stock (t ha-1)
C stock (t ha-1)
250
300
250
SOC
LHG-C
BGB-C
AGB-C
200
150
100
50
0
CF
LHAF
Land Use Category
121
AG
24-25 March 2015
Rasuwa Site
600
C stock (t ha-1)
500
400
SOC
LHG-C
BGB-C
AGB-C
300
200
100
0
CF
LHAF
AG
Land Use Category
Figure 4: Total carbon stocks in biomass and soil for different land uses in the three
study districts. Note: CF = community forest, LHF = Leasehold forest, and
AG = agriculture; SOC = soil organic carbon, LHG-C = leaf-litter, herbs
and grasses carbon, BGB-C = below ground (root) biomass carbon, and
AGB-C = above ground biomass (tree) carbon.
Effect of biochar amendment on growth of coffee and vegetables
Biochar applied to the soil in nursery trials at Panchkhal produced a mixed response in
the growth of coffee seedlings as seen in Table 5. Compared to the control treatment,
which received only vermi-compost according to the usual farmer practice, the mixed
(weed/grass) biochar gave the best response as seen in overall plant height and growth
rate (Table 5 and Figure 5). The higher application rate of 4 t ha-1 (20% of FYM) gave
the better responses for both mixed and coffee pulp biochar. Other combinations and
lower rate (2 t ha-1) of biochar application including cattle urine application did not
have improved growth over the control treatment.
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24-25 March 2015
Table 5:Mean height of coffee plants in the coffee nursery trial at Panchkhal, Kavre.
Days after planting
Treatment
73
91
122
139
172
201
245
Control
2.1
2.7
6
7.7
9.9
13.3
14.1
MB-20
2.4
2.9
6.3
8.4
10.6
13.3
15
CB-20
2.6
3.1
6.1
7.8
10.6
11.9
14.6
3
3
5.6
7.4
9.1
12
14.2
Control
2.3
3.3
5.6
7
9.6
11.5
13.9
CB-10+U
2.8
3.6
6.3
8.6
10
12
13.6
CB-20+U
2.5
3.2
6
8
9.9
11.6
11.9
MB-20+U
16
Platn Height (cm)
14
12
10
Control
MB-20
8
CB-20
6
MB-20+U
4
2
0
50
100
150
200
250
300
Days After Planting
Figure 5:Coffee plant growth following emergence at about 70 days after planting at
the Panchkhal nursery trial.
In a separate field plot trial at Saraswatikhel, Bhaktapur, the growth rate of coffee
plants with mixed grass/weed biochar applied at a rate of 4 t ha-1 also exhibited a
higher growth rate (Table 6). Although the overall mean height of coffee plants was
higher for non-biochar plants, the increase in height was more for the biochar applied
plants at 5.4 cm over a 30 day period compared to 4.8 cm increase for non-biochar
plants. The higher overall plant height in the latter was due to the transplanting of
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24-25 March 2015
older and taller coffee plants in the non-biochar treatment as compared to the biochar
treatment.
As with the coffee plants, radish planted in rows between the coffee trees showed a
positive response to biochar application, as shown in Table 7. Radish plants that
received biochar application (at a rate of 4 t ha-1) grew to an average height of nearly
24 cm compared to non-biochar plants, which only reached an average of about 19 cm.
This difference in height was statistically significant at the 5% level of probability.
Thus, biochar application appears to have potential to improve crop performance and
yields as reported by other workers (IBI 2012, Sohi 2012). The application of
biofertilizers and other organic amendments have been shown to improve soil quality
while eN hancing productive capacity of soils (Sherchan and Karki 2006, Bajracharya
and Sherchan 2009). Furthermore, diversified cropping systems such as agroforestry
and inter-cropping have been noted to be effective for soil quality maintenance and
sustainable production (Sharma and Sharma 2004, Dahal et al. 2008).
Table 6:Coffee plant growth during a thirty day period for biochar applied and nonbiochar treatments at Saraswatikhel, Bhaktapur.
Treatment*
Plant Growth, cm
Height (11/10/14)
Height (10/12/14)
Ht. Increase
(30-day), cm
w/ biochar
Std. Dev.
No biochar
Std. Dev.
36.8
2.2
49.5
8.6
42.2
1.9
54.3
9.7
5.4
1.2
4.8
4.7
-1
*Biochar applied in two doses of 2 t ha for a total of 4 t ha-1
Table 7: Growth rate of radish plants in rows between the coffee agroforestry plots at
Saraswatikhel, Bhaktapur during October to December 2014.
Plant No
Biochar, cm
Non-Biochar, cm
1
2
3
4
5
6
7
8
9
10
Mean*
Std. Dev.
24
27
32
18
23
30
18
28
23
17
23.9
5.4
15
25
17
24
20
18
15
20
20
15
19.1
3.7
*Means statistically significantly different at P < 0.05.
Apart from plant growth rates, biochar influenced the emissions of greenhouse gases
from the agroforestry trial plots at Saraswatikhel, Bhaktapur. The flux of GHGs
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24-25 March 2015
measured at weekly intervals during April and May 2014 showed a general trend of
lower emissions for the biochar applied treatment (Table 8). Although the values were
not statistically significantly different for carbon dioxide and methane, nitrous oxide
flux exhibited significantly (P < 0.05) lower values in the biochar amended soil as
compared to soil without biochar. This finding is especially relevant for agricultural
soils which are the main source of N2O emission to the atmosphere, particularly with
the application of chemical nitrogen fertilizers. Crop types and tree species have been
reported to influence GHG flux in soils among other soil and climatic factors (Raut et
al. 2012, Ramesh et al. 2013).
Table 8: Fluxes of greenhouse gases (µg CO2 m-2 h-1) from biochar applied and nonbiochar plots at Saraswatikhel, Bhaktapur.
GHG
CO2
N2O
CH4
Treatment
Min.
Max.
Mean
biochar
10.5
432
225.4
non-biochar
40.8
589
298.5
biochar
5.12
370
89.0
non-biochar
6.30
523
157.2
biochar
1.58
22.9
12.1
non-biochar
0.86
39.8
16.0
Signif.
ns
P<0.05
ns
Conclusion
The findings of the above studies may be summarized as follows. Sustainable soil
management practices can lead to significant C accumulations (4-8 t ha-1 over 6 yrs) in
mid-hill districts of Nepal. The SOC contents and soil C stocks tend to increase with
elevation due to the cooler climate and slow rates of organic matter decomposition.
The total carbon stocks for three land use types, namely, community forest,
leasehold/agroforestry, and agriculture followed the trend: CF>LH/AF>AG. However,
agroforestry practices also had high total carbon stocks comparable to community
forestry, making them a potentially suitable option for eN hanced livelihoods of rural
communities while helping to sequester carbon in the hill regions of Nepal. Similar
findings have been reported by other workers in Nepal and the region (Pandit et al.
2012 and 2014, Ramesh et al. 2013).
Application of biochar to soil at low rates (2-4 t ha-1) increased growth of both coffee
plants and radish. Mixed grass/weed biochar gave the best results for coffee seedlings
grown on nursery beds. Application of diluted cattle urine did not have a notable effect
on coffee seedlings. Biochar amended soil generally had reduced emission of GHGs.
This reduction was significantly lower for N2O flux. Hence, agroforestry systems in
combination withbiochar application to soils, offers a potentially viable option for
sustainably eN hancing agricultural production, while also helping to mitigate
greenhouse gas emissions and climate change. This conclusion, however, needs
further research and verification.
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24-25 March 2015
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MVK Sivakumar, SMA Faiz, AHM Mustafizur Rahman, KR Islam (eds.)
Climate change and Food Security in South Asia. Springer. Pp 137-152.
Linquist BA, V Phengsouvanna and P Sengxue. 2007. Benefits of organic residues and
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Pandit BH, RP Neupane, BK. Sitaula and RM. Bajracharya. 2012. Contribution of
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Nepal: An overview. Small-scale Forestry, DOI 10.1007/s11842-012-9224-0
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Pandit BH, KK Shrestha and SS Bhattarai. 2014. Sustainable local livelihoods through
enhancing agroforestry systems in Nepal. J. of Forest and Liveliood.12 (1):4763.
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Ramesh T, KM Manjaiah, JMS Tomar and SV Ngachan. 2013. Effect of multipurpose
tree species on soil fertility and CO2 efflux under hilly ecosystems of
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SF-10
Studies on Sustainable Soil Fertility Management on Rapeseed
Rajan Malla1, Shankar Shrestha2, Himal P Timalsina1, Bahuri P Chaudhary1 and Om N
Chaudhary1
1
Oil Seeds Research Programme (NARC), Nawalpur, Sarlahi.
2
Sugarcane Research Programme, NARC, Jitpur, Bara
Abstract
An experiment was conducted at Oilseed Research Program, Nawalpur Sarlahi during
2007-08. It comprised of three activities. It was laid out in RCB design with various
treatments and various replications. Preeti variety of tori was used in the experiments. In
activity titled integrated nutrient management practice for sustainable toria seed yield,
seeded on Kartk 3, data on siliqua per plant, seeds per siliqua and seed yield were
statistically significant. The maximum 185 siliqua per plant was recorded by the treatment
in which recommended dose of N, P2O5 and K20 (100%) + Boron (1kg ha-1) were applied.
Similarly the maximum 13.6 and 13 seed per siliquae were recorded in which
recommended dose of N, P2O5 and K20 (100%) + Sulphur (30 kg ha-1) and N, P2O5 and
K20 (100%) + Boron (1kg ha-1) were applied respectively. Results on seed yield revealed
that maximum 1313 kg seed per ha was recorded when recommended N, P2O5 and K20
(100%) + Sulphur (30 kg ha-1) were applied followed by N, P2O5 and K20 (50%) + FYM
@ 10 t ha-1 + Sulphur (30 kg ha-1) + Boron (1kg ha-1) which yielded 1247 kg ha-1. In
second activity titled liming of acidic soil for improving soil reaction and contribution in
toria seed yield, seeded on Kartik 10, fertilizer was applied @60:40:20 kg ha-1 of N, P2O5
and K20 in all the treatments. Data on siliqua per plant, seeds per siliqua, 1000 seed mass
and seed yield were statistically significant. The maximum 148 siliquae per plant was
produced by the treatment in which 2 tons agri-lime was applied. Also the same treatment
recorded maximum 12.3 seeds /siliqua. Similarly, the same treatment obtained maximum
1000 seed weight of 3.01 gm. The result revealed the highest seed yield of 918 kg ha-1 was
recorded when applied lime @2.0 t ha-1 followed by lime @2.5 t ha-1 (778 kg ha-1). Again
in third activity response of toria to different levels of nitrogen and sulphur, seeded on
Kartik 3 was studied with an objective to see the effect of nitrogen (N) and sulphur (S)
levels on plant height, secondary branches per plant, siliqua per plant, seeds per siliqua
and 1000 seed weight were found statistically non-significant. However the effect of
nitrogen level on primary branches per plant was significant. The maximum 3.8 primary
branches per plant was recorded when 90 kg ha-1 N was applied. The data on seed yield for
N level was found non-significant. However the effect of sulphur was found significant.
The maximum seed yield of 837 seed kg ha-1was recorded when 90 kg ha-1 N and 45 kg
ha-1 S were applied followed by N 30 kg ha-1 and S 45 kg ha-1 (760 kg ha-1).
Keywords: Acidic soil, integrated nutrient management, liming, rapeseed yield.
Introduction
Oilseed crop plays a crucial role in Nepalese economy. It has high domestic demand as
well as export potential. Oilseed crops, Rapeseed(Brassica campestrisvartoria L.),
Rayo (Brassica juncea), and Sarson (Brassica campestrisvar yellow sarson) are the
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24-25 March 2015
most important edible oil producing crops of the country. The production of rapeseed
and mustard seeds meet the major requirements of oil being consuming. RapeseedMustard is the dominant oilseed crop of Nepal. It is mainly grown as rainfed with
limited use of fertilizer. Yield of Rapeseed-Mustard has declined in past few years. The
reasonsforlowrapeseed-mustardyieldaretheuseof low yield potential varieties, poor soil
fertility and nutrientmanagementpractices.Among the agronomic factors, nutrient
stands first and is one of the most important inputs in agriculture for increasing
productivity which must be addressed sooner than later.
With increase in intensive cropping system in agriculture with high yielding varieties,
soils are becoming depleted in nutrients. Indiscriminate use of the chemical fertilizer
for the supply of major nutrients and limited use of other nutrients and organic sources
of input over time have led to deficiency in soil and plants. Farmers rarely recycle the
plant residues tothefield and help build up soil organic matter. Besides, only a handful
of farmers seem to be aware of increasing soil acidity problem and take steps to
address them. Particularly micro-nutrients like Boron and Zinc are emerging as one of
the major constraints for sustainable production in rainfed areas. There is a need for
efficient consumption of chemical fertilizers and increase use oforganic manure, crop
residuesincorporation andbio-fertilizers application (De and Sinha2011).On the other
hand, continuous use of organics manure helps to build up soil humus and increase
beneficial microbes besides improvingsoilphysio-chemical properties. Therefore,a
substitutionand/orsupplementationofmajornutrients
withaconsiderableproportionfromorganicmanures for sustaining higher yield, is of
urgent need (De et al.2009).
To study on sustainable soil fertility management on Rapeseed production, the
following three activities were carried out by Oilseed Research Program, Nawalpur,
Sarlahi during 2007-08.
• Integrated Nutrient Management practice for sustainable rapeseed seed yield.
• Liming of acidic soil for improving soil reaction and contribution in
rapeseedgrainyield.
• Response on rapeseed yield and yield attributing parameters to different levels
of Nitrogen and Sulphur.
The research was carried out Oilseed Research Program, NawalpurSarlahi during
2007-08. The farm is situated at 26° 19' 86" N latitude and 89°23'53"E longitude and at
an altitude of 143meters above the meansealevel. The soil type was Sandy loam. The
experimental details of three activities are shown below.
SN
Design
Treatment
Replication
Plot Size
RR*PP
Variety
Activity 1
RCB
10
3
4m*3m
30 cm*cont.
Preeti
Activity 2
RCB
5
5
4m*3.6m
30 cm*cont.
Preeti
Activity 3
RCB
12
3
5m*2.4m
30 cm*cont.
Preeti
129
24-25 March 2015
Integrated Nutrient Management practice for sustainable rapeseed seed yield
In order to evaluate the rapeseed seed yield under different nutrient management
practice, 10 treatments were set up comprising a combination of 50% and 100% of
recommended doses @60:40:20 N:P2O5:K2O kg ha-1with FYM @10 t ha-1, Boron
@1kgha-1 and Sulphur @30 kg ha-1.Trial was seeded in Kartik 3, 2064 and harvested
on Magh 3, 2064. Other cultural practices were done as required.
Liming of acidic soil for improving soil reaction and contribution in rapeseed seed
yield
It comprised of 5 treatments, RDF with different levels @ 0, 1.5, 2.0, 2.5 and 3.0
ton/ha of agri-lime. Trial was seeded at Kartik 10, 2064 and harvested on Magh 5,
2064. Fertilizer was applied @ 60:40:20 N:P2O5:K2O kg ha-1 in all the treatments.Other
cultural practices were done as required.
Response on rapeseed yield and yield attributing parameters to different levels of
Nitrogen and Sulphur
It comprised of 3 levels of Nitrogen (30, 60 and 90 kg N ha-1) and 4 levels of Sulphur
(0, 15, 30 and 45 kg ha-1 treatments. Trial was seeded at Kartik 3, 2064 and harvested
on Magh 2, 2064. Preeti variety of tori was used in the experiment. Other cultural
practices were done as required.
All the recorded data were subjected to analysis of variance and Duncan’s Multiple
Range Test (DMRT) for mean separations using MSTAT-C. ANOVA was done at 5%
significance level.
Results and Discussions
Integrated nutrient management vs. yield components
The data on siliqua per plant, seeds per siliqua and seed yield were statistically
significant (Table 1). The maximum siliqua per plant (185) was recorded on the
treatment recommended dose of NPK (100%) + Sulphur (30 kg ha-1) applied. Similarly
the maximum 13.8 seed per siliquawere recorded for treatment with NPK (50%) +
FYM @ 10 t ha-1 + Sulphur (30 kg ha-1) + Boron (1 kg ha-1) followed by 13.6 under
recommended dose of NPK (100%) + Sulphur (30 kg ha-1). Results on seed yield
showed that maximum 1313 kg ha-1 on recommended NPK (100%) + Sulphur
(30 kg ha-1) applied followed by NPK (50%) + FYM @ 10 t ha-1 + Sulphur
(30 kg ha-1) + Boron (1kg ha-1) which yielded 1247 kg ha-1.
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24-25 March 2015
Table 1: Effect of nutrient management on agronomic and yield parameters of
rapeseedduring 2007-08, ORP, Nawalpur.
TN
1
2
Plant
Height
, cm
77.6
Name of Treatments
Control (0:0:0 NPK kg ha-1)
100%
NPK
(60:40:20
N:P2O5:K2Oha-1)
kg
Sec.br/p
lant-1
2.9
4
Siliqua/
plant
Nos.
90
11.8
1000
SW,
gm
3.5
86
3
4.2
105
11.3
3.2
806
985
Seeds/
siliqua
Seed
Yield,kg
733
87
3
4.3
140
12.6
3.4
85.3
3
4
135
13
3.2
838
82
3
4.4
185
13.6
3.3
1313
100% NPK + Boron + Sulphur
87.3
3.4
4.2
165
12.6
3.8
1242
50% NPK + FYM (10 t ha-1)
89.6
2.6
3.9
140
12.5
2.8
866
88
3.2
4.6
155
12.1
3.1
965
92.6
2.6
4.4
165
10.8
3
958
93.3
3.5
4.6
175
13.8
3.7
1247
-1
3
100% NPK + FYM (10 t ha )
4
100% NPK + Boron (1.0 kg ha-1)
5
100% NPK + Sulphur (30 kg ha-1)
6
7
8
50% NPK + FYM + Boron
9
50% NPK + FYM + Sulphur
50% NPK + FYM + Boron +
Sulphur
10
Pr.br.
plant-1
F-test
ns
ns
ns
*
*
ns
*
CV,%
10.7
14.3
25.8
17.1
10.6
14.6
19
The different nutrient management combinations showed increase in seed yield over
absolute control. As though the highest seed yield was seen in 100% NPK + 30 kg ha-1
of Sulphur, it would not be wise choice of sustainable production. The treatment with
50% NPK + FYM + Boron + Sulphur which was just as high yielding and with the
highest value for seeds/ siliqua and second highest for siliqua/plant is the best option
due to its mix of organic, inorganic and presence of micronutrients.
Liming vs. yield components
Liming the field @2.0 t ha-1 with agri-lime resulted in the highest seed yield of 918 kg
ha-1, 27.1% more compared to that of the control plot, followed by lime @2.5 t
ha-1 which yielded 778 kg ha-1. The yield attributes and seed yield increased with
increase in amount of lime but tended to decline above the rate of 2.0 t ha-1 in
Nawalpur, Sarlahi conditions. This amount of liming was most relevant and
economical to bring the soil to the optimum pH, thus giving higher yields in Nawalpur,
Sarlahi.
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24-25 March 2015
Table 2: Effect of lime on yield and yield attributing characters of rapeseed during
2007-08, ORP, Nawalpur.
T
N
Plant
Height,
cm
Name of Treatments
Control
Pr.br.
plant-1
Sec.br/
plant-1
Siliqua/
plant
Nos.
Seeds/
siliqua
1000
SW,
gm
Seed
Yield,k
g
1
RDF
lime)
(no
68.4
3.1
4.2
110.6
10.9
2.64
722
2
RDF + 1.5 lime t ha-1
70.6
2.9
4.6
125
11.4
2.74
776
3
RDF + 2.0 lime t ha-1
71.2
3
4.6
148.2
12.3
3.01
918
62
2.7
4.4
130.8
11.6
2.81
778
-1
4
RDF + 2.5 limet ha
-1
5
RDF + 3.0 lime t ha
68.2
3.2
4.8
115.6
11.4
2.88
734
F-test
ns
ns
ns
*
*
*
*
CV, %
11.2
22.1
16
12.4
11.2
10.5
13.9
LSD 0.05
-
-
-
12.1
0.2
0.1
91
Seed yield/ cost
25
yield (qt/ha)
cost ('000)
20
15
10
5
0
RDF Control RDF + 1.5 t RDF + 2.0 t RDF + 2.5 t RDF + 3.0 t
(no lime)
lime/ha
lime/ha
lime/ha
lime/ha
Figure1: Seed yield of rapeseedon various doses of lime and their incurred costs,
2007-08, Nawalpur.
Nitrogen and Sulphur vs. yield parameters
The effect of N level was found non-significant on seed yield, however the highest
seed yield was when Nitrogen was applied @ 90 kg ha-1. Researchers have found
Nitrogen to increase yield upto 120 kg ha-1 level of application (Rashid et al. 2007).
The effect of Sulphur was found significant only for the seed yield. The maximum seed
yield of 837 seed kg ha-1 was recorded when 90 kg ha-1 N and 45 kg ha-1 S were
applied. Khan et al. (2002) found similar results, where he found pods plant-1 and seed
yield to be significant but the seeds pod-1 and 1000 SW were not significant,
meanwhile yielding significantly higher for the highest doses of both nitrogen and
sulphur.
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24-25 March 2015
Table 3: Effect of nitrogen and sulphur application on agronomic and yield
parameters of rapeseed during 2007-08, ORP, Nawalpur.
Level of
Pr.br.
plant-1
Sec.br
plant-1
Siliqua
plant-1
nos.
Seeds/
siliqua
1000
SW, g
Seed
yield,kg
Pr.br.
plant-1
TN
Nitrogen
Sulphur
1
30 kg/ha
0 kg/ha
63.3
3.06
4.4
41
12.1
1.67
474
2
30 kg/ha
15 kg/ha
69.6
2.8
5.7
39.3
13.4
1.86
577
3
30 kg/ha
30 kg/ha
64.3
2.7
5.2
42.6
12.2
1.51
565
4
30 kg/ha
45 kg/ha
71
3.2
4.5
54.6
12.8
1.92
760
5
60 kg/ha
0 kg/ha
70
3.2
4.9
48
11.2
1.58
680
6
60 kg/ha
15 kg/ha
69
3.1
4.2
41
10.4
1.54
605
7
60 kg/ha
30 kg/ha
70
3.6
5.8
49
12.4
1.58
530
8
60 kg/ha
45 kg/ha
67.7
3.3
5.2
51.6
13.1
1.73
747
9
90 kg/ha
0 kg/ha
69
3.8
6.1
47.6
13
1.51
470
10
90 kg/ha
15 kg/ha
76
3.3
4.8
52.6
12.3
1.67
620
11
90 kg/ha
30 kg/ha
75
3.4
4.2
43
13.6
1.74
743
12
90 kg/ha
45 kg/ha
74.3
3.6
6.5
57.6
13.7
1.5
837
CV,%
13.7
16.9
33.8
27.8
11.5
12.3
28
F-test Nitrogen A
ns
*
ns
ns
ns
ns
ns
F-test Sulphur B
ns
ns
ns
ns
ns
ns
*
LSD 0.05
ns
ns
ns
ns
ns
ns
ns
Conclusion
The problem of low yield in Rapeseed is mainly associated with decline in soil fertility.
The judicious use of nutrients along with plenty of organic sources, with emphasis on
Sulphur and Boron for rapeseed is seen vital. The incorporation of farm yard manure is
equally important. The soil acidity problem is increasing in trend, which needs
attention and awareness to be raised among the farmers. Building the soil organic
matter is the only way for a sustainable production.
Acknowledgement
The work is supported and funded by Nepal Agricultural Research Council. Oilseed
Research program, Nawalpur, Sarlahi.
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24-25 March 2015
References
Rashid R, F Karim and M Hasanuzzman. 2007, IDOSI Publications.Middle-East J. of
Scien. Research. 2 (3-4): 146-150.
De B and AC Sinha. 2011.Integrated Nutrient Management on Rapeseed (Yellow
sarson).Lambert Academic Publisher, Germany.
De B, AC Sinha and PS Patra. 2009.Effect of organic and inorganic sources of
nutrients on rapeseed (Brassica campestrisL.) under terai region. J. Crop Weed.
5: 281-84
Khan N, J Amanullah, Ihsanullah, IA Khan and N Khan. 2002. Asian J. of Plant
Sci.1(5): 516-518
134
24-25 March 2015
SF-11
Study on Soil Fertility Status of Vegetable Growing Pocket Areas of
Dhading District, Nepal
Binita Thapa, Dinesh Khadka and Shree P Vista
Soil Science Division (NARC), Khumaltar, Lalitpur
Abstract
A study was conducted for assessing nutrient status of vegetable growing area in Naubise,
Jeevanpur and Kebalpur VDCs of Dhading district. These sites are pocket areas popularly
for the vegetable production. A total of 36, 20 and 26 soil samples were collected from
farmers’’ field at 0-20 cm depth by using soil sampling auger from Naubise, Jeevanpur
and Kebalpur, respectively. Laboratory analysis for the determination of soil pH, OM, N,
P2O5 and K2O was done following standard method in the laboratory of Soil Science
Division, Khumaltar. The soil test data revealed that mean soil pH (5.95±0.061) of
Naubise site was slightly acidic, low in organic matter (OM) (2.45±0.15%), medium in
total nitrogen (0.11±0.004%), very high in phosphorus (372.6±43.26 kg ha-1) and medium
in potassium (245.3±59.3 kg ha-1). Correspondingly, the mean soil pH (5.07±0.117) of
Jeevanpur site was very acidic, low in organic matter (1.82±0.094%), low in total nitrogen
(0.09±0.003%), very high in phosphorus (165.95±35.97 kg ha-1) and low potassium
(55.1±13.13 kg ha-1). Similarly, at Kebalpur site soil pH (5.77±0.171) was moderately
acidic, low in organic matter (1.89±0.207%), low in total nitrogen (0.09±0.006%), very
high in phosphorus (353.1±53.54 kg ha-1) and low in potassium (133.7±37.1 kg ha-1).The
soil at these site should be maintained properly through application of organic and
inorganic sources of nutrients to make vegetable farming sustainable. In additions, the soil
; therefore, application of agricultural lime
reaction of Jeevanpur site was found very
practices to
is recommended to manage soil while n the other sites proper manage
in
maintain soil reaction is recommended for sustaining vegetable production. OM
recommended to add OM
for
all three sites is low is
sustaining profitable production.
Keywords:
vegetable
growing area.
Introduction
Soil fertility is the inherent capacity of the soil to supply nutrients to plants in adequate
amounts and in sustainable proportions. Soil fertility is a prerequisite to its
productivity. It is the capacity of soil to produce crops of economic value and to
maintain health of the soil without deterioration.
Dhading is a nearby district of the Kathmandu valley; especially Naubise, Jeevanpur
and Kebalpur very popular site for the vegetable production. The testing of soil and
recommendation based on the result to maintain soil health is a necessity in such
vegetable growing area.
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24-25 March 2015
Therefore, considering this factor soil science division started to work in the vegetable
growing especially nearby side of the Kathmandu valley especially for the soil health
diagnosis and improvement through the soil and plant testing.
The different materials and method used for an assessment of nutrient status are
described under the following headings:
Collection of soil and plant samples
The soil samples were collected from the vegetable farming area of the Dhading district
namely Naubise (Kanakot), Jeevanpur (Kumaikhola) and Kewalpur (Dharke). The soil
samples were collected from the 0-20 cm depth.
Figure 1: Research sites of plant samples diagnosis.
Analysis of soil samples
The pH (1:2), Soil organic matter (Walkely 1934), total nitrogen (Bremner and
Mulvaney 1982), available phosphorus (Olsen et al. 1954) and extractable potassium
(Jackson 1967) content in the collected samples were determined by standard method
in the Soil Science Division.
Soil Fertility Status of the Naubise (Kanakot)
The soil fertility status of the vegetable growing area of the Naubise (Kanakot) of
Dhading district is shown on the Table 1.
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24-25 March 2015
Table 1: Soil Fertility Status of the Naubise (Kanakot).
S.N. Particular
pH
OM,%
TN,%
Av. P2O5,
kg ha-1
1.
Mean
5.95
2.45
0.11
372.6
Ext.
K2O,
kg ha-1
245.3
2.
Standard Error
0.061
0.153
0.004
43.26
59.3
3.
0.375
0.921
0.025
259.57
355.5
4.
Standard
Deviation
Range
5.1-6.8
0.56-4.46
0.06-0.17
53-1206
7-1769
5.
Count
36
36
36
36
36
Soil pH
The mean pH of the tested samples of this site was 5.95. The maximum and minimum
observed pH of this site was 5.1 and 6.8, respectively. The majority (58.3%) were
slightly acidic while, remaining 33.3%, 5.6% and 2.8% of the analyzed samples were
moderately acidic, nearly neutral and very acidic, respectively.
Organic Matter (OM)
The mean OM of tested samples of this site was 2.45%. The maximum and minimum
observed OM of this site were 0.56% and 4.46%, respectively. In organic matter, 8.3%,
36.1% and 55.6 % of the analyzed samples were low, medium and high in the range,
respectively
Total Nitrogen
The mean nitrogen of the tested samples of this site was 0.11%. The maximum and
minimum observed nitrogen of this site were 0.06% and 0.17%, respectively. Total
nitrogen, among the tested samples 83.3% was low while, remaining was medium.
Low to medium range of nitrogen was observed on the tested samples of this site.
Available phosphorus
The mean phosphorus among the tested samples of this site was 372.6 kg ha-1. The
maximum and minimum observed phosphorus of this site were 53 and 1206 Kg ha-1,
respectively. In available phosphorus, 94.4% samples were very high whilst, remaining
equal (2.8%) samples were medium and high in status.
Extractable Potassium
The mean potassium of the tested samples of this site was 245.3 kg ha-1. The maximum
and minimum observed potassium of this site were 7 and 1769 Kg ha-1, respectively. In
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24-25 March 2015
extractable potassium 30.6%, 19.4%, 22.2% and 11.1% of the samples were very low,
low, medium and high in the category, respectively.
Soil Fertility Status of the Jeevanpur (Kumaikhola)
The soil fertility status of the vegetable growing area of the Jeevanpur (Kumaikhola) of
Table 2: Soil Fertility Status of the Jeevanpur (Kumaikhola).
S.N.
Particular
pH
1.
2.
3.
4.
5.
Mean
Standard Error
Standard Deviation
Range
Count
5.07
0.117
0.521
4.0-6.1
20
OM,%
1.82
0.094
0.421
0.98-2.8
20
TN,%
0.09
0.003
0.013
0.07-0.12
20
Av. P2O5,
kg ha-1
165.95
35.97
160.85
29-681
20
Ext.
K2O,
55.1
13.13
58.73
10-234
20
Soil pH
The mean soil pH content of the study area was 5.0. The maximum and minimum
value was 4.0 and 6.1, respectively. The 65%, 30% and 5% of the analyzed samples
were very acidic, moderately acidic and slightly alkaline in reaction, respectively. In
overall, high variation on soil reaction was also observed on this site.
Organic Matter (OM)
The mean OM among the tested samples was 1.82%. The maximum and minimum
value was 0.98% and 2.89%, respectively. In overall, majority (95%) are low while,
remaining 5% are very low in content.
Total Nitrogen
In total nitrogen, the mean content was 0.11%. The maximum and minimum content
was 0.06% and 0.17%, respectively. In overall, 70% of the analyzed samples were
medium while, remaining was medium in status.
In available phosphorus, the mean content was 165.95 kg ha-1. The maximum and
minimum amount was 29.0 and 681 kg ha-1, respectively. In overall, 45% and 35%
samples contains very high and high range, respectively; while, others samples each
contains equal (10%) low and very low status.
In extractable potassium, the mean content was 55.1 kg ha-1. The maximum and
minimum content was 10 and 234 kg ha-1, respectively. In overall, 65% of the analyzed
samples were very low, 20% was low and remaining 15% was medium in status.
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24-25 March 2015
Soil Fertility Status of the Kewalpur (Dharke)
The soil fertility status of the vegetable growing area of the Kebalpur (Dharke) of
Table 3: Soil Fertility Status of the Kewalpur (Dharke).
S.N. Particular
pH
OM,%
TN,%
1.
2.
3.
4.
5.
Mean
Standard Error
Standard
Deviation
Range
Count
Av. P2O5,
kg ha-1
Ext. K2O,
kg ha-1
5.77
0.171
0.874
1.89
0.207
1.056
0.09
0.006
0.031
353.1
53.54
273.0
133.7
37.1
189.176
4.4-7.03
26
0.2-4.46
26
0.04-0.17
26
20-877
26
11-940
26
Soil pH
The mean pH of the tested samples of this site was 5.77. The maximum and minimum
content of this site were 4.4 and 7.0, respectively. Among the tested samples, 38.5%,
19.2% and 5.4% were very acidic, moderately acidic and slightly acidic in reaction,
respectively while, others 19.2% and 7.7% samples were nearly neutral and slightly
alkaline, respectively.
Organic Matter
The mean OM of the tested samples of this site was 1.89 %. The maximum and
minimum observed OM of this site was 0.2% and 4.46%, respectively. In organic
matter, 23.1%, 57.7% and 19.2% samples were very low, low and medium in the
range, respectively.
Total Nitrogen
The mean nitrogen of the tested samples of this site was 0.09%. The maximum and
minimum observed nitrogen of this site was 0.04% and 0.17%, respectively. In total
nitrogen, very low, low and medium status was observed on the 3.8%, 53.8% and
42.3% of the total analyzed samples, respectively.
The mean phosphorus of the tested samples of this site was 353.1 kg ha-1. The
maximum and minimum observed phosphorus of this site were 20 and 877kg ha-1,
respectively. In available phosphorus, 80.8%, 15.4% and 3.8% of the total samples
were very high, high and low in the range, respectively.
Extractable potassium
The mean potassium of the tested samples of this site was 133.7 kg ha-1. The maximum
and minimum observed potassium of this site were 11 and 940 kg ha-1, respectively. In
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24-25 March 2015
extractable potassium, 34.6%, 26.9%, 19.2% and 11.5% of the tested samples were
very low, low, medium and high in the range, respectively.
Conclusion
In overall (based on the mean value) soil fertility condition for the vegetable growing is
satisfactory in the tested soil parameters in Naubise, Dhading. Similarly, Soil pH,
organic matter, nitrogen and potassium is below the optimum for the most of the
vegetable growing areas of Jeevanpur. In Kewalpur site, soil pH (slightly below),
organic matter, nitrogen and potassium is below the optimum for the most of the
vegetable growing.
Reference
Bremner JM and CS Mulvaney. 1982. Nitrogen total. In: Methods of soil analysis.
Agron. No. 9, Part 2: Chemical and microbiological properties, 2nd ed. AL
Page. (ed.). Am. Soc. Agron. Madison, WI, USA. Pp. 595 – 624.
Jackson ML. 1967. Soil chemical analysis. Prentice Hall of India Pvt. Ltd., New Delhi.
Olsen SR, CVCole, FS Watanabe and LA Dean. 1954. Estimation of available
phosphorus in soils by extraction with sodium bicarbonate. U. S. Dep. Agric.
Circ. 9, USA. 39.
Walkley A. 1934. A critical examination of a rapid method for determining organic
carbon in soils. Effect of variations in digestion conditions and inorganic soil
constituents. Soil Sci. 63:251-263.
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24-25 March 2015
SF-12
Effect of Different Sources of Organic and Inorganic Nutrients in Wheat
under Terai Condition
Sabina Devkota, Shova Shrestha and Shree P Vista
Soil Science Division (NARC), Khumaltar
Abstract
An experiment was conducted at RARS, Parwanipur in rice wheat cropping system for
two years from 2012 to 2013with nine treatments and four replication with an objective to
compare the effect of different sources of organic manure and high analysis chemical
fertilizer. Results of the combined analysis revealed that wheat yield and yield attributing
parameters such as plant height and panicle length differed significantly with the
treatments of the experiment. The highest grain yield (2599 kg ha-1) of wheat was obtained
from the plot treated with recommended dose of chemical fertilizer followed by combined
application of chemical fertilizer (half of the RDF) and poultry manure @ 10 t ha-1 (2435
kg ha-1). Parameters
no. of tillers and test weight w
non-significant.
Unexpected
obtained in combined application of vermicompost, FYM and
poultry manure.
Keywords: Chemical fertilizer farm yard manure (FYM), poultry manure and
vermicompost.
Introduction
The demand of organic manure is increasing day by day as the farmers are getting
more used to with the high yielding crops, but still there is lack of knowledge on soil
organic matter management. Rice and wheat are the major food crops of Nepal and the
yield of these crops can be improved using the organic manure. The crop yields
especially of rice and wheat crops are stagnant or declining for the last decade in
Nepal. The use of organic manures and composted organic materials along with
chemical fertilizers may be effective for further increasing crop yield. Organic manure
addition in the soil is major source to increase microbial activities which are necessary
to render less productive soil into highly productive soil due to their role in
mineralization and mobilization of applied manures and fertilizers. No soils can be set
fertile without microbial activities. Hence, improvement of soil fertility with organic
manure supplement is the aim of this study.
The experiment was carried out in RARS, Parwanipur with 9 different treatments and 4
replications in wheat variety Aditya. The field trial was laid out in Randomized
Complete Block Design. The details of treatments in the said experiments are
presented in Table-1. Wheat seed was seeded continuously in lines of 25 cm apart in
individual plot of 4 X 3 =12 m2. Half N and full amount of P and K were applied
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during last field preparation, just before seeding. Remaining half of N was top dressed
at about 30 days after seeding. Soil samples were collected from each plot before
seeding and after harvesting of wheat for laboratory analysis. The crop was monitored
regularly and raised with best possible management.
Table 1: Treatments composition applied in the field experiment.
SN
1
2
3
4
5
6
7
8
9
Treatmentscombination
Control
NPK (100:40:30 kg ha-1)
NPK (50:20:15 kg ha-1) + FYM 10 t ha-1
NPK (50:20:15 kg ha-1) + Poultry manure 10 t ha-1
NPK (50:20:15 kg ha-1) + Vermicompost 10 t ha-1
FYM 10 t ha-1
Vermicompost 10 t ha-1
Poultry manure 10 t ha-1
FYM 10 t ha-1+ Vermicompost 10 t ha-1+ Poultry manure 10 t ha-1
Results of the combined analysis of two years revealed that wheat yield and yield
attributing parameters such as plant height and panicle length differed significantly
with the treatments of the experiment (Table-2). The highest grain yield (2599 kg ha-1)
of wheat was obtained from the plot treated with recommended dose of chemical
fertilizer followed by combined application of chemical fertilizer (half of the RDF) and
poultry manure @ 10 t ha-1 (2435 kg ha-1). Parameters
no. of tillers and test
-1
weight w
non-significant. Application of FYM at 10 ton ha alone could not show
good results in terms of yield. However, application of vermicompost and poultry
manure along with FYM showed good response. Amongst the three organic sources of
nutrients, poultry manure was found better comparatively followed by vermicompost.
Unexpected
obtained in combined application of vermicompost, FYM and
poultry manure. Combination of organic sources of nutrients produced good grain yield
of wheat. This shows that even among the various sources of organic nutrients,
combined application showed synergistic effect on yield. Controlled treatment showed
least grain yield (959 kg ha-1) which shows that nutrients is required to get optimum
yield. Moreover, combined applications of different sources have shown response in
the present study.
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Table 2: Effect of various sources of nutrients on yield and yield attributing
parameters of wheat.
Treatments
1
2
3
4
Plantheight,
cm
65.50
86.23
83.93
87.83
Tillers
m-2, nos.
223.9
244.6
234.5
250.6
Panical length,
cm
6.475
8.775
8.050
8.813
Grain yield,
kg ha-1
959
2599
2113
2435
Test weight,
g
36.78
39.95
39.24
37.40
5
84.31
265.6
8.300
2333
32.23
6
7
8
9
G mean
Lsd
F- test
CV, %
75.90
75.30
78.60
85.75
80.37
5.067
<.001
6.3
206.9
227.4
257.0
220.9
236.8
56.99
0.528
24.1
7.200
7.375
8.075
8.475
7.949
0.6800
<.001
8.6
1254
1257
1796
2117
1875
392.5
<.001
20.9
37.56
39.29
36.94
40.19
37.73
5.190
0.101
13.8
Conclusion
Application of FYM at 10 ton ha-1 alone could not show good results in terms of yield.
However, application of vermicompost and poultry manure along with FYM showed
good response. Amongst the three organic sources of nutrients, poultry manure was
found better comparatively followed by vermicompost. Application of full dose of
chemical fertilizer produced higher yield followed by half dose of chemical fertilizer
and poultry manure. Combined application of nutrients was also observed to produce
good yield. Therefore, both organic and inorganic sources of nutrients should be
applied for increased wheat production.
Acknowledgement
Authors highly acknowledge the organizing committee of Second National Soil
Fertility Research Workshop for accepting this paper for poster presentation. We
would like to thank Regional Director of RARS, Parwanipur and other support staffs of
RARS. Support from Chief and other staffs of Soil Science Division for effective and
timely support in implementing diverse activities of the research is also due
acknowledged.
Reference: (Not cited in the text)
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SF-13
Sustainability of Long-term Soil Fertility Management in Rice Wheat
Cropping Pattern n Eastern Mid Hills of Nepal
Parashuram Bhantana1, Shree P Vista2 and Ram B Katuwal
1
Agricultural Research Station (NARC), Pakhribas, Dhankuta, Nepal
2
Soil Science Division (NARC), Khumaltar, Lalitpur, Nepal
Abstract
A long-term soil fertility trail on rice wheat crop rotation was studied in
Agricultural Research Station Pakhribas since 2054. There were seven different
treatments replicated four times. The treatments allocated were (a) full control (b)
full inorganic (c) full organic (d) 50% organic plus 50% inorganic (e) 50%
inorganic (f) 50% organic (f) 25% organic plus 25% inorganic. Data on plant
height, no. of tillers, no. of filled grain or unfilled grain per panicle, panicle
length, biomass, straw weight, grain yield etc. were recorded. Most of the
were not significant whereas few were significant. Five years data
(2067-2071)
that the highest rice yield was recorded in the year 2068,
whereas the highest wheat yield was recorded in the year 2069. There is decline in
the yield of rice and wheat after 2068 and 2069, respectively. Similarly the
highest yield for both crops was recorded in the treatment with application of 50%
organic plus 50% inorganic treatment. This treatment differed significantly from
the control.
Keywords: Inorganic fertilizer, long-term soil fertility, organic manure.
Introduction
Farming system in Nepal is an integrated farming system, whereas livestock, crop and
horticulture are judiciously mixed into each other. Resources from one enterprise are
utilized into other enterprise and so on. For the supply of organic nutrients farm yard
manure, compost, green manure, various oil cakes and waste products of animal origin
has been used. But now a days these materials are not available in sufficient quantity.
This is because of disintegration of the farming system. Also attempts have been made
towards incorporation of leguminous plant to enrich soil fertility (Swaminathan 1996).
And there is increasing use of chemical fertilizer along with organic.Thus to develop a
sustainability of farming system is pinpoint of this study.
Rice-Wheat cropping pattern is one of the predominant cropping patterns in Nepal.
Total area under rice wheat production is 0.6 M ha contributing 71% of total cereal
production (Timsina and Connor 2001). Rice is the first and wheat is the third most
important staple food crop in Nepal. However there is huge yield gap between potential
and actual yield (Timsina and Connor 2001). Such yield gap needs to be narrowed
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down. However rice yield of best fertilized treatments remain unchanged for 10-25
years (Ladha et al. 2000). There are two central issues on rice-wheat management. One
is due to diverse soil system and agronomy between rice and wheat crop. Development
of hard plough pan below the root zone which hampers wheat root proliferation and
penetration. And the other is declining soil organic matter (SOM). The real challenges
of the rice wheat cropping system are to develop high yielding cultivar
includingsustainable production system (Timsina and Connor 2001).
Knowledge transfer to the rural life is one of the major issues for the development.
New technology can be such that it can be adopted by the small, poor and illiterate
farmer. Do we have such technology? It is a question of discussion. Yes it is possible
for the transformation of rural life with zeal and devotion. Mainly extension agents are
responsible for the transfer of available technologies to the farmers. Moreover there are
global communication network for the transfer of appropriate technology. But what is
urgently needed is such a communication network at the service of the poor farmer in
our country. It is not only knowledge that is needed but an approach which will be able
to supply the right knowledge and tools to the right people at the right time and place
(Swaminathan 1996).
Sustainability is the key characteristics in the traditionally driven agriculture like
Nepal. Sustainability is a favorable interaction among social, economic and ecological
factors. But in this article more emphasis is given to ecological factors. The ability of
an agro-ecosystem to remain productive at a constant or increasing level without
degrading natural resource based upon which future productivity will depend is called
sustainable (Ellis and Wang 1997). This is how a study for the sustainability of long
term soil fertility management of rice wheat cropping pattern is taken into account.
The study location was situated at latitude 27°03’ N, longitude 87°17’ E and 1680 masl
elevation in the Eastern Development Region of Nepal. The rice variety Khumal-4 and
wheat variety WK-1204 were chosen for cultivation.
Table 1: Treatments details.
Treatment No.
T1
T2
T3
T4
T5
T6
T7
Symbols
a
b
c
d
e
f
g
Per cent nutrients
Inorganic = 0, Organic = 0
There were seven different treatments replicated four times in a plot size of 16 m2. The
treatments allocated were (a) full control (b) full inorganic (c) full organic (d)
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50%organic plus 50% inorganic (e) 50% inorganic (f) 50% organic (g) 25% organic
plus 25% inorganic.
Agronomic operation: Sowing of rice in a seedbed was done for rice crop. Agronomic
operation such as transplanting of rice was done on the 15th of Ashadh each year.
Harvesting of rice and data collection was done for rice crop in 8th of Mangsir every
year. Similarly sowing and harvesting of wheat was done on the Mangsir and Baisakh
every year.
Data recorded
Data recorded were plant height, no. of tillers, no. of filled grain or unfilled grain per
panicle, panicle length, biomass, straw weight, grain yield etc. Recorded data were
analyzed with astatistical software M-Stat.
Mean, ±standard deviation of rice biomass kg plot-1 is shown in the Figure 1. As seen
in the figure treatment with 50% inorganic and 50% organic showed the highest yield.
Whereas control treatment showed the least. The respectives values for rice biomas are
16.48 kg plot-1and 8.8 kg plot-1in the year 2067. Similarly the highest and the lowest
values for the rice biomass in the year 2068 was 17.2 kg plot-1 and 8.5 kg plot-1.
Moreover 13.18 and 6.2 , 14.24 and 7.5 kg plot-1, and 12.37 and 6.08 were recoded as
maximum and minimum values for the rice biomass in the year 2069, 2070 and 2071,
respectively. Among the five years data presented, in the year 2068 showed the best.
Similar pattern is observed for rice straw yield, rice grain yield as shown in the Figure
2 and 3, respectively.
2067
2068
2069
2070
25
20
15
Rice Biomass
(kg plot-1)
10
5
0
Treatments
Figure 1: Mean ±standard deviation of Rice biomass kg plot-1.
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2071
24-25 March 2015
2067
2068
2069
2070
2071
25
20
15
Straw
weight (kg
plot-1))
10
5
0
Treatments
Figure 2: Mean±standard deviation of Rice Straw weight kg plot-1.
2067
2068
2069
2070
2071
3.5
3
2.5
Rice Grain
2
yield kg
1.5
plot-1
1
0.5
0
Treatments
Figure 3: Mean±standard deviation of Rice Grain yield weight kg plot-1.
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Likewise, rice biomass, rice straw yield and rice grain yield, wheat biomass, wheat
straw yield and wheat grain yield are presented in the Figures 4, 5 and 6, respectively.
All of these three parameters recorded were significant over the control treatment.
Wheat biomass showed the highest in a treatment number (d) i.e. application of 50%
organic and 50% inorganic and the least in the treatment number (a) i.e. control. Also
other data such as wheat straw yield and wheat grain yield showed similar pattern. The
highest and lowest value of wheat biomass were 9.83 to 2.42 kg plot-1, respectively in
the year 2069. Similarly the highest and lowest values for wheat straw yield recorded
in the year 2069 were 5.21 and 1.06 kg plot-1, respectively. Also in the year 2069 the
highest and the lowest values for wheat grain yield were 2.74 to 0.615 kg plot-1,
respectively. The yield records of the rest of the year are presented in the Figures 4, 5
and 6, respectively.
Highest value among the five years data on wheat biomass, wheat straw yield and
wheat grain yield was in the year 2069. It is possibly due to climatic factors favorable
for the rice and wheat growing environments in the year 2068 and 2069 respectively.
2067
2068
2069
2070
2071
20
Wheat
Biomass kg
plot-1
15
10
5
0
Figure 4: Mean±Standard deviation of wheat biomass kg plot-1.
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24-25 March 2015
2067
2068
2069
2070
2071
8
7
6
5
Wheat straw
yield kg plot- 4
1
3
2
1
0
Figure 5: Mean±Standard deviation of wheat straw yield kgplot-1.
2067
2068
2069
2070
2071
4
3.5
3
Wheat grain
yield kg plot1
2.5
2
1.5
1
0.5
0
Figure 6: Mean±Standard deviation of wheat grain yield kg plot-1.
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Conclusion
Among the seven tested treatments number four (d) with application of 50% organic
plus 50% inorganic showed best over others. Thus application of inorganic fertilizer
along with organic manures proved to be sustainable for the rice and wheat production
in the ARSP condition of mid hill of eastern Nepal.Among the five years of data, the
year 2068/2069 was recorded better than other years. Rice crop showed best yield in
the year 2068 and wheat crop showed best in the year 2069.
References
Ellis EC and SM Wang. 1997. Sustainable Traditional Agriculture in the Tai lake
region of China. Agric. Ecosys. Environ. 61:177-193.
Ladha JK, KS Fischer, M Hossain, PR Hobbs and B Hardy. 2000. Improving the
productivity and sustainability of Rice-Wheat syste ms of the indo gangetic
plains: A synthesis of NARS-IRRI partnership research. Discussion Paper No.
40. International Rice Research Institute, Philippines.
Swaminathan MS. 1996. Sustainable agriculture towards an evergreen
revolution.Konark publishers Pvt. Ltd. A-149, Main Vikas Marg, Delhi
110092.
Timsina J and DJ Connor. 2001. Review on Productivity and management of ricewheat cropping systems: issues and challenges. Field Crop Research. 69:93132.
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SF-14
Effects
Drought
the Mobility
Arjun Shrestha
1
Foliar-Applied Boron
Thomas Eichert
Plants
2
1
Agro-enterprises Centre, FNCCI, Kathmandu
2
University of Bonn, Germany
Abstract
Boron is a unique micronutrient with narrow margin between deficiency and toxicity. It is
considered to be phloem immobile or to have only limited phloem mobility in many
higher plant species, where it is transported along the transpiration stream and accumulates
in the margins of leaves. However, one would expect a phloem transport of boron if the
back diffusion into the xylem in some way be prevented. The back diffusion into the
xylem may only be possible under reduced transpiration. In the present research, the
distribution of foliar-applied B in green gram plants (Vigna radiata L.) under varying
transpiration rates was evaluated in the Plant Nutrition greenhouse at the University of
Bonn, Germany, between July and September 2009. The experiment was laid out in a
Complete Randomized Block Design (CRBD) comprising three moisture levels (75, 50
and 25 % WHC), two boron levels (100 and 0 mM B). The top of the second trifoliate leaf
was immersed in 100 mM boric acid solution for one hour. The plant samples were
digested in pressure digestion and B concentration of digested samples were determined
by miniaturized cucurmin method. Results showed that most of the B absorbed from the
foliar application was accumulated in the treated leaf. There was no evidence of phloem B
movement out of the leaves under reduced transpiration. The transpiration rates affect the
foliar-B uptake in plants. However, the reduced transpiration did not support the phloem B
transport out of the leaves. Correction of B deficiency is directly affected by B mobility
(or immobility) in plants. It has generally been assumed that boron is relatively immobile
in dicotyledonous plants and that a continuous supply of this element in the substrate is
required for normal growth. In those species in which B is immobile, foliar-applied B will
not be translocated from the site of application. This B cannot supply the B requirements
of tissues not yet formed.
Keynotes: Boron dicotyledonous plants, foliar-application, mobility, transpiration rate.
Background
Boron is a unique micronutrient with narrow margin between deficiency and toxicity.
It is considered to be phloem immobile or to have only limited phloem mobility in
most of the higher plant species (Brown and Hu 1996, Brown and Shelp 1997).
Evidence suggests that the principal factorthat confers phloem B mobility to a plant
species is the synthesisof sugar alcohols and the subsequent transport of the Bsugaralcohol complex in the phloem to sink tissues such as vegetative or reproductive
meristems (Anonymus 2006, Brown and Hu 1998a, Brown and Hu 1996, Brown and
Shelp 1997, Hu et al. 1997. In species, where boron is phloem mobile, a polyol-Bpolyol complex is formed in the photosynthetic tissues as shown in the following
equation:
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Adopted from Masrchner (1995).
The polyols are single sugers, as sorbitol, manitol and dulcitol present in many plants
(Zimmermann and Ziegler 1975), but not present in several dicotyledonous plants.
A steep gradient in B concentration has often been found such that B concentration in
petioles and midribs is always lower than margins and tips (Oertli and Rechardson
1970). This pattern of distribution coincides with the appearances of deficiency
symptoms in young parts and toxicity symptoms in the margins of developed leaves of
plants (Brown and Jones 1971, Miwa and Fujiwara 2009). The occurrence of higher B
concentrations in old or matured leaves in comparison to younger leaves is evidence of
B immobility (Brown and Shelp 1997). If B is immobile in a species, then application
of foliar B fertilizers will results in enrichment of the treated leaf, but will not result in
enhanced B content of leaves formed after treatment or of tissues supplied primarily by
the phloem (Brown and Shelp 1997). It has generally been assumed that boron is
relatively immobile in dicotyledonous plants and that a continuous supply of this
element in the substrate is required for normal growth (Gauch and Dugger 1954).
Correction of B deficiency is directly affected by B mobility (or immobility) in plants.
In those species in which B is immobile, foliar-applied B will not be translocated from
the site of application. This B cannot supply the B requirements of tissues not yet
formed.
In species that do not produce significant quantities of polyols, boron is transported
along the transpiration stream and accumulated in the margins of leaves (Brown and
Hu 1998) and thus becoming immobile. Oertli and Richardson (1970). They also
emphasized since that the transport capacity of the xylem normally exceeds the
capacity of the phloem, the influx of boron into the leaf should exceed the efflux. Their
hypothesis states that B is phloem immobile because it can move out of the phloem
easily due to the high membrane permeability of boric acid (small, uncharged and
therefore membrane permeable molecules). High membrane permeability of B is
thought to induce a rapid efflux of B out of the phloem and its subsequent and
immediate retranslocation into the source leaf by the transpiration stream which
prevents the long distance phloem transport. The distribution of B is related to the loss
of water from shoot organs, suggesting that it is primarily xylem-mobile with limited
re-translocation in the phloem (Miwa and Fujiwara 2009 and Shelp et. al. 1995).
The consequence of the hypothesis of Oertli and Richardson (1970) would be that, a
low transpiration rate would reduce the xylem flux (influx) and thus the re-transport of
B into the leaf that ultimately increases the distance which B can be transported out of
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the leaf. Based on this assumption, the hypothesis of this research is “Under the
condition of reduced transpiration boron translocation in the phloem is enhanced”.
Plant material and growth conditions
The green gram plants (Vigna radiate) were grown till third true leaf stage with B
deficit condition but with sufficient amount of water and other nutrients.When the
plants reached third true leaf stage (40 DAS), three different moisture levels were
induced for one week: high moisture level (75% WHC), medium moisture level (50%
WHC) and low moisture level (25% WHC) considering low moisture level creates
drought stress to the plants. The moisture levels were maintained accordingly during
the treatment application. In order to add equal amounts of nutrients to all pots, the
amount of nutrient solution required for the lowest water level was added to all pots.
Then, the additional amount of water was added to pots for the medium and high water
levels in order to maintain the calculated standard pot weight. After the induction of
three different water levels, transpiration rates were measured only under different soil
moisture levels in the second true leaf of each selected plant by using a Steady State
Porometer LI 1600 (LI-CoR, Inc.). All other factors like light intensity and duration,
relative humidity, air temperature and air humidity remained constant. After a week of
drought stress, the top of the second trifoliate leaf was immersed into 100 mM boric
acid solution for one hour. The samples were collected one week after boron treatment.
During the sample collection, each plant was separated into six different parts
comprising the top of the trifoliate treated leaf including the sub-petiole, the rest of the
trifoliate treated leaf including the petiole, the parts above the treated leaf including the
third true leaf and growing tips, the first true leaf including the petiole, the stems below
the treated leaf and the roots (Figure 1). After harvest, all the samples were oven dried
at 600C for three days.
Figure 1: Illustration of different plant parts harvested in the experiment: top of the
trifoliate treated leaf including the sub-petiole (1), rest of trifoliate treated
leaf including the petiole (2), parts above the treated leaf including the
third true leaf and growing tips (3), first true leaf including the petiole (4),
stems below the treated leaf (5) and roots (6).
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24-25 March 2015
Tissue boron concentration
The plant material was dried at 600C for 3 days and subjected to a pressure digestion.
Tissue B concentration in the digested samples was then determined by miniaturized
curcumin method (Wimmer and Goldbach 1999).
Statistics
Data obtained from the experiments were analyzed by SPSS for Windows Version 18.0
using the General Linear Model (GLM). Analysis of Variance (ANOVA) was used to
determine significant effects of the treatments. Tukey-test was used to determine
significant differences between treatments. All graphs were plotted using Sigma plot
version 11.0. All results are given as means of three replicates ± standard error of the
mean.
Results
Transpiration characteristics
The transpiration rates of plants under low moisture level was significantly lower than
higher and medium MLs in both B treated and B controlled plants (Figure 2). The
transpiration was 2.6±0.5 mmol m-2 s-1 at high ML, 2.2±0.5 mmol m-2 s-1 at medium
moisture level and 1.4±0.4 mmol m-2 s-1 at low moisture levelin B treated plants. It was
3.0±0.6 mmol m-2 s-1 at high ML, 2.3±0.5 mmol m-2 s-1 at medium moisture level and
1.6±0.4 mmol m-2 s-1 at low moisture levelin B controlled plants.
Total Boron uptake
Water supply and foliar-application of boric acid differentially affected the total B
uptake and B content in roots, stems, leaves and shoots. The effects varied with
sampling time (immediately or one week after B treatments). Comparing the B content
of B treated and untreated plants separated after soil moisture level gave a significant
difference at high and low moisture levels (Figure 3). The mean B content was
118.7±8.2 µg at high, 96.5±5.7 µg at medium and 92.7±6.1 µg at low moisture levels
in treated plants, respectively. It was 75.4±2.2 µg at high, 72.0±11.0 µg at medium and
68.8±5.5 µg at low moisture level, respectively, in untreated control plants.
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24-25 March 2015
Figure 2: Transpiration rates (mmolm-2s-1) of 6 week-old Vigna radiata L. plants after
treatment application. Black bars and grey bars represents the B treated and
untreated controls, respectively. Measurement was taken by using the Steady
State Porometer LI 1600 (LI-CoR, Inc.) in the second true leaves of each
selected plants.
Figure 3: Total B content (µg) in 6 weeks-old B treated Vigna radiata L. plants (black
bars) and in untreated control (white bars) one hour after foliar B application
(a) and one week after foliar B application (b) as boric acid solution (100 mM).
Before B application, plants were exposed to different moisture conditions for a
week. Asterisks indicate significant differences between B-treated and
untreated control plants at the respective moisture levels (t-test, n=3, *: p≤0.05,
**: p≤0.01, ***: p≤0.001). Vertical bars indicate standard errors of the means.
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Boron Distribution
Plants showed a significant difference between the B content of treated leaf of B
treated plants and corresponding leaves of untreated control plants at all moisture
levels (Figure 4a). Total mean B content of B treated leaf was 28.5±2.3 µg at high ML,
27.1±3.9 µg at medium moisture level and 21.6±5.0 µg at low moisture levelin B
treated plants, and it was 4.3±0.6 µg at high ML, 4.4±0.9 µg at medium moisture level
and 4.3±1.0 µg at low moisture level in the corresponding leaves of untreated control
plants (Table 3). The increment of B was 24.2 µg at high, 22.7 µg at medium, and 17.3
µg at low moisture level, which account for 558, 511 and 400 % of the total B content
of the corresponding leaves of control plants, respectively.
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Figure 4: B content (µg) in treated leaf (a), surrounding leaflets of treated leaf (b), first
true leaves (c), parts above treated leaf (d), stem (e) and roots (f) one week
after foliar B application as boric acid solution (100 mM) to 6 weeks-old
Vigna radiata L. plants (black bars) and in untreated control (white bars).
Before B application, plants were exposed to different moisture levels for a
week. Asterisks indicate significant differences between B-treated plants
and control at the respective water level (t-test, n=3, *: p≤0.05, **: p≤0.01,
***: p≤0.001). Vertical Bars indicate standard errors of the means.
Plants showed a significant difference between the B content of rest of treated leaf of B
treated plants and corresponding leaves of untreated control plants only at a high
moisture level (Figure 4b). Total mean B content in the surrounding leaflets of treated
leaf was 11.8±1.4 µg in treated plants and 7.4±0.7 µg in untreated control plants. The
increment of B content was 4.4 µg, which account for 60% of total B content at high
moisture level in rest of treated leaf of untreated control plants. There was no
significant difference between the B content of parts above the treated leaf (Figure 4c),
first true leaf (Figure 4d), stem below the B treated leaf (Figure 4e) and roots (Figure
4f) of B treated and untreated control plants at all moisture levels.
Discussion
The foliar application of B had a highly significant effect on total plant B content.
Plants grown under high moisture level resulted in highest B uptake and low moisture
level resulted in lowest B uptake. It might be due to the fact that plants grown under
low moisture level might have received lower amount of water from the soil compared
to plants grown under medium and high moisture levels. Because of the water scarcity
to transpire, there might be the formation of waxes in the cuticle layer of the
transpiring leaves of the plants grown under low moisture level to minimise the water
loss from the transpiration which might prevent the foliar-applied B to enter inside the
leaf. The significant effect of the B treatment on total plant B content under different
soil moisture levels indicates that the plants were able to take up foliar-applied B.
Similarly, high moisture level resulted in the highest B content, followed by the
medium and low moisture levels, irrespective of the boron levels. Within the moisture
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levels, there was a significant difference of B content in B treated plants at medium and
low moisture level one hour after treatment and at high and low moisture level one
week after treatment (Figures 3). It is well known that B transport into shoot parts
exposed to the atmosphere is predominantly driven by transpiration flow in the xylem
(Brown and Shelp 1997). The significant correlation between transpiration and total B
uptake indicates that transpiration rates affected the total B uptake of the plants. The
correlation coefficient was higher in B control plants (r2 = 0.99, Figure 3b) than in B
treated plants (r2 = 0.71, Figure 3a). This is comparable to the results of Kohl and
Oertli (1961) found in Easter lily. They concluded that boron moves passively in the
transpiration stream. Eichert and Goldbach (2010) after an experiment in Richinus
communis L. under controlled environment suggested that mobility of foliar-applied B
could increase not only during humid conditions reducing the transpirational water loss
of leaves but also during dry soil conditions reducing water availability. Hu and Brown
(1997) reviewed several experimental studies and concluded that B uptake in higher
plants is a passive process and one of the influencing factors of which is transpiration
rates. The lower the correlation coefficient in the B treated plants compared to control
plants (as stated above) might be due to the additional B from foliar application and not
due to transpiration.
Boron level had a highly significant effect on leaf B content of treated leaf. There was
a significant difference between the leaf B content from treated leaf of B treated plants
and corresponding leaf of untreated control plants (Figure 4a). Most of the foliarapplied B accumulated in the treated leaf and did not show the movement from treated
leaf towards surrounding leaflets (of treated leaf). Boaretto et al. (2007) found the
similar findings in citrus. They concluded that the foliar fertilization increased the leaf
B content. However, the B content did not occur difference in the leaves and fruit
developed after the spraying. Comparatively lower the B content in B treated leaf at
low moisture level indicates that the absorbed B in the source leaf was moved out
towards the other plant parts. However, other plant parts including rest of the treated
leaf did not received B from the source leaf. It was expected that reduced transpiration
could reduce the re-transport of B into the source leaf and thereby increase the distance
that B can be transported out of the leaf, resulting in increased amounts of B in
untreated plant parts, e.g. the newly growing shoots. But the result did not support the
assumption. High B concentration at high moisture level might be due to high
transpiration. Under the condition of low moisture level, the surface of transpiring
leaves become thicker by the formation of wax layer in the cuticles to minimise the
water loss from transpiration. And, this thick wax layer might prevent to enter the
foliar applied boron into the leaves.
The B levels had a significant effect on leaf B content of rest the treated leaf. The
significant difference in B content in rest of treated leaf from B treated plants and
untreated control plants indicated that part of foliar-applied B, absorbed from the
treated leaf moved towards the surrounding leaflets of the treated leaf (Figure 4b).
158
24-25 March 2015
Movement of B from treated leaf towards surrounding leaflets (of treated leaf)
indicates that the absorbed B in the source leaves was able to move out towards the
other plant parts. However, the movement of B was detected only at high moisture
level. It might be due to high B concentration in the B treated leaf. At extremely high
concentrations, some boron moves in tissues other than the xylem (Oertli and
Richardson 1970). Oertli (1993) conducted an experiment on tomato seedlings and
examined the symptoms expressions of B deficiency. He concluded that little B was
mobilized and transported into the tops, whereas small but adequate amount was
remobilized and transported to the roots. It is important to note, however, that even
though the data obtained support the view that B moves in the xylem, the
complications arising from differential transport mechanisms (influx and efflux) and
accumulation in transit (petiole) must be underlined. The lateral leaflets of the treated
leaf acquired B not only from the B treated leaf but also from the roots. At the same
time, it lost parts of acquired B together with the treated leaf to rest of other (younger)
parts.
The B content of the treated leaf in the B treated plants significantly correlated with
transpiration (Figure 6). It might be due to the accumulation of foliar-applied B in the
treated leaf and transported B from the roots in the treated leaf. The high transpiration
rate increased the amount of B in the treated leaf (highly transpiring organ). This result
suggests that B moves with transpiration streams in the non-living xylem tissue and
accumulated in the highly transpiring organs (older leaves). The high rate of
transpiration might prevent the efflux of B out of the leaf with increasing capacity of
xylem flow rate. Once B transported into the leaves in the xylem and as water is lost
through the transpiration, it is concentrated in the margin of the leaf (Oertli and
Richardson 1970). The lateral leaflets of the treated leaf probably received B both from
159
24-25 March 2015
the treated leaf via phloem transport and from the roots via transpiration. B might be
loaded into the phloem in the margin of treated leaf to equilibrate the concentration and
transport towards the basal areas of the leaf with the concentration gradient as
suggested by Oertli and Richardson (1970). They hypothesized that part of the phloem
loaded B in the leaf is lost into the adjacent tissues in the basal areas of the leaves and
petiole where concentration is low. It was expected that reduced transpiration decrease
the xylem flux and reduce the re-transport of B into the source leaf. This ultimately,
increase the distance that B can be transported out of the leaf. Shelp et al.(1995)
reviewed several experimental evidences and concluded that the distribution of B is
related to loss of water from shoot organs, suggesting that it is primarily xylem mobile.
Conclusion
The present study confirms the well-known fact that plants have a capacity to take up
foliar-applied B. The total B uptake depended on the moisture levels in the root zone of
the plants as well. The uptake (total B mass) and translocation (B in rest of treated leaf)
of B in the plant was related to the amount of water consumed and consequently to the
transpiration rates of the plants. However, all of the plant parts do not participate to the
same extent in B distribution.
Movement of B from treated leaf towards surrounding leaflets indicates that the
absorbed B in the source leaves was able to move out towards the other plant parts.
However, the movement of B was detected only at high moisture level. It was expected
that reduced transpiration could reduce the re-transport of B into the source leaf and
thereby increase the distance that B can be transported out of the leaf, resulting in
increased amounts of B in untreated plant parts, e.g. the newly growing shoots.
However, the increase in the B content of the parts above the B treated leaf may not
only come from the older leaves but could also be due to the increase in dry weight of
biomass. Increase in the biomass due to the plant growth also increased the B uptake
from the roots which interfered in the present study with B translocation from the
treated leaf. B content in the newly growing plant parts cannot be separated whether it
come from B treated leaf or from the roots. The results showed no evidence of phloem
B movement out of the leaves under reduced transpiration. The suggested conclusion is
that the transpiration rates affect the foliar-B uptake and distribution in plants.
However, the question of phloem B transport under reduced transpiration is still to be
answered. To answer this question it is necessary to analyse the phloem flux too, which
is still lacking in this research. Analysis of rubidium (Rb) as a phloem marker may
verify the findings of this research. The reduction of transpiration rates by low soil
water availability might have not been sufficient to allow the export of the foliarabsorbed B out of the treated leaf. It could thus be better to reduce the transpiration by
further lowering the moisture levels below 25 % WHC for clearer results. It is
necessary to quantify the amount of B that plant received from the soil before and after
the B treatment. It would be better to use B isotopes (10B and 11B) to quantify the trace
amount of B.
160
24-25 March 2015
References
Annonymus. 2006. Is boron mobile or immobile? Agrichem Liquid Logic (0005)
Retrived from http://www.agrichem.com.au/liquidlogics/pdf/
Liquid%20Logics%205.pdf
Boaretto RM,T Muraoka,MF Gine and AE Boaretto. 2007. Absorption of foliar
sprayed boron and its translocation in the citrus plants when applied at
different phonological phases. Pp. 25-31. In: Proc. of third International
symposium on all aspects of plant and animal boron nutrition. F Xu , HE
Goldbach, PH Brown, RW Bell,T Fujiwara, CD Hunt,S Goldberg and L Shi
(eds.). Advances in Plant and Animal Boron Nutrition. Springer. The
Netherlands.
Brown JC and WE Jones. 1971. Differential transport of boron in tomato
(Lycopersicon esculentum). Physiol. Plant. 25: 279-82.
Brown PH and H Hu. 1996. Phloem mobility of boron is species dependent: evidence
for boron mobility in sorbitol-rich species. Ann. Bot. 77: 497-505.
Brown PH and H Hu. 1998a. Boron mobility and consequent management in different
crops. Better Crops 82: 2.
Brown PH and B J Shelp. 1997. Boron mobility in plants. Plant Soil 193: 85–101.
Eichert T and Goldbach H E. 2010. Transpiration rate affects the mobility of foliarapplied boron in Ricinus communis L. cv. Impala. Plant Soil. 328(1-2): 165174.
Gauch HG and Jr. WM Dugger.1954.The physiological action of boron in higher
plants: A review and interpretation. Maryland Agric. Exp. Sta. Tech. Bull. A80.
Hu H and PH Brown. 1997. Absorption of boron by plants. Plant Soil 193: 49-58.
Hu H,SG Penn,CB Lebrilla and PH Brown. 1997. Isolation and characterization of
soluble boron complexes in higher plants: The mechanism of phloem mobility
of boron. Plant Physiol. 113: 649-655.
Kohl HC and JJ Oertli. 1961. Distribution of boron in leaves. Plant Physiol. 36: 420424.
Marschner H. 1995. Boron. Marschner H. (ed.) Mineral nutrition of higher pants.
Academic Press, London. Pp. 379-396.
Miwa K and T Fujiwara. 2009. Boron transport in plants: coordinated regulation of
transporters. UC Davis: The Proceedings of the International Plant Nutrition
Colloquium XVI. (Retrieved from: http://escholarship.org/uc/item/8qj8q3d7)
Oertli JJ. 1993. The mobility of boron in plants. Plant Soil 155/156: 301-304.
Oertli JJ and WF Richardson. 1970. The mechanism of boron immobility in plants.
Physiol. Plant. 23: 108-116.
Shelp BJ, E Marentes, AM Kitheka and P Vivekanandan. 1995. Boron mobility in
plants. Physiol. Plant. 94: 356-361.
161
24-25 March 2015
Wimmer MA and HE Goldbach. 1999. A miniaturized curcumin method for the
determination of boron in solutions and biological samples. J. Plant Nutr. Soil
Sci. 162:15-18.
Zimmermann MH, HZiegler. 1975. List of sugars and sugar alcohols in sieve-tube
exudates. MH Zimmermann and JA Milburn. (eds.) Encyclopedia of plant
physiology (new series) vol. 1, transport in plants I. Phloem transport.
Springer, Berlin. Pp. 480-503.
162
24-25 March 2015
SF-15
Efficacy of Nitrogen and Phosphorus on Rice under Rice-Tomato
Cropping System at Central Terai Region, Nepal
Shova Shrestha1, Sabina Devkota1, Bishnu H Adhikary and Sahabuddin Khan
1
Soil Science Division (
) Khumaltar
Agricultural Research Station (NARC),
, Nepal
Abstract
Field experiments were conducted during the rice seasons for two consecutive years (2070
and 2071) in ARS, Belachapi to evaluate the optimal level of nutrient for better and
sustainable rice grain production under Rice-Tomato cropping system. Randomized
Complete Block Design (RCBD) was used with twelve treatments of four N levels (0, 80,
120 and160 kg ha-1) and three level of P (0, 40 and 80 kg ha-1). The plot size was 12 sq. m.
and rice variety Hardinath-1 was
for the study. The highest rice grain yield (4854 kg
ha-1), plant height (108.23 cm) was recorded in 160:80:40: N: P2O5: K2O kg ha-1.
Statistically, both grain and straw yield were significantly higher as compared to other
(P)
treatments. Two-years results revealed that recommended dose
(K)could be increase for sustainable rice production under rice-tomato cropping
system in light textured soil of ARS, Belachapi. The experimental results also indicated a
depletion of inherent soil organic matter.
Keywords: Crop productivity, grain yield, rice-wheat system sustainable rice production.
Introduction
Rice is the most important crop of Nepal. The area and production of the crop is
increasing but productivity is still not satisfactory. Inadequate plant nutrients supply
has been the major factor contributing to the decreased crop productivity (Gami and
Sah 1998, Dobermann et al.). 2002. Similarly, increased use of unbalanced fertilizer
without considering the native soil fertility and decline trend in organic matter
incorporation by farmers are some of possible factors affecting productivity and soil
fertility (Balasubramanian et al. 1999. Furthermore, nutrient management is the key
factor for deciding the productivity of crop. The method of N application is also
important for reducing N losses and improving the nitrogen use efficiency the crop.
Rice crop absorbs an average of 20 kg N:11 kg P2O5:30 kg:K2O, 3 kg S, 7 kg Ca, 3 kg
Mg, 675 g Mn, 150 g Fe, 40 g Zn, 18 g Cu, 15 g B, 2 g Mo and 52 kg Si. Out of the
total uptake, about 50 percent of N, 55 percent of K and 65 percent of P are absorbed at
early panicle-initiation stage. About 80 percent of N, 60 percent of K and 95 percent of
P uptake is completed at heading stage (http://www.fao.org/3/a-a0443e/a0443e04
down loaded on 13.6.2013).
163
24-25 March 2015
Materials and Method
The field experiment was initiated since August 2012 on Rice -Tomato cropping
system with an objective to enhance the socioeconomic condition of Nepalese farmers
through the adoption of optimum level plant nutrient application appropriate
technologies in rice and tomato cultivation.The experiment was conducted in RCBD
design with twelve treatments and three replications at ARS, Belachhapi. Hardinath 1
variety of rice was transplanted. Treatments consisted of four rates of N fertilizers (0, 80,
120,160 kg ha-1) and three rates of P fertilizers (0, 40, 80,160 kg P2O5 kg ha-1) and
constant level of K fertilizer (40 kg ha-1). Half dose of N and full dose of P and K were
applied as basal dose. Remaining half dose of N was applied in two splits doses.
Required parameters were recorded and analyzed statistically to observe the treatment
differences. Collected data were compiled and subjected to analysis of variance by
using MSTAT-C package. Mean was separated at 5% level of significance using
Duncan’s Multiple Range Test (DMRT).
Table 7: Nutrient treatments applied for paddy – tomato cropping system in ARS,
Belachapi.
Treatments
Rice(N:P2O5:K2O),
Tomato(N:P2O5:K2O),
kg ha-1
kg ha-1
1
0:0:0
0:0:0
2
80:0:40
100:0:80
3
120:0:40
150:0:80
4
160:0:40
200:0:80
5
0:40:40
0:100:80
6
80:40:40
100:100:80
7
120:40:40
150:100:80
8
160:40:40
200:100:80
9
0:80:40
0:200:80
10
80:80:40
100:200:80
11
120:80:40
150:200:80
12
160:80:40
200:200:80
Result and Discussion
Combined data reveal that the highest rice grain production found 4882 kg ha-1 and plant
height 108.23 cm was recorded highest in 160:80:40: N: P2O5: K2O kg ha-1 which was
found at par with
120:0:40: N: P2O5: K2O kg ha-1 was 4854 kg ha-1 (Table 2).
Statistically, both grain and straw yield were found significantly higher as compare to
control. The optimal supply of P and K is required for high yields, even during periods
of water stress. Tiwari 2002 reported that the current general use of P and K is very
low in India and the recommended fertilizer dose 120:60:60: N: P2O5: K2O kg ha-1for
6.87 t ha-1.
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24-25 March 2015
Table 8:
Agronomic performance of paddy
Belachapi from 2013 to 2014
Treatments Yield, kg
Plant height,
-1
ha
cm
0:0:0
2774d
94.77a
80:0:40
4387 abc
105.5a
120:0:40
4854a
106.1a
abc
160:0:40
4285
102.7a
bcd
0:40:40
3184
98.53a
80:40:40
4323 abc
104.7a
abc
120:40:40
4316
103.9a
160:40:40
4502ab
106.2a
cd
0:80:40
3083
97.63a
abcd
80:80:40
4077
103.3a
120:80:40
4579ab
101.7a
a
160:80:40
4882
108.2 a
Mean
3917.35
108.889
CV,%
16.80
5.36
F- value
2.8288
3.4755
in paddy – tomato system in ARS,
Number of
tiller
209 b
266 ab
284 ab
292 ab
220ab
270 ab
292 ab
298 ab
246ab
309a
255 ab
262 ab
260.056
13.92
3.8051
Panicle length,
cm
26.03a
25.7a
27.23a
27.23a
26.83a
26.8a
26.98a
26.3a
26.5a
27.03a
26.72a
27.1a
27.467
3.95
2.0853
Conclusion
The timing of N applications is very important for improving the efficiency of the
Nitrogen fertilizer. The split applications are especially for where total N requirement
is high in order to avoid leaching losses. The site specific nutrient management
technology would be useful for increasing the rice production. Phosphorus and potash
recommendation dose could be increased for sustainable rice production under Rice Tomato cropping system in light textured soil under Belachapi condition.
References
BalasubramanianV,JK Ladha, and GL Denning. 1999.Resource management in Rice
System. Nutrients:167-180.
Dobermann A, C Wiltand and D Dawe.2002. Performance of Site-Specific Nutrient
Management in Intensive Rice Cropping Systems of Asia. Better Crops
International Vol. 16, No. 1
Gami SK, and MP Sah.1998. Long-term soil fertility experiment under Rice-wheat
cropping system. In: Proc. of first national workshop on long-term soil fertility
experiments.
Tiwari KN. 2002. Better Crops International Vol. 16, Special Supplement.
Website :(http://www.fao.org/3/a-a0443e/a0443e04 down lode 13.6.2013
165
24-25 March 2015
SF-16
Long-term Soil Fertility Experiment Under Rice – Wheat Cropping
System in Regional Agricultural Research Station, Parwanipur, Bara,
Nepal
Shova Shrestha1, Gautam Shrestha2, Maheshwor P Sah3, Kailash P Bhurer and, Bishnu
H Adhikary
1
Khumaltar
Regional Agricultural Research Station
3
Regional Agricultural Research Station
2
, Nepal
, Khajura, Banke
, Pawanipur
Abstract
Due to over mining of plant nutrients, soil in the Terai region have been depleted and to
overcome th problem, it is necessary to add additional elements in the field. Long-term
soil fertility experiment in Parwanipur was started since 1980/1981 to evaluate the longterm effect of organic manure and inorganic fertilizer on crop yield and soil properties.
experiment was conducted in Randomized
Complete Block Design (RCBD) with three replications and twelve treatments. Analysis of
both
and wheat grain yield, straw yield, thousand grain
variance revealed
weight, number of tillers, panicle length and plant height were significant
(p
value <0.001) between treatments. Wheat grain yield (2533 kg ha-1 ),straw yield (5323 kg
ha-1),
grain yield (3835 kg ha-1 ) and straw yield (6061 kg ha-1) were significant high
in the plots with the treatment applied at 10t ha-1 of FYM +50 kg ha-1 of N in Rice and
100:30:30 kg ha-1of N:P2O5:K2O in Wheat). Regression analysis showed that wheat
thousand grain weight significant
(p value <0.05) (adjusted R squared value >
0.20)
the time line in all the treatments. From these results, farmers are recommended
to use farm yard manure for increase the long-term productivity and to enrich the soil with
plant nutrients and organic matter.
Keywords: Cropping system, grain yield, long-term soil fertility, nutrient management
straw yield.
Introduction
Paddy - wheat cropping system is a predominant cropping system in the Terai and mid
hills of Nepal. However, inherent fertility constraints have resulted in the lower
productivity(Fischer 1998). Long term experiments are valuable for evaluating the
effects of continuous cropping on the cropping system and the soil capacity to sustain
nutrient supply and the productivity.
In long term soil fertility experiment started in 1972, application of FYM 20 t ha-1
resulted in higher yield of both paddy and wheat than full dose of chemical fertilizer
(120-30-30 kg N-P2O5-K2Oha-1) in Panjab, India condition (Rasool et al. 2007).
166
24-25 March 2015
The Parwanipur long term experiment was started in 1980/81 to evaluate the effect of
organic manure and inorganic fertilizers on crop yields as well as on soil properties and
to study the effect of N with or without P and K in the long run under paddy –wheat
system. A past paper by Gami and Sah (1998) has already published the 15 years
research results in Parwanipur. They revealed that application of100-30-30N-P2O5K2Okg per hectare produced the highest grain yield with production of 3.16 t ha-1
paddy and 3.106 t ha-1 wheat. They also mentioned that addition of zinc (25 kg per
hectare) could increase the grain yield in the long term.
However, there is increased concern about the yield decline in long term fertilizer
experiments(Dawe et al. 2000).Hence, this paper tries to affirm the present condition
of crop production in long term soilfertilityexperiment at RARS, Parwanipur, Bara
Nepal.
The field experiment was initiated since June 1980 on paddy -wheat cropping system.
A randomized complete block design was used with three replications. The plot size
was 24square meter(6 ×4 sq.meter). There were 12 different treatments (Table 1). Rice
was transplanted at 20 by 15 cm spacing and wheat was continuously sown in row
25cm apart. All phosphate and potassium fertiliser and one half of nitrogen was
applied in the form of urea,triple super phosphate (TSP),Diammonium Phosphate
(DAP), Complexal, Murate of Potash (based on the availability of fertilizer material)
.Zinc Sulphate (ZnSO4)at the rate of 10 kg Zn ha-1was applied according to the
treatments. The remaining half dose nitrogen was top dressed 30-35 days after
planting. At harvest, agronomic parameters were measured. Collected data were
compiled and subjected to analysis of variance by using R package.
Table 1: Nutrient treatments applied for paddy – wheat cropping system in
RARS, Parwanipur.
Treatments
Paddy (kg N:P2O5:K2O)
Wheat(kg N:P2O5:K2O)
1
0:0:0
0:0:0
2
100:0:0
100:0:0
3
100:30:0
100:30:0
4
100:0:30
100:0:30
5
100:30:30
100:30:30
6
100:0:0
100:0:0
7
50:0:0
50:0:0
8
50:20:0
50:20:0
9
FYM10t ha-1
FYM10 t ha-1
-1
10
100:30:30+25kg ZnSO4 ha
100:30:30
11
FYM10t ha-1+ 50:0:0
100:30:30
12
50:0:0+ chopped straw 10 t ha-1
100:30:30
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24-25 March 2015
Paddy agronomic characteristics
In paddy, the highest plant height (95 cm), panicle length (25 cm) and thousand grain
weight (21 g)were observed in100:30:-30 kg N:P2O5:K2O + 25kg ZnSO4 ha-1 in paddy
(Table 2). At par with Gami and Sah (1998), effect of zinc sulphate application was
distinct in plant height.The highest grain yield (3835 kg ha-1) and straw yield (6061 kg
ha-1) were obtained with 50:0:0 N:P2O5:K2O + FYM 10 t ha-1 (Table 2).However, Gami
and Sah (1998) reported that 15 years the result of by highest grain yield in
100:30:30 kg N:P2O5:K2O ha-1. Whereas Shrestha and Chaudhary (2015) obtained
higher rice grain yield (3730 kg ha-1) with the application of FYM 10 t ha-1 than in
100:30:30 N:P2O5:K2O kg ha-1.The result also revealed that FYM use is essential for
long term increase the soil fertility and crop productivity. However, FYM alone was
not meeting the nutrient requirement of the crop.The addition of 50 kg ha-1 with FYM
was needed to increase the paddy production.
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24-25 March 2015
Table 2: Agronomic performanceof paddyin paddy – wheat system in RARS, Parwanipur from 2000 to 2014.
Treatment(N-P2O5-K2O
kg ha-1)
0-0-0
100-0-0
100-30-0
100-0-30
100-30-30
100-0-0
50-0-0
50-20-0
FYM 10 t ha-1
100-30-30 + 25 kg
ZnSO4 ha-1
50-0-0 + FYM 10 t ha-1
50-0-0 + 10 t ha-1
chopped straw
P - value
HSD value
CV,%
Plant height,
cm
73.9±3.2d
85.9±1.6bc
88.5 ±1.4abc
88.2 ±1.6abc
92.2±1.5ab
92.3 ±1.4ab
83.5±1.5c
85.4±1.4bc
84.2±1.4c
Number of
tillers
180.5±6.5e
248.2±5.6abc
244.2±5.7abcd
249.0±5.0ab
263.3±6.7a
255.9±4.9a
221.0±4.5cd
225.1±4.8bcd
216.8±7.0d
Panicle length,
cm
20.295±0.4d
23.157±0.4abc
23.286±0.3abc
23.233±0.5abc
24.262±0.4ab
24.252±0.5ab
22.31±0.4c
23.024±0.4abc
22.538±0.4bc
Thousand
grain weight, g
19.8±0.2c
20.5±0.2abc
20.6±0.2abc
20.7±0.2ab
20.8±0.2a
20.9±0.2a
20.3±0.2abc
20.4±0.2abc
19.9±0.2bc
Straw yield, kg ha3272.5±200.0g
5240.1±158.3bcd
5501.8±166.3abc
5533.4±189.6abc
5972.9±168.7abc
5686.5±186.8abc
4299.0±180.8f
4447.6±114.7ef
4480.8±162.4def
1929.7±109.5h
3058.1±119.7def
3330.4±10.5bcd
3128.8±106.5cdef
3571.2±88.6abc
3494.3±123.7abcd
2527.6±92.4g
2746±100.0fg
2808.7±109.5efg
94.911±1.24a
262.0±5.7a
24.6±0.5a
21.1±0.2a
6000.7±163.5ab
3706.2±103.8ab
92.73±1.1ab
245.8±7.4abc
24.443±0.4ab
20.9±0.2a
6061.4±183.3a
3835.2±101.6a
88.4 ±1.6abc
242.4±6.6abcd
23.629±0.4abc
60.9±40.1a
5174.7±155.9cde
3276.6±110.9bcde
<0.001
6.8
9.32
<0.001
29.6
13.53
<0.001
2.0
8.01
<0.001
0.9
80.43
<0.001
793.1
16.1
<0.001
497.1
21.2
169
Grain yield, kgha-1
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24-25 March 2015
Table 3: Regression results of different treatments in paddy grain yield along the years
(2000 to 2014).
Treatments
Intercept
p-value
0:0:0
100:0:0
100:30:0
100:0:30
100:30:30
100:0:0
50:0:0
50:20:0
-90389.0
0.064
-1321.0
0.937
-15854.9
0.707
-48955.1
0.288
18275.3
0.719
-91374.4
0.101
-57020.2
0.156
-33836.6
0.424
4900.7
0.967
-50802.8
0.261
-68104.0
0.145
-90389.0
0.074
-1
FYM 10 t ha
-1
100:30:30 + 25 kg ZnSO4 ha
-1
FYM 10 t ha + 50:0:0
-1
50:0:0 + chopped straw 10 t ha
Wheat agronomic characteristics
In wheat, highest grain yield (2530 kg ha-1) was obtained in the plots applied with 50
kg nitrogen plus FYM 10 t ha-1 in paddy and 100:30:30 kg N:P2O5:K2O ha-1 in wheat
(Table 4). There were no significant differences in after-effect of paddy nutrient
treatments in wheat agronomic characteristics (Table 4). Regression analysis of paddy
grain showed neither significant negative trend line nor positive trend line for paddy
grain yields (Table 3).
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24-25 March 2015
Table 9: Wheat agronomic performance in paddy – wheat system in RARS, Parwanipur from 2000 to 2014.
Treatment(NP2O5-K2O kg
ha-1)
0:0:0
100:0:0
100:30:0
100:0:30
100:30:30
100:30:30
50:0:0
50:20:0
FYM 10 t ha-1
100:30:30
100:30:30
100:30:30
P - value
HSD value
CV,%
Plant height,
cm
Number of
tillers
63.0 ± 2.1e
69.1±1.7de
79.0±1.5bc
74.6 ±1.0cd
88.9 ± 2.0a
86.5 ± 2.3ab
72.5± 1.5cd
77.9 ± 1.67 c
77.3 ± 1.9cd
90.2±2.0a
89.4±1.7a
89.3±1.8a
<0.001
8.64
9.67
145.2±10.3e
169.8±13.5de
206.6±13.1abcd
189.8±11.6bcde
240.2±11.9ab
231.2±9.4abc
169.6±9.8de
186.8±9.5cde
173±8.8de
249.7±10.7a
242.2±11.4a
235.7±9.8abc
<0.001
51.278
22.56
Panicle
length,
cm
7.0±0.8b
8.7±0.4ab
9.8±0.3a
10.1±0.4a
10.2±0.2a
10±0.16a
9.13±0.1a
9.6±0.2a
9.3±0.2a
10.5±0.1a
10.3±0.0a
10.3±0.3a
<0.001
1.78
4.71
Thousand grain
weight, g
Straw yield, kg
ha-1
36.7±1.8a
35.5±1.7a
33.6±1.7a
38.5±1.8a
38.6±1.7a
38.2±1.7a
35.1±1.6a
34.9±1.7a
40.4±2.0a
38.1±1.6a
38.8±1.9a
38.6±2.2a
<0.001
8.5
20.55
1253.87±104.8d
2077.07±156.8cd
3449.18±260.8bc
2753.38±214.1cd
4750.07±425.9ab
4317.07±360.0ab
2192.48±186.1cd
2815.06±244.7c
2435.67±192.4cd
5050.66±450.7a
5323.938±506.9a
5291.96±457.5a
<0.001
1508.2
35.34
Regression analysis showed no significant trend lines in wheat grain yield (Table 5).
171
Grain yield, kg ha-1
577.2± 28.8e
944.1±66.4de
1614.6±112.3b
1449.6±70.8bc
2454.9±107.8a
2258.8±114.5a
1128.4±58.1cd
1358.7±88.3bcd
1203.3±55.6bcd
2398.8±126.9a
2533.8±113.1a
2478.7±121.5a
<0.001
434.99
29.62
24-25 March 2015
Table 5: Regression results of different treatments in wheat yield along the years
(2000 to 2014).
Treatments
0:0:0
100:0:0
100:30:0
100:0:30
100:30:30
100:30:30
50:0:0
50:20:0
FYM 10 t ha-1
100:30:30
100:30:30
100:30:30
Intercept
-12499.5
-67064.9
-133815.0
42952.8
-58659.5
-46599.3
-43503.4
-94614.1
-53202.0
-55134.5
-120919.0
-47619.3
p-value
0.446
0.075
0.34
0.316
0.333
0.467
0.186
0.057
0.089
0.13
0.059
0.498
Conclusion
The Farm Yard Manure should be applied to maintain the soil fertility. However, FYM
alone cannot be expected to give economic returns and it is essential that it should be
applied in combination with inorganic fertilizer to obtain the optimum economic yield.
The integrated use of farm yard manure and inorganic fertilizers was found to increase
the sustainable crop productivity and soil fertility Use of FYM at the rate of 10 t ha-1 +
50 kg N ha-1in paddy and 100-30-30 kg N:P2O5:K2O ha-1showed the best combination
for the sustainability of paddy – wheat cropping system. The response of yield to
applied phosphorus is greater in wheat than in paddy. The balance dose of NPK in
wheat is essential to sustain the productivity in R-W system.
Acknowledgements
Authors are grateful to late Mr. Maheshwor P Prasad Sah who initiated as well as
conducted this long term soil fertility experiment in RARS, Parwanipur. We thank the
Regional Director, RARS Parwanipur Mr. Kailash Prasad Bhure rfor providing
logistics support to continue this experiment.
References
Dawe D, A Dobermann, P Moya, S Abdulrachman, B Singh, P Lal, SY Li, B Lin, G
Panaullah, O Sariam, Y Singh, A Swarup, PS Tan and QX Zhen. 2000. How
widespread are yield declines in long-term rice experiments in Asia? Field
crops research. 66:175-193.
Fischer K. 1998. Toward increasing nutrient-use efficiency in rice cropping systems:
the next generation of technology. Field Crops Research. 56:1-6.
Gami SK and MP Sah. 1998. Long-term soil fertility experiment under rice-wheat
cropping system. National long-term soil fertility experiments workshop.
Nepal Agricultural Research Council, Soil Science Division, NARC,
Khumaltar. Pp. 12-28.
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24-25 March 2015
Rasool R, S Kukal and G Hira. 2007. Soil physical fertility and crop performance as
affected by long term application of FYM and inorganic fertilizers in rice–
wheat system. Soil and Tillage research. 96:64-72.
Shrestha G and RD Chaudhary. 2015. Agronomic performance of paddy-wheat system
under long term soil fertility trial: a guide-line for fertilizer recommendation in
mid-western terai region. In: Proc. of the 28th summer crops workshop. Nepal
Agricultural Research Council, National Rice Research Programme (NRRP).
173
24-25 March 2015
SF-17
Biochar: ts ole in oil
anagement and otentiality in Nepalese
Agriculture
Shree P Vista , Ananta G Ghimire , Schmidt Hans Peter , Simon Shackley and Bishnu
H Adhikary1
Soil Science Division, (NARC), Khumaltar, Lalitpur, Nepal
Ithaka Institute for Carbon Intelligence
Landell Mills Limited
Abstract
Biochar, the final product of pyrolysis of biomass, can be used as a soil amendment to
increase plant growth, yield, improve water quality, increase soil moisture retention and
availability to plants, reduce soil emissions of greenhouse gases (GHGs), reduce leaching
of nutrients, reduce soil acidity, and reduce irrigation and fertilizer requirements. These
properties of soil are very dependent on the properties of the biochar, and may depend on
site specific ecological conditions including soil type, condition (depleted or healthy),
temperature, and humidity. Biochar can be used in the reclamation of degraded and
spoiled lands (acidic, alkaline, sodic and saline soils).It can sequester massive amounts of
carbon (C) in the soil for hundreds to thousands of years. Originally, biochar was
promoted primarily by the soil community, who were drawn by its remarkable soil eN
hancement properties. Now, however, the significance of the climate change benefits
offered by biochar is becoming the key driver. Biochar is now acknowledged as one of the
main ways of decarbonising the atmosphere. In the developing regions of the world, where
the bulk of the land and the best climatic conditions for biomass production exist, policy
incentives to drive carbon (C) removals may be expected to result in the widespread
adoption of biochar. It has multiple complementary and often synergistic effects on soil
which may motivate biochar applications for environmental management, namely soil
improvement, water and waste management, energy production and climate change
mitigation.
Very recently, biochar has gained its popularity in Nepalese Agricultural Research with
the inception of Biochar Project in Nepal and Soil Science Division (NARC) as an
implementing body of the project, has initiated scientific research in three agro-ecological
zones tested in six different crops. Results of the research can be obtained with different
soil nutrient analysis after completion of the project. Preliminary studies show that there is
tremendous potentiality of biochar production and utilization in Nepalese agriculture.
Keywords: Biochar, degraded and spoiled lands, Nepalese agriculture tremendous
soilpotentiality management.
Background
Production and use of charcoal in everyday life is not a new story in Nepal. Charcoal
production from cooking has been a major feature for thousands of years. The use of
these produced charcoals in the field is not in practice. Charcoal is used by blacksmith
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24-25 March 2015
for heating iron and in common, it was used for cleaning the teeth in past days.
However, with the advancement of science and technology, its use has been widening
and the process of making charcoal has also been coming up with modification. The
placement of charcoal in soils is what we say biochar in recent days. This is only a
practice of application of charcoal in soil with the intention of soil improvement and it
is our ancestral way of life that modern science is trying to understand and
replicate.Biochar is a fine grained charcoal high in organic carbon and highly resistant
to decomposition. It is produced by the thermal decomposition of organic feedstock/
biomass generally known as pyrolysis,generally at low heating rates under oxygen
limited condition. It has significant carbon content, high internal surface area and
adsorption properties. It has high cation exchange capacity, better fertilizer retention
and less field runoff. It also has significant synergisms with soil microbes over time.
Important sector of biochar use
1. As a Soil Amendment
2. Closing nutrient cycles in agriculture (animal farming)
3. Waste water treatment, sewage sludge pyrolysis
4. Remediation of contaminated soils
5. Carbon sequestration
6. Mitigating Climate Change
Biochar and environmental management
There are four complementary and often synergistic objectives which may motivate
biochar applications for environmental management, namely soil improvement, waste
management, energy production and climate change mitigation. They need to have
either a social or a financial benefit, or both and as a result, there are a number of very
different biochar systems of different scales. Originally biochar was promoted
primarily by the soil community, who were drawn by its remarkable soil enhancement
properties. Now however the significance of the climate change benefits offered by
biochar is becoming the key driver. Biochar is now acknowledged as one of the main
ways of decarbonising the atmosphere. There has been much discussion in the press
and the literature regarding the scope for Carbon Capture and Storage – that is
sequestering CO2 gas. The scope for carbon sequestration with biochar however may
be just as significant. In the developing regions of the world, where the bulk of the land
and the best climatic conditions for biomass production exist, policy incentives to drive
Carbon removals may be expected to result in the widespread adoption of biochar soil
improvement based on pyrolysis technologies. The potential role of biochar for the
removal of carbon dioxide (CO2) from the atmosphere and storage in soil of very large
quantities of Carbon appears to lie mainly in developing countries.
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24-25 March 2015
Biochar and the soil
Biochar can be used as a soil amendment to increase plant growth yield, improve water
quality, increase soil moisture retention and availability to plants, reduce soil emissions
of GHGs, reduce leaching of nutrients, reduce soil acidity, and reduce irrigation and
fertilizer requirements. These properties are very dependent on the properties of the
biochar, and may depend on regional conditions including soil type, condition
(depleted or healthy), temperature, and humidity. Modest additions of biochar to soil
were found to reduce N2O emissions by up to 80% and completely suppress methane
emissions. Conservation of energy is achieved through the avoidance of energy
incurred in the production of excess fertilizers. Biochar can be used in the reclamation
of degraded and spoiled lands (Acidic and Alkaline soils).
Biochar and Nepal
Research on biochar production and its use in agricultural soil is very limited in Nepal.
Very recently, this concept has been gaining importance and popularity. However, only
few projects in biochar are running in Nepal and there has been a rapid change in the
concepts of biochar use. Earlier, biochar itself was considered as a substitute of
fertilizer and now it has been commonly agreed that it is just a carrier of the nutrients.
Use of only biochar in soil did not improve crop yield, it locked the nutrients and
therefore, in recent years, mixing of nutrients with biochar has become a practice.
Biochar Research in NARC
Very recently, biochar has gained its popularity in Nepalese agricultural research with
the inception of Biochar Project in Nepal and NARC as an implementing body of the
project, has initiated scientific research in three agro-ecological zones tested in six
different crops. Biochar was prepared with three different kilns using different
feedstock in four locations and with six crops. In Hill Crop Research Program, barley
and potato were grown using biochar at 4t ha-1 and with seven different treatments.
This research represents mid hills condition and for terai condition, research was
carried out at RARS, Parwanipur. Onion and maize were grown with seven different
treatments. Similarly, one more trial was conducted in sugarcane crop at SRP, Jitpur.
To represent foothills, another trial was carried out at Spice Development Center,
Panchkhal with ginger crop. All the treatments were replicated five times. One hundred
and ten farmers field trial were also carried out side by side to know their perception on
biochar. Soil Science Division as a implementing body of the research trial has also
started doing some basic research on biochar in green house condition. Pot culture with
tomato is undergoing with eight different treatments and five replications. Intensive
study is on the way with biochar to test its potentiality in Nepalese agriculture. Results
of the research can be obtained with different soil nutrient analysis after completion of
the project. Preliminary studies show that there is tremendous potentiality of biochar
production and utilization in Nepalese agriculture. Farmers involved in field trial are
giving positive response to biochar application.
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24-25 March 2015
Some recommendations
Though biochar research in NARC is still in preliminary stage, however following
points have come up while working in biochar as way forward.
1.
Study and assess the nature of the local feedstocks and based on it develop a
National Biomass Resource Atlas.
2.
Different pyrolysis stove designs could then be tested to establish the optimum
solutions in the different agroecological zones.
3.
Determination of the optimum way of accounting for, and being credited for the
carbon sequestration in the soil.
4.
Dose of biochar with respect to location, soil types and climatic variation is a
must in near future.
Reference: (Not provided)
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24-25 March 2015
SF-18
Effect of Organic Matter and Iron Slime on Changes in Soil Properties
S
P Vista1 and Dipankar Saha2
1
2
Soil Science Division (NARC), Khumaltar, Nepal
Department of Agricultural Chemistry and Soil Science, BCKV, West Bengal, India
Abstract
Iron-ore-slime is the waste product of iron and steel industries which has the particle size
of below 15µm and is being discarded as waste during the mining and processing stages
to
of iron ore. Laboratory incubation experiment was conducted in the laboratory
investigate the effect of organic matter (OM) on soil physico-chemical properties
amended with iron- slime with four different treatments replicated four times. Results of
characterization study of iron-slime revealed that it is neutral in reaction, contains
considerable amount of available plant nutrients and is fairly good enough its fertility
status. Addition of iron-slime influenced soil reaction in maintaining towards neutrality
as that of organic matter. Iron- slime has proved to have more or less similar effect like
- EC and organic
that of organic matter (OM). Addition of iron-slime improved pH,
carbon (OC) content of the soil. Combined application of iron-slime and organic matter
increased organic carbon in soil. Application of organic matter increased the amount of
available N, total N, available P and available K in soil. Use of iron-slime with organic
matter resulted better availability of these nutrients in soil.
Keywords:
Better availability, iron-slime, organic matter, physico-chemical
properties
Iron ore slime is the waste product of iron and steel industries which has the particle
size of below 150µm and is being discarded as waste during the mining and processing
stages of iron ore and it will be stored at the tailing dam. It is estimated that 15% - 20%
of tailing will be generated during the processing of iron ore. The major compositions
of iron ore slime are hematite, quartz, alumina, mica and kaolin. The iron ore slime is
discarded due to its particle size and chemical composition which are not suitable to
feed the blast furnace. Although the fines can be sintered to larger particle, the alumina
to silica ratio which is normally more than one pose serious problem during sintering
process and subsequent smelting in blast furnace. The alumina content in the slime
needs to be reduced in order for it to be used as the feed for blast furnace. On the other
hand, the concept of value adding the industrial waste into value added product has
received considerable attention recently. Among the product that can be developed
through beneficiation of this waste are feed for blast furnace, ceramic tile floor, wall
tile body, additional material to cement raw mix, glass ceramics and soil modifier
(www.tatasteel.com).
India ranks fourth largest producer of iron ore in the world with more than 25 billion
tonnes (IBM, Nagpur). The current practice of washing of iron ore in India results in
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24-25 March 2015
the generation of huge quantity of tailings (around 14 million tonnes per year). For the
production of one ton of steel, about 200 to 400 kg of by-products is liberated during
processing of iron ore mines. Globally, about 400 million tons of these by- products are
generated annually. India alone produces about 14 million tons of by- products of
which 15-20% is iron slime (www.worldsteel.com).
The relevant physical, chemical and physico-chemical properties of the said iron slime
are pH 7.2, moisture holding capacity 33.40%, particle density 2.78 g/cc, bulk density
1.45 g/cc, electrical conductivity 0.164 dSm-1, Cation exchange capacity1.86 cmol (P+)
kg-1, Organic carbon 0.08%, Total Nitrogen 0.027%, exchangeable NH4 167.93 mg
kg-1, soluble nitrate 32.00 mg kg-1, available K2O 60 kg ha-1 and available P 28.40 mg
kg-1(Vista, 2014). Based on the test report, it appears that the iron slime may act as one
of the agricultural inputs in soil health and nutrients as well.
In the present study, the utilization of iron ore fines and slimes has been dealt with.
Various proportions of iron slime are amended to soil and its changes on chemical,
physical and physico-chemical properties of soil have been studied. Experimental
findings based on laboratory experiment are discussed in detail.
Objectives of the investigation
Researchers are on the work for successful utilization of the iron slime by converting it
to value added products like building materials as mentioned. However, till date, the
prospect of utilization of the slime for agricultural purposes particularly with respect to
qualitative improvement of soil has not been studied. It is evident that iron slime might
be exhibited problem for growing any type of crop on it because of its composition not
conducive for crop establishment. Therefore, the present study is being undertaken for
its effective utilization in agricultural sector with the following objective to improve
the soil conditions with respect to physical, chemical and physico-chemical attributes
amended with iron slime
Laboratory incubation experiment was conducted in the laboratory to investigate the
effect of organic matter on soil physico-chemical properties amended with iron slime.
Soil sample was collected (0-15 cm depth) from the Instructional farm of Jaguli,
Bidhan Chandra Krishi Viswavidyalaya main campus (22.930N latitude and 88.530 E
longitudes), Mohanpur, Nadia, West Bengal. Collected soil sample was air dried,
ground with a wooden pestle and mortar, sieved through nylon sieve (80 mesh) and
carefully preserved in the laboratory to avoid any contamination. Relevant physical and
chemical properties of the soil are presented in Table 2.
Methods followed
Physical analysis
Bulk density, particle density and water holding capacity of the soil was determined by
Keen (Rackzowski) box technique as described by Baruah and Barthakur (1997).
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24-25 March 2015
Mechanical Analysis
Mechanical analysis of the soil samples was done by Hydrometer method (Bouyoucos
1927) as described by Black (1965).
Physico-chemical analysis
The pH of the soil was determined with the help of a pH meter in 1:2.5 soil: water
suspension ratio. The electrical conductivity of the soil was determined at the room
temperature in a soil water suspension ratio of 1:2.5 with the help of conductive
bridge.The CEC of the soil was determined by the method of ammonia saturation
(Black, 1965).
Chemical analysis
Total N content of the soil was determined by modified Kjeldahl method.
Exchangeable NH4+ and soluble NO3-, together termed as available N, were estimated
according to the method developed by Bremner and Keeney (1966). Organic carbon
content of the soil was estimated by following the method suggested by Walkley and
Black. Available P was extracted from soil with Olsen’s extractant (0.5M sodium
bicarbonate) and analyzed calorimetrically (Jackson 1973). Available K content of the
soil was determined by flame photometer after extraction with neutral one normal
ammonium acetate solution as described by Jackson (1973).
Experimentation
The incubation study was conducted in the laboratory with the following experimental
set up.
Amount of soil/iron slime per pot
:
Five kg
Period of incubation
:
Ninety days
Number of treatments
:
Four
Number of replications
:
Four
Sampling stages
:
30th, 60th and 90th day of incubation
Treatments adopted
In order to ascertain the effect of mixing iron slime with soil at different proportion and
in different combinations in presence and absence of added organic matter, the
following treatment combinations were followed.
Table 1: Treatments used in the experiment.
Treatments
Details
T1
Soil
T2
Soil + iron slime (1:1)
T3
Soil + Organic matter (1%)
T4
Soil + iron slime (1:1) +Organic matter (1%)
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24-25 March 2015
Practically no research work has been carried out to use iron slime for agricultural
purposes. Most often, research thrust was put in engineering perspectives. Iron slime
samples were collected from Tata Steel Limited, Jamshedpur for the study. The
collected iron slime samples were brought to laboratory and characterised in the
Department of Agricultural Chemistry and Soil Science, Bidhan Chandra Krishi
Viswavidyalaya. Some important physical and chemical characteristics of the iron
slimes are summarized below:
Table 2: Physical, chemical and physico –chemical properties of Iron Slimes used
for the experiments.
S. Parameters
Iron Slime- I
Iron Slime- II
No
1
pH
7.44
6.90
2
EC (dSm-1)
0.164
0.580
3
Max. Water Holding Capacity (%)
53.35
56.39
+
4
Cation Exchange Capacity (Cmol p kg 4.32
6.44
1
)
5
Organic Carbon (%)
0.08
0.357
6
Total Nitrogen (%)
0.027
0.029
7
Exchangeable ammonium (mg kg-1)
112.00
138.00
8
Soluble Nitrate (mg kg-1)
44.80
47.50
1
9
Available Nitrogen (mg kg- )
156.80
185.50
10 Available Phosphorus (mg kg-1)
4.50
112.50
11 Available Potassium (mg kg-1)
15.40
97.30
12 Available iron (mg kg-1)
158.98
85.00
13 Available Cu (mg kg-1)
12.02
2.24
14 Available Zn (mg kg-1)
58.60
17.08
1
15 Available Mn (mg kg- )
5.75
15.64
The iron slime-I is neutral in reaction (Table 2). Results further showed that the
amount of total N, available N, exchangeable ammonium, available K and available P
are recorded as 0.027%, 156.8 (mg kg-1), 112 (mg kg-1), 15.4 (mg kg-1) and 4.5 (mg kg1
), respectively. Low organic carbon content (0.08 %) and CEC (4.5 Cmol (p+) kg-1)
reveal that the supplied iron slime- I material, a by-product of Tata Steel Ltd, is fairly
good enough with respect of its fertility status where agricultural crops can be grown
successfully with some sorts of appropriate management practices.
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24-25 March 2015
Table 3: Effect of organic matter on changes in pH in soil amended with and without
iron slime.
Treatments
Incubation Period, days
30
60
90
Mean
Soil
7.67
7.61
7.69
7.64
Soil+ Iron Slime
7.51
7.89
7.79
7.73
Soil+ Organic matter
7.58
7.95
7.61
7.71
Soil+ Iron Slime +Organic Matter
7.80
7.79
7.75
7.78
Mean
7.64
7.81
7.71
Statistical Analysis
Treatments
Incubation
Treatments X Incubation
SEm
CD (p=0.05) SEm (±)
CD (p=0.05)
SEm (±)
CD
(±)
(p=0.05)
0.0009 0.0025
0.00075
0.0022
0.0015
0.0044
Changes in pH in soil amended with or without iron slime due to addition of organic
matter is presented in Table 3. Irrespective of treatments, in general, pH of the soil
increased over 90 day period of incubation (Table 3). Combined application of organic
matter and iron slime maintained soil pH neutral over 30 day of incubation. The
increase in pH of the soil due to addition of iron slime is due to higher pH of the iron
slime (Table 2). The slight increase in pH might be due to the soil moisture as well as
reduction of iron and manganese (Das, 2011). The pH differs significantly with the
treatments. The addition of iron slime increased soil pH significantly upto 60 days and
then showed a slight decreasing trend upto 90th day of incubation. The results thus
showed that iron slime influences soil reaction in maintaining towards neutrality as that
of organic matter.
Table 4: Effect of organic matter on the changes in EC (dSm-1) of soil amended with
and without iron slime.
Treatments
30
60
90
Mean
Soil
0.140
0.185
0.182
0.169
Soil+ Iron Slime
0.209
0.201
0.192
0.201
0.195
0.190
0.188
0.192
0.152
0.219
0.196
0.189
Mean
0.174
0.199
0.189
Treatments
Incubation
Treatments X Incubation
SEm
CD (p=0.05)
SEm (±)
CD (p=0.05)
SEm (±)
CD (p=0.05)
(±)
0.0006 0.0018
0.00053
0.00155
0.00105
0.00309
Changes in EC in soil amended with or without iron slime due to addition of organic
matter is presented in Table 4. Statistical analysis of the results revealed that electrical
conductivity differs significantly with the treatments, period of incubation as well as
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24-25 March 2015
interaction of treatments and incubation. A gradual decreasing trend of EC was
observed in both the slime and organic matter treated soil over the initial stage till the
end of the experiment. This shows that iron slime has more or less similar effect like
that of organic matter in influencing electrical conductivity.
Results in Table 4 revealed that irrespective of treatments, electrical conductivity of the
soil decreased except iron slime treated system over 90 day period of incubation.
Critical analysis of the results showed that soil treated with iron slime resulted highest
electrical conductivity on 30th day of experiment. Slight increase of EC of the soil
amended with iron slime might be due to the release of soluble salts (Das, 2011).
Addition of iron slime improves the EC value of the soil.
Table 5:Effect of organic matter on the changes in OC content (%) of soil amended
with and without iron slime.
Treatments
Soil
Soil+ Iron Slime
Mean
Treatments
Incubation
SEm CD (p=0.05)
SEm (±)
(±)
0.00 0.0083
0.00348
4
30
60
90
0.79
0.88
0.89
1.00
1.21
1.29
1.10
1.29
1.35
1.40
1.35
1.39
1.07
1.18
1.23
Mean
0.85
1.17
1.25
1.38
CD (p=0.05)
Treatment X Incubation
SEm (±)
CD(p=0.05)
0.00722
0.007
0.0144
Changes in the amount of organic carbon in soil amended with or without iron slime
due to addition of organic matter is presented in Table 5. Data in Table 5 revealed that
combined application of iron slime and organic matter increased organic carbon
content in soil compared to single application of either iron slime or organic matter.
The result thus suggests that iron slime has some favourable characteristics for binding
organic carbon in the iron slime matrices. The treatments and the period of incubation
differ significantly with each other. The interaction of treatments and incubation was
also highly significant. Results further showed that irrespective of treatments, the
organic carbon content increases with the increase in period of incubation. The slight
increase in organic carbon content in soil amended with iron slime might be due to the
reduction of soil resulting decomposition of organic matter due to the soil moisture.
Further enhancement of organic carbon content in soils amended with both iron slime
and organic matter might be due to additive effect of organic matter causing a greater
magnitude of organic carbon content (Das 2011). Therefore, iron slime has some
positive effects just similar to that of organic matter in improving properties of soil.
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24-25 March 2015
Results of the effect of organic matter on changes in the amount of available N in soil
amended with and without iron slime are presented in Table 6 and Figure 1. The result
(Table 6) shows that the amount of available N was found to increase with the
application of organic matter. Although a higher amount of available N was recorded
in soil+ organic matter treatment but the highest value was recorded in soil+ iron slime
+ organic matter treated system. It may therefore be concluded that the use of iron
slime mixing with normal soil and organic matter may be beneficial in enhancing soil
fertility and in turn crop production.
Table 6:Effect of organic matter on the changes in the amount of available N (mg kg-1)
in soil amended with and without iron slime.
Treatments
Soil
30
60
90
46.0
41.0
40.0
Soil + Iron slime (1:1)
Soil+ Iron Slime (1:1) +Organic Matter
Mean
39.0
51.0
69.0
51.2
37.0
49.0
61.0
47.0
36.0
46.0
57.0
45.6
Mean
43.4
37.3
48.7
62.3
Treatments
SEm (±)
0.000056
Incubation
CD (p=0.05)
0.0002
SEm (±)
0.0000481
CD (p=0.05)
0.0001411
SEm (±)
0.0000962
CD (p=0.05)
0.0003
Available N (mg kg-1)
Effect of organic matter on the changes in the
amount of available N (mg kg-1) in soil amended
with and without iron slime
80
60
40
20
0
30 day
Soil
Soil+ Iron Soil+ Organic Soil+ Iron
Slime
matter
Slime
+Organic
Matter
60 Day
90 Day
Treatments
Figure 1: Effect of organic matter on the changes in the amount of available
N (mg kg-1) in soil amended with and without iron slime.
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24-25 March 2015
Results of the effect of organic matter on changes in the amount of total N in soil
amended with and without iron slime are presented in Table 7 and Figure 2. Results
presented in Table 7 showed that the amount of total N increased with the application
of organic matter. Although a higher amount of total N is recorded in soil+ organic
matter treatment but the highest value is recorded with soil+ iron slime + organic
matter treated system. The result thus pointed out that mixing of iron slime with
normal soil and organic matter is beneficial in enhancing soil fertility.
Table : Effect of Organic matter on the changes in the amount of total N (%) in soil
amended with and without iron slime.
Treatments
30
60
0.044
0.045
0.050
0.054
0.047
0.048
Soil
Soil+ Iron Slime
0.050
Mean
0.050
Treatments
Incubation
0.059
0.050
90
0.043
0.058
0.049
Mean
0.040
0.050
0.050
0.062
0.050
0.060
SEm (±)
CD (p=0.05)
SEm (±)
CD (p=0.05)
SEm (±)
0.0001
0.0037
0.0001
0.00312
0.0002
CD
(p=0.05)
0.0062
Results of the effect of organic matter on changes in the amount of total P in soil
amended with and without iron slime are presented in Table 8 and Figure 3. The
amount of total P increased with the application of organic matter (Table 8). Although
a higher amount of total P is recorded in soil+ organic matter treatment but the highest
value is observed in soil+ iron slime + organic matter treated system. Results thus
further pointed out that use of iron slime with normal soil and organic matter enhanced
P content in soil.
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24-25 March 2015
Total N (%)
Effect of organic matter on the changes in the
amount of total N (%) in soil amended with and
without iron slime
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
30 day
60 Day
Soil
Soil+ Organic
matter
Soil+ Iron
Slime
Soil+ Iron
Slime
+Organic
Matter
90 Day
Treatments
Figure 2: Effect of organic matter on the changes in the amount of total N (%) in soil
Table 8: Effect of organic matter on the changes in the amount of total phosphorus
(%) in soil amended with and without iron slime
Treatments
Soil
30
0.061
60
0.065
90
0.064
Mean
0.060
0.072
0.077
0.079
0.080
Soil+ Iron Slime
0.075
0.078
0.077
0.080
0.090
0.098
0.097
0.100
Mean
0.070
0.080
0.080
Treatments
Incubation
SEm (±)
CD (p=0.05)
SEm (±)
CD (p=0.05)
SEm (±)
CD (p=0.05)
0.0005
0.0074
0.00038
0.0068
0.0008
0.0136
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24-25 March 2015
Total P (%)
Effect of organic matter on the changes in the amount of
total phosphorus (%) in soil amended with and without
iron slime
0.12
0.1
0.08
0.06
0.04
0.02
0
30 day
Soil
Soil+ Organic
matter
Soil+ Iron
Slime
Soil+ Iron
Slime
+Organic
Matter
60 Day
90 Day
Treatments
Figure 3: Effect of organic matter on the changes in the amount of total phosphorus
(%) in soil amended with and without iron slime.
Results of the effect of organic matter on changes in the amount of available K in soil
amended with and without iron slime are presented in Table 9 and Figure 4. Data in
Table 9 showed that the amount of available K increased with the application of
organic matter. Again, although the amount of available K is of higher order in soil+
organic matter treatment but the highest value is recorded in soil+ iron slime + organic
matter treatment. The results thus lead to conclude that the use of iron slime with
normal soil and organic matter improves soil fertility.
Table 9: Effect of organic matter on the changes in the amount of available potassium
(mg kg-1) in soil amended with and without iron slime.
Treatments
Soil
30
43.70
60
39.26
90
38.76
Mean
40.57
48.00
45.42
44.89
46.10
Soil+ Iron Slime
50.30
48.74
47.73
48.92
50.90
49.63
48.32
49.62
Mean
48.23
45.76
44.92
Treatments
Incubation
SEm (±)
CD (p=0.05)
SEm (±)
CD (p=0.05)
SEm (±)
CD (p=0.05)
0.0048
0.0134
0.0042
0.0127
0.0084
0.0254
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24-25 March 2015
Effect of organic matter on the changes in available K
(mg kg-1) in soil amended with and without iron slime
Available K (mg kg-1
60
50
40
30
30 day
20
60 day
10
90 day
0
Soil
Soil+ Organic
matter
Soil+ Iron
Slime
Soil+ Iron
Slime +Organic
Matter
Treatments
Figure 4: Effect of organic matter on the changes in available K (mg kg-1) in soil
Conclusion
A completely new venture on utilisation of iron slimes for agricultural purposes was
taken up to explore its utility. The results of the experiment conducted to investigate
the effect of iron slime on physical, chemical and physico-chemical properties of soil
are point wise summarised below.
1.
2.
3.
Characterisation study of iron slime revealed that it is neutral in reaction,
contains considerable amount of available plant nutrients and is fairly good
enough with its fertility status. Therefore, it is concluded this material can be
utilised in soil to grow rice and cabbage without any adverse effect on these
crops at any growth stage.
Addition of iron slime influences soil reaction in maintaining towards
neutrality as that of organic matter. Iron slime has proved to have more or less
similar effect like that of organic matter. Addition of iron slime improves pH,
EC and organic carbon content of the soil. Combined application of iron slime
and organic matter increased organic carbon in soil.
Application of organic matter increased the amount of available N, total N,
available P and available K in soil. Use of iron slime with organic matter
resulted better availability of these nutrients in soil.
188
24-25 March 2015
Reference:
Baruah, T.C. and Barthakur, H.P. (1997). A Textbook of Soil Analysis.Vikas
Publishing House Pvt. Ltd. New Delhi.
Black, C.A. (Ed.) (1965). Methods of Soil Analysis. Part I and II. American Society of
Agronomy, Inc., Publishers, Madison, Wisconsin, USA.
Bouyoucos, G.J. (1927). The hydrometer as a new method for the mechanical analysis
of soils. Soil Sci.23: 343-353.
Bremner, J. M. and Keeny, D. R. (1966). Determination of exchangeable ammonium
nitrate and nitrite by extraction distillation methods. Soils Sci. Soc. Am. Proc.,
30 : 577-587.
Das, D.K. (2011). Introductory Soil Science. Kalyani Publishers.
GenStat Discovery Edition 4, Copyright 2011, VSN International Ltd. (Rothamsted
Experimental Station) viewed at http://discovery.genstat.co.uk.
http//www.ibm.nagpur
http//www.tatasteel.com
http//www.worldsteel.com
Jackson, M. L. (1973). Soil Chemical Analysis, Prentice Hall of India Pvt. Ltd., New
Delhi.
Vista, Shree Prasad (2014). Utilisation of Iron Slime for Agricultural Purposes. A
Thesis submitted to Bidhan Chandra Krishi Viswavidyalaya, Mohanpur,
Nadia, West Bengal in partial fulfillment of the requirements for the award of
degree of Doctor of Philosophy in Agricultural Chemistry and Soil Science,
2014.
World Steel Association, 2010. (n.d.) Available from http://www.worldsteel.org
189
24-25 March 2015
SF-19
Efficacy of Fertilization Levels and Genotypes on the Grain Yield of
Winter Maize (Zea mays L.) in the Acidic Soils of Chitwan Valley
Bishnu H Adhikary1, Bandhu R Baral2, Jiban Shrestha2 and
Robinson Adhikary3
1
Soil Science Division (NARC),NARI, Khumaltar, Lalitpur, Nepal
National Maize Research Program (NARC), Rampur, Chitwan, Nepal
3
Institute of Agriculture and Animal Science (IAAS), Lamjung Campus, Tribhuvan University,
Lamjung, Nepal
2
Abstract
Maize crop is one of the heavy feeder of plant nutrients. Different varieties of maize (Zea
mays L.) have different potentiality and requirements of plant nutrients. Hybrids require
high dose of mineral fertilizers and manures as compared to those of open pollinated
improved varieties (OPV) and the locals. In order to investigate the effects of different
rates of fertilizers (nitrogen, phosphorus, potassic fertilizers) and farmyard manures on
grain yield and yield attributing traits of different maize varieties, field experiments were
conducted at the farm of National Maize Research Program, Rampur, Chitwan, Nepal
during winter seasons of 2009/10 and 2010/011 employing randomized complete block
design with three replications. Five levels of fertilization; Control (zero fertilizer), Farm
yard manure (FYM) 10 t ha-1 60:30:20 N, P2O5 and K2O plus FYM 10 t ha-1, 120: 60: 40
N, P2O5 and K2O plus FYM 10 t ha-1, 180: 90: 60 N, P2O5 and K2O kg ha-1plus FYM 10
t ha-1 and 120: 60: 40 N, P2O5 and K2O kg ha-1 were applied to four maize varieties
(Rampur Composite, Manakamana-4, Across9942 × Across 9944 and S99TLYQ-B) in the
experiments. The results of the experiments showed that grain yield was non-significant
for maize genotypes but the fertilization rates were highly significant for grain yield.
Rampur Composite produced the highest grain yield (5195 kg ha-1), followed by
Manakamana-4 (5074 kg ha-1), Across9942 × Across9944 (5052 kg ha-1) and S99TLYQ-B
(4789 kg ha-1) with application of N, P2O5 and K2O at 180: 90: 60 kg ha-1 plus FYM 10
t ha-1. The information obtained from these experiments might be useful in generating
suitable fertilization packages for obtaining higher grain yield of winter maize varieties.
Key words: Fertilizer and manures, grain yield, maize genotypes, yield attributing traits.
Introduction
Maize (Zea mays L.) has the highest productivity per unit area as compared to other
cereal crops. It ranked third among the cereal crops in the world after wheat and rice.
In Nepal, it is the second most important staple food crop in terms of both area and
production after rice but it is the first staple crop for hills. In Nepal, it is the food for
more than 14 million people in the hills and is playing a vital role in the livelihood of
rural people in Nepal. It is used for food and feeds, fodder, and fuel. More than 87%
maize production is used for direct human consumption; 12% for poultry and animal
feeds and 1% is for different purposes. Maize is highly nutritive and its seed contains;
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24-25 March 2015
78% starch,10 % protein, 4.8 % oil, 8.5 % fibre, 3.1 % sugar and 1.7 % ash
(Chaudhary, 1983).
The productivity of maize in Nepal is very low (2.2 t ha-1) as compared to the world
average of 4.3 t ha-1 (Joshy 1997). It can be improved or increased through adequate
nutrient management practices. Inappropriate crop nutrition management and poor soil
fertility are the most important factors responsible for the low yield in Nepal. Soil
fertility can be enhanced through the application of mineral fertilizers as well as with
the addition of organic matter to the soil. The judicious management of fertilization
must attempt to ensure both an enhanced and safeguarded environment. Manures and
fertilizers both play important role in the maize cultivation. Hybrids and composite
varieties exhibit their full yield potential only when supplied with adequate quantities
of nutrients at proper time. Requirement of nutrients by hybrids is the higher because
of its greater potentiality for grain production. Growing local material at a high nutrient
level need not result in higher grain yield. But on the contrary, a high level of nutrients
for hybrids and composites proves beneficial. N is usually applied in 3 equal splits at
sowing, knee high stage and tasseling stage. Nitrogen level in the range of 100-120
kg/ha is applied with a view to obtain 4-5 t ha-1 of grain yields and likewise, it can be
reduced or increased as per its expected yield. Phosphorus (P) is the next most
important plant nutrient after N which is found difficult in most soils. It has beneficial
effect on root growth and plant health. This nutrient should be applied initially at the
early stage because of its low solubility in water. It should be applied in moist zone to
be transformed quickly for early absorption by plant. The dose of phosphorus (P)
should be balanced with the dose of N applied. Potassium (K) is considered to be the
3rd most essential fertilizer element, it is not found deficient in most of the soils. It is
essential for vigorous growth of the plant and for so many other metabolic activities.
Placement of 30-40 kg ha-1 of K2O is generally found adequate; however, this can be
increased with increased rate of nitrogen (N) to balance the nutrient status of soil for
better uptake of total essential nutrients (Dayanand 2002).
Potassium (K) application through fertilizers has been responding satisfactorily (Regmi
et al. 2002). Maize being a high nutrient mining crop it needs higher amount of NPK
for its economic production. Farmers applying 20-25 t ha-1 of compost/FYM (manures)
are not sufficient to replenish the harvested nutrients and hence need sufficient amount
of mineral fertilizers addition with heavy manure application (Joshy 1997). Adhikary et
al. (2001) reported that the highest maize grain yield (4.65 t ha-1) could be obtained
when the crop is fertilized by 20 t of compost plus 100: 75: 40 kg ha-1 of N: P2O5 : K2O
in the acidic soils of Malepatan, Pokhara. Adhikary and Ranabhat (2004a) studied the
economics of manures and fertilizer application on maize production and concluded
that most economic dose of fertilizer was 100: 75 : 40 kg ha-1 N:P2O5 : K2O from
inorganic sources and 20 t ha-1 of compost that contained 280 kg N, 184 kg P2O5 and
216 kg K2O. Similarly, Adhikary et al. (2004b) reported the efficacy of nitrogen (N)
rates on maize planted at varying densities at Rampur condition. Adhikary et al.
(2007) studied the effect of fertilizer and agricultural lime on grain yield of different
maize genotypes in the Western hills of Nepal and reported that improved maize
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24-25 March 2015
variety (Manakamana-1) did not differ in grain production with the local variety when
supplied with fertilizers at 60: 30: 30 kg N:P2O5 : K2O ha-1 and 4 t ha-1 of agri-lime.
Adhikary (2008) also studied the effects of nitrogen on maize inbred (NML-1) and
reported that grain yield (2.9 t ha-1) was obtained when supplied with 180 kg N and
crop planted at the density of 66,666 plants ha-1 and crop fertilized along with the
recommended dose of P and K fertilizers. Adhikary et al. (2010) reported that
application of 180:90:60 kg N: P2O5 : K2O ha-1 produced the highest grain yield (7.4
t ha-1) by the Rampur Composite variety when applied along with 10 t ha-1 of compost
in Chitwan Valley soil. Series of experiments were conducted to evaluate the effects of
fertilizers on different maize genotypes during the years 2009/10 and 2010/11. The
results revealed that the highest grain yield of 6.3 t ha-1 was produced by the
S99TLYQ-B when the crop was fertilized with 120: 60: 40 kg N: P2O5:K2O ha-1 and 10
t ha-1 of compost (NMRP 2006, NMRP 2010). Hence, balanced dose of fertilizers are
needed to increase the crop yield of maize in acid soils. The amount of fertilizers to be
applied in maize depends largely on genotypic makeup of plants.
The objective of this experiment was to study the response of fertilizer nutrients at
different levels on the different maize genotypes in the soil condition of Rampur,
Chitwan, Nepal.
Materials and Method
The experiment was conducted at the farm of National Maize Research Program,
Rampur, Chitwan, Nepal during the winter season of the year 2009/10 and
2010/11.The site was located in central Nepal at 27° 40’ N latitude and 84° 19’ E
longitude with an elevation of 228 m above mean sea level and had a sub tropical
climate (NMRP 2010).
Maize was planted on sandy silt loam, acidic soil (pH 5.5). Fertilizer was applied in the
form of Urea, di-amonium phosphate (DAP), and murate of potash (MoP). Entire dose
of DAP and MoP was applied at the time of sowing while half of urea was first top
dressed at knee high stage and second top dressed at tasseling stage. The average data
derived from both years on maximum temperature ranged from 21.95 (January) to
36.35 0C (April), the minimum temperature varied from 9.4 (January) to 24.65 0C
(October). There is no rainfall in November and January, minimum rainfall (1.1 mm)
occurred in January and maximum rainfall occurred in 99.35 mm (April). Similarly,
average data on relative humidity showed that minimum humidity (76.8%) occurred in
April and maximum relative humidity (99%) was occurred in December. The details of
weather data of individual year was shown in Table 2.
The crop was planted in October and harvested in April. Twenty four treatment
combinations consisting of six levels of fertilization and four maize genotypes were
replicated three times and laid out in a Randomized Complete Block Design (RCBD).
The details of the treatment combinations are given in Table 1. Row to row spacing 75
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24-25 March 2015
× 25 cm was maintained. The net harvested area was 7.2 sq. m. The gross plot size was
12 sq.m.
At maturity central two rows from each plot were separately harvested and the fresh
ear weight was measured in each plot. Grains were shelled from five randomly selected
cobs to observe the percent grain moisture at harvest for each plot. Thousand grain
weight and grain yield were recorded at 15% moisture level.
Table 1: The details of the treatments used in experiment in 2009/10 and 2010/11
winter seasons at Rampur, Chitwan, Nepal.
Genotypes
V1= Rampur Composite
V2= Manakamana-4
V3=Across9942 x Across9944
V4= S99TLYQ-B
Fertilizer rates
F1=Control (zero fertilizer)
F2= FYM @ 10 t ha-1
F3= FYM @ 10 t ha-1 plus 60:30 20 kg ha-1 of N:2O5 : K2O
F4=FYM @ 10 t ha-1 plus 120: 60: 40 kg ha-1 of N: P2O5 :
K2O.
F5=FYM @ 10 t ha-1 plus 180: 90: 60 kg of N:P2O5: K2O .
F6= 120: 60: 40 kg ha-1 of N:P2O5 : K2O.
Table 2: Monthly mean weather condition during crop growing season (OctoberApril) in2009/10 and 2010/11 winter seasons at Rampur, Chitwan, Nepal.
Month
October
November
December
January
February
March
April
Maximum
temperature, 0C
2009/10
31.4
27.1
24.0
20.0
25.4
33.1
38.1
2010/11
31.4
27.1
24.0
23.9
26.1
31.1
34.6
Minimum
temperature,0C
2009/10
26.5
21.6
16.0
10.3
11.9
19.1
23.3
2010/11
22.8
17.0
9.1
8.5
15.1
18.9
19.6
Rainfall, mm
2009/10
101
0.0
2.2
0.0
0.0
0.0
165
2010/11
48.6
0.0
0.0
0.0
34.9
34.4
33.7
Relative humidity,
%
2009/10
97.0
99.0
99.0
94.6
89.5
82.2
75.4
2010/11
97.5
98.8
99.0
100.5
96.3
83.2
78.2
Source: (NMRP, 2010/11)
Observations were taken on plant height, ear height, cob length, no. of Kernel rows per
cob, no. of kernels per rows, and grain yield. Plant height and ear height was recorded
at just near to harvesting and rest of data were recorded after harvesting. All these
parameters were statistically analyzed. Analysis of variance for all data was analyzed
using MSTAT computer program.
The interaction between different fertilizer levels and varieties on grain yield showed
that the highest grain yield (5195 kg ha-1) was obtained in Rampur Composite followed
by Manakamana-4 (5074 kg ha-1) and Across9942 × Across 9944 (5052 kg ha-1) with
the application of 180: 90: 60 kg N: P2O5:K2O ha-1 plus FYM 10 t ha-1. Similarly,
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24-25 March 2015
S99TLYQ-B produced the second highest grain yield (4789 kg ha-1) in the same level
of fertilization (Figure 1).
2000
4789
4210
2105
3002
3940
4560
2920
3000
1959
Grain yield (GY), kg/ha
2152
2960
4000
4077
4910
5052
4530
5000
1732
2657
6000
4337
4899
5074
4260
3944
4852
5195
4682
7000
1000
0
V1F1 V1F3 V1F5 V2F1 V2F3 V2F5 V3F1 V3F3 V3F5 V4F1 V4F3 V4F5
GY, 2009/10
Fertilization:non significant
Varieties: Highly significant
F x V:Non significant
GY, 2010/11
Figure 1: Effect of different level of manures and fertilizers and different maize
genotypes on maizegrain production in 2009/10 and 2010/11 winter seasons
at Rampur, Chitwan, Nepal.
The highest yield attributing traits namely cob length, no. of kernel rows per cob and
no. of kernels per kernel rows were found in 180:90:60 kg N:P2O5 : K2O plus 10 t ha-1
of FYM in Rampur Composite, Manakamana-4, Across 9942 × Across 9944. The
interaction effect between genotypes and fertilizers was not obtained
F1
F2
F3
F4
F5
F6
5000
4000
Variety
V1
V2
V3
V4
3000
2000
5000
F ertilizers
F1
F2
F3
F4
F5
F6
4000
3000
2000
V1
V2
V3
V4
Figure2: Schematic diagram for interaction effect between maize genotypes and
fertilizer levels at Chitwan valley soils.
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24-25 March 2015
Table 3:
Treat
ments
V1F1
V1F2
V1F3
V1F4
V1F5
V1F6
V2F1
V2F2
V2F3
V2F4
V2F5
V2F6
V3F1
V3F2
V3F3
V3F4
V3F5
V3F6
V4F1
V4F2
V4F3
V4F4
V4F5
V4F6
Grand
mean
CV, %
F-test
(V)
(F)
(V ×
F)
LSD0.0
5
Effect of different level of manures and fertilizers on different maize
genotypes in 2009/10 and 2010/11 winter seasons at Rampur, Chitwan,
Nepal.
Cob length,
Kernel rows per
Kernels
Grain yield,
cm
cob, nos.
per kernel
kg ha-1
row, nos.
2009/
2009/1 2010/1 2009/10
2010/ 2009/10 2010/
10 2010/11
0
1
11
11
11.4
9.6
10.7
10.4
22.6
14.9
2860
1443
12.2
11.6
12.0
11.9
24.2
17.5
3740
2180
13.8
14.1
12.8
13.6
31.1
28.3
4960
2927
14.1
14.4
13.0
13.9
30.5
30.4
5840
3863
14.2
15.1
13.1
14.0
31.9
30.8
6260
4130
13.8
13.8
12.6
13.7
29.1
29.5
5630
3733
10.4
9.1
11.5
10.0
21.1
15.5
2240
1677
11.7
11.6
13.3
11.7
25.3
21.9
3830
2010
13.8
14.6
15.2
13.4
28.5
30.2
5340
3333
14.3
14.7
15.3
13.9
30.2
31.0
5960
3837
14.9
14.8
15.5
14.3
31.7
31.7
5990
4157
14.2
13.0
15.1
13.0
30.7
27.2
5280
3240
9.7
8.3
11.7
9.2
19.7
13.8
2300
1163
11.6
10.8
13.7
11.5
25.5
21.1
3360
1953
12.6
13.2
15.7
12.0
29.3
30.4
5120
3033
13.3
13.6
15.7
13.3
28.8
29.0
6190
3630
13.4
13.9
16.3
13.4
30.9
29.5
6280
3823
13.2
13.2
15.1
13.2
29.1
28.2
5770
3290
9.9
7.2
11.6
9.3
20.7
12.7
2750
1460
11.7
10.2
13.5
10.1
25
20.1
3920
2083
14.3
13.5
14.9
12.3
28.3
25.4
4990
2890
14.9
13.7
15.2
12.1
32.5
29.7
5740
3380
13.9
13.1
14.9
12.5
30.5
26.1
5760
3817
14.1
13.4
14.9
12.0
29.1
28.6
5280
3140
13
12.5
13.9
12.3
27.8
25.1
4810
2925
4.6
**
ns
**
ns
9.4
**
ns
**
ns
7.5
**
ns
**
ns
8.0
**
ns
**
ns
6.3
ns
ns
**
ns
15.0
ns
ns
**
ns
15.3
ns
ns
**
ns
17.4
ns
ns
**
ns
0.40
2
0.788
0.701
0.658
1.428
2.468
605
419
**Highly significant at 0.01 level, *significant at 0.05 level and ns, non-significant.
195
24-25 March 2015
In 2009/10 and 2010/11, the effect of genotypes was non-significant where as the
effect of fertilizers was found highly significant. In 2009/10, grain yield was increased
with the increased levels of fertilizers. The highest grain yield (6068 kg ha-1) was
obtained at highest level of fertilization (180:90:60 kg N: P2O5 : K2O ha-1 plus FYM 10
t ha-1). The variety Rampur composite produced highest grain yield (4882 kg ha-1)
followed by Across 9942 x Across 9944 (4837 kg ha-1) and Manakamana-4 (4773 kg
ha-1) Similarly in 2010/11, grain yield was increased with the increased level of
fertilization. The highest grain yield (3873 kg ha-1) was obtained at highest level of
fertilization (180:90:60kg N:P2O5:K2O ha-1 plus FYM 10 t ha-1). The variety Rampur
composite produced highest grain yield (3046 kg ha-1) followed by Manakamana-4
(3042 kg ha-1) and Across 9942 x Across 9944 (2816 kg ha-1) (Table 4).
Table 4 : Grain yield under different fertilizer levels and genotypes in 2009/10 and
2010/11 winter seasons at Rampur, Chitwan, Nepal.
Treatments
Grain yield, kg ha-1
Fertilizer levels
2009/10
2010/11
F1 (Control)
2538
1436
F2 (FYM 10 t ha-1)
3713
2057
F3 (60:30:20 N,P2O5 and K2O kg ha- 5103
3046
1
plus FYM 10 t ha-1
F4 (120:60:40 N,P2O5 and K2O kg
5938
3787
ha-1 plus FYM 10 t ha-1
F5 (180:90:60 N,P2O5 andK2O kg
6068
3873
F6 (120:60:40 N,P2O5 andK2O kg
5490
3351
CV,%
15.32
17.4
F-test
**
**
LSD0.05
221.5
419.1
Genotypes
V1 (Rampur Composite)
4882
3046
V2 (Manakamana-4)
4773
3042
V3 (Across9942 × Across9944)
4837
2816
V4 (S99TLYQ-B)
2795
4740
CV,%
15.32
17.4
F-test
ns
ns
LSD0.05
605
342.2
196
24-25 March 2015
Conclusion
On the basis of the results of two years experiments, it can be concluded that maize
genotypes namely Rampur Composite, Manakamana-4, Across 9942 × Across 9944
and S99TLYQ-B produced higher grain yield of 5195, 5074, 5052 and 4789 kg ha-1,
respectively with application of 180: 90: 60 kg N:P2O5 : K2O ha-1 plus FYM 10 t ha-1.
The highest grain yield (4970 kg ha-1) was observed when the crop was fertilized with
180:90:60 kg ha-1 of N:P2O5 : K2O plus FYM 10 t ha-1. Similarly, the highest grain
yield (3964 kg ha-1) was recorded in the Rampur Composite variety.The yield
attributing traits namely cob length, no. of kernel rows per cob and no. of kernels per
kernel rows were found higher at the fertilization rate of 180: 90: 60 N, P2O5 and K2O
kg ha-1 plus FYM 10 t ha-1. It can be concluded that maize varieties need high dose of
chemical fertilizers and organic manure for obtaining high yield of maize.
References
Adhikary BH, S Upadhya, BR Pandey, J Gaire and BR Baral. 2010. Enhancing maize
productivity through the use of manures and fertilizers on the grain yield of
different maize varieties under acidic condition. Pp. 344-350. In: Proc. of the
26th National Summer Crops Research Workshop. Summer crops research in
Nepal, organized by Nepal Agriculture Research Council (NARC) and NMRP,
held 3-5 March, 2010, Rampur, Chitwan, Nepal.
Adhikary BH and DB Ranabhat. 2004a. An economic perspective of manures and
fertilizer application on maize. Pp.287-290. In: Proc. of the 24th National
Summer Crops Research Workshop on maize Research and Production in
Nepal. Nepal Agriculture Research Council (NARC) and NMRP, held June
28-30, Kathmandu, Nepal.
Adhikary BH, DP Sherchan and DD Neupane. 2004b. Effects of N levels in the
production of maize planted at varying densities in the Chitwan valley.Pp.216219. In: Proc. of the 24th National Summer Crops Research Workshop on
maize research and production in Nepal. National Maize Research
Programme, NARC, June 28-30, 2004, Kathmandu, Nepal.
Adhikary BH, BR Pandey and DD Neupane.2007.Increased productivity of maize
genotypes through the use of inorganic fertilizers and agricultural lime in the
Western hills of Nepal.Pp.225-230. In: Proc. of the 25th National Summer
Crops Research Workshop. NARI, NARC, Khumaltar, Lalitpur, Nepal, held
21-23 June,2007.
Adhikary BH, RC Gauli and BB BC. 2001. Effects of manures and fertilizers on the
grain production of maize in rotation with cowpea in acid soils of Malepatan,
Pokhara. Pp. 160-162. In: Proc. of an International Maize Symposium.
Sustainable maize production Systems for Nepal, held December 3-5, 2001,
Kathmandu, Nepal.
Adhikary BH. 2008. Effect of nitrogen on inbred maize seed production planted at
varying densities in the acidic soil at Rampur, Chitwan.Pp.19. In: Proc. of the
Abstracts. The Fifth National Conference on Science and Technology. Nepal
197
24-25 March 2015
Academy of Science and Technology (NAST), Nov. 10-12, 2008. Kathmandu,
Nepal.
Chaudhary AR. 1983. Maize in Pakistan. Pb. Agri. Res. Coordination Board,
University of Agriculture, Faisalabad, Pakistan. Pp. 289-304.
Dayanand. 2002. Maize. Techniques and management of field crops production.
P.S.Rathore (ed.). Rajasthan Agri. University, Bikaner 334006, Agro-bios
(India), Agro House, Jodhpur, India. Pp. 41-61.
Joshy D. 1997. Soil fertility and fertilizer use in Nepal. Soil Science Division, NARC,
Khumaltar, Lalitpur, Nepal. 1997. 82 p.
NMRP. 2006. Soil fertility research highlights. In: Annual Report for the year
2005/06. National Maize Research Programme (NMRP), NARC, Rampur,
Chitwan, Nepal.
NMRP. 2010. Soil Fertility Research Highlights. In: Annual Report for the year
2009/10. National Maize Research Program, Rampur (NMRP), NARC,
Rampur, Chitwan, Nepal.
Regmi AP, JK Ladha, E Pasuquin, H Pathak,PR Hobbs, LL Shrestha, DB Gharti and
E Duveiller. 2002. The role of potassium in sustaining yields in a long-term
rice-wheat experiment in the Indo-Gangetic plains of Nepal. Biol. Fert. Soils.
36 : 240-247.
198
24-25 March 2015
SF-20
Sowing Time and Nutrient Management in Cowpea Under Light Textured
Acidic Soil of Central Chitwan Valley, Rampur
Renuka Shrestha , Bhim N Adhikari and Ramesh Shrestha
Agronomy Division,
, Nepal
Hill Crops Research Program (NARC), Dolakha, Nepal
National Grain Legumes Research Program (NARC), Khajura
, Nepal
Abstract
Cowpea (Vignaunguiculata L. Walp), a short-day plant when sown in rainy season
produced excessive vegetative growth and less grain, and usually high incidence of
insect pests. Introduction of short duration cowpea variety makes possible to grow
cowpea in post rainy season under subtropical climate of central inner terai. As a
legume, cowpea fixes its own nitrogen, however, there has not been any fertilizer
recommendation for short duration cowpea variety in Nepal. Field experiments
consisting of four sowing dates starting from first week of August at 10 days intervals,
and three nutrient management: chemical fertilizers @ 20:40:20 N:P2:O5:K2O kg ha-1,
farmyard manure 10 t ha-1 (FYM), and half dose of chemical fertilizer + 5 t ha-1 FYM
were carried out in determinate cowpea var. Surya to evaluate the optimum time of
sowing and nutrient source under subtropical climate of Rampur from 2008 to 2010.
Growth, grain yield, number of pods per plant and seed size were significantly affected
by sowing dates, while nutrient management had no effect on these parameters. There
was a significant variation among years on those attributes whereas none of interaction
effects except sowing date year were significant. Mean grain yields recorded were 1.49
t ha-1 in 2008, 1.60 t ha-1 in 2009 and 0.89 t ha-1 in 2010. Overall, there was reduction in
grain yield by 12-22% when sowing was delayed after first week of August (1.5 t ha-1).
Plant height, number of pods and plant stand were affected as sowing was delayed.
However, seed weight increased with subsequent delay in sowing. Depending upon the
availability, nutrient management could be done. Reasonable mean grain yield of 1.3
t ha-1 with improved seed size (up to 20% increase) could be achieved even when sowing
was delayed until the last week of August under Rampur condition.
Keywords: Cowpea grain yield nutrient management, sowing time, tropical climate.
Introduction
Cowpea (Vigna unguiculata L. Walp.), also know as black-eyed pea, southern pea is a
warm-season an annual legume originated from Africa, well adapted to many areas of
the humid tropics and temperate zones, and more drought resistant than common bean
(Davis et al 1991). Cowpea is grown as a grain crop, animal fodder, green manure and
green pods as vegetable. Dry grain is also commonly milled and consumed in
numerous traditional main dishes (porridge and breads) in Africa, used as weaning
food for young children, and also eaten as processed snack food (Cisse and Hall 2010).
Grain contains 23-25% protein, 50-67% starch, 1.3% fat, 1.8% fibre, B vitamins such
199
24-25 March 2015
as folic acid, and essential micronutrients such as iron, calcium, and zinc (Cisse and
Hall 2010, TJAI 2010). In world, cowpea (dry) is cultivated in about 11.93 million ha
with production of 6.22 million tons during 2013 (FAOSTAT 2015). The primary
cowpea producing countries in West Africa are Nigeria, Niger, Burkina FasoMali,
Cameroon. Significant area is also grown with cowpea in East African countries such
as Uganda, Mozambique, Tanzania and Ethiopia. Average world yield of cowpea grain
is 522 kgha-1, low yield is due various biotic, abiotic and socioeconomic factors. In
Nepal, the estimated area under cowpea is 8,000 ha with production of 5,660 t and
yield of 700 kgha-1(Yadav et al 2004). With the availability of high yielding short
duration cowpea varieties area has been increasing drastically in the recent years.
Cowpea is a short day plant and flower bud initiation occurs when day length plus
twilight becomes less than 12.5 hours (Cisse and Hall 2010). Sowing at the beginning
of the rainy season in July produced excessive vegetative growth, less grain and show
high incidence of insects (pod eating borer and aphids). As a legume, cowpea fixes its
own nitrogen, however, potassium and phosphorus needs have not been studied for
improved varieties of cowpea in Nepal. Therefore, this study was carried out to
evaluate the best nutrient source and optimum date of sowing under post rainy season
under inner Terai condition.
Four sowing dates: 1 August (17 Shrawan), 11 August (27 Shrawan), 21 August (5
Bhadra) and 31 August (15 Bhadra) in 2008 and 2 August, 12 August, 22 August and 1
September in 2009 and 2010 and three nutrient management: 20:40:20 N:P2O5 :K2O kg
ha-1, 10 t Farmyard manure (FYM) ha-1 and 10:20:10 N:P2O5:K2O kgha-1+ 5 t FYM ha1
were evaluated at Rampur. The soil of experimental plots was light textured sandy
loam. The soil pH of the experimental plot was 5.8 and medium in organic matter
(2.4%) and total nitrogen (0.115%). The experimental design was split plot with three
replications. Sowing dates were assigned to main plot and fertilizer combination to sub
plots. Gross plot size was 4 m x 3 m (8 rows of 3 m length), and yield and yield
components were recorded from net plot area of 3 m x 3 m (6 rows of 3 m length) in
2008, 2009 and 4 m x 2 m (four rows of 4 m length) in 2010. Dual purpose (fresh pod
and grain type) cowpea variety Surya was sown with spacing of 50 cm between rows
and 10 cm between plants in a row.
Chemical fertilizers (urea, diammonium phosphate and muriate of potash) and FYM
were thoroughly mixed with soil prior to sowing. One hand weeding was carried out
about 2 weeks after sowing (DAS). Crops were sprayed with insecticide Thiodan @ 2
mll-1 water 4-6 times, at about 10 day intervals during crop growth period in 2008 and
2009, while twice in 2010. In 2008, matured pods were harvested four times in about a
week interval for crops sown in first and second dates starting from last week of
September (first date) and first week of October (second date), while 2-3 pickings at an
interval of 1-3 weeks were carried out for third and fourth sown crops. In 2008, crop in
the first sowing date had about 60% (first picking) insect damage. In 2009 and 2010,
200
24-25 March 2015
only two pickings were carried out at about 60 and 75 DAS for all sowing dates.
Matured pods were harvested twice beginning from first week of October (first date) to
third week of November (fourth day).
Five plants were randomly selected from each plot to measure the number of pods per
plants, plant height, and pod length. Number of seeds per pod was recorded from 10
pods. Seed yield and straw biomass were estimated from 9 m2 area (6 rows of 3 m
long). Seeds were sun-dried, and fresh straw subsamples weighed and sun-dried to
estimate the straw dry matter yield. Data were analyzed using Genstat Discovery
Edition 3.
There was a significant year to year variation in parameters under studied.
Temperatures and rainfall
Mean maximum and minimum temperatures showed declining trends after October.
(Figure 1). Rainfall more or less evenly distributed during monsoon period in 2008 as
compared to 2009 and 2010. Year 2010 was much drier than the previous two years.
Figure 1: Weekly mean maximum and minimum temperatures and total rainfall
during cowpea growing period in Rampur.
Effect of sowing dates on establishment, growth and yields of cowpea
Plant population
Plant stand at harvest differed significantly among planting dates except for year 2009
(Table 1). Plant stand reduced with subsequent delay in sowing, except for 2008 where
second sowing date had high plant count. There was no difference in plant stand
201
24-25 March 2015
among nutrient combinations. None of the interaction effects (data not shown) except
sowing date x year were significant.
Days from sowing to flowering
The time from sowing to 50% flowering ranged from 34 to 38 days, with the first
harvest of matured pods was in about 60 days after sowing, and the final picking in
about 80 DAS (data not presented).
Plant height
In the year 2008, there was a slight decrease in plant height with delay in sowing, while
plants were taller with subsequent delay in sowing in year 2009 (Figure 2). Rainfall
during flowering time of third and fourth sowing dates had resulted in vigorous growth,
while crops sown on first and second dates already had pod at physiological maturity.
Figure 2: Plant height of cowpea var. Surya at varying dates of
sowing in Rampur.
202
24-25 March 2015
Table 1: Final stand (m2) of cowpea var. Surya as affected by sowing dates and
nutrient management at Rampur (2008-2010).
Year
S
Treatment
N
2008
2009
2010
Mean
Sowing dates (D)
1. 1-2 Aug
20
20
18
20
2. 11-12 Aug
30
20
18
23
3. 21-22 Aug
19
20
15
18
4. 31 Aug-1 Sept
22
20
15
19
Mean
23
20
17
20
P value: D
<.001
0.809
0.013
<.001
LSD (<0.05)
2.2
2.5
1.0
Nutrients (N)
1. 20:40:20 NP2O5K2O kg ha-1
23
20
17
20
2. FYM 10 t ha-1
22
20
16
19
10:20:10 NP2O5K2O kg ha-1+ FYM
3.
20
5 t ha-1
23
20
17
P value - N
0.45
0.57
0.631
0.486
Year (Y)
<.001
LSD (<0.05)
0.893
DxY
<.001
CV, %
7
3
16
10
High plant population in second sowing date during 2008 had resulted in taller plants
and thus greater reduction numbers of pods and seeds) (Table 2).
Grain yield and yield components
In 2008, mean grain yield was the highest (1.8 t ha-1) in early sowing (1 August) and
thereafter grain yield reduced with subsequent delay in sowing (Figure 3). In year
2009, there were no significant differences in grain yield (mean grain yield ranged 1.11.9 t ha-1) among sowing dates (Figure 3), while grain yield ranged from 0.621-1.12 t
ha-1 in 2010. Over all delayed sowing reduced grain yield by 17-44%. Straw biomass
increased with subsequent delay in sowing (Figure 3b).
Greater numbers of pods per plant, seeds per pod and high harvest index contributed to
higher grain yield (Tables 2, 3). Total rainfall recorded during 1-15 August 2009 was
555 mm, i.e., 60% greater as compared to the same period in 2009 (Figure 1). Heavy
rainfall during that period might have affected crop growth as indicated by large
coefficient of variation, and hence greater reduction in grain yield (Figure 3). In 2007,
reducing trend of grain yield with delayed planting after the first week of August was
reported (Yadav et al.2008). Effect of sowing dates on number of seeds per pod was
not consistent between years (Table 2).
203
24-25 March 2015
Figure 3: Grain yields and straw dry matter of cowpea var. Surya as affected by
sowing dates under Rampur condition.
204
24-25 March 2015
Table 2: Number of pods and seeds of cowpea var. Surya as affected by sowing dates
and nutrient management at Rampur (2008-2010).
S
N
Pods plant-1
Seeds pod-1
Treatments
2008
2009
2010
Mean
200
8
2009
2010
Mean
10
8
6
8
13
13
13
13
5
8
5
6
11
13
14
13
8
8
6
7
12
14
13
13
7
8
5
7
12
15
11
13
7
8
7
12
14
13
13
0.003
0.99
6
0.46
4
0.017
0.23
<.001
<.001
0.669
1.6
-
1
-
0.6
1.1
0.344
0.13
0.67
0.941
Sowing dates
(D)
1
.
2
.
3
.
4
.
1-2 Aug
11-12 Aug
21-22 Aug
31 Aug-1 Sept
Mean
P value: D
LSD (<0.05)
P value Fertilizer (F)
0.38
0.26
0.55
7
Year (Y)
<.001
LSD (<0.05)
DF
0.735
<.001
0.86
0.5
0.32
0.93
6
0.699
0.63
0.27
0.077
0.988
DxY
FxY
0.005
0.751
<.001
0.743
DxFxY
CV, %
0.915
26
0.643
13
29
18
29
10
7
9
Seed size (100 seed weight) increased by delay in sowing time (Figure 4). Similarly, in
2007 not the number of pods per plant and seeds per pod but the large seed contributed
to higher grain yield (Yadav et al. 2008). Overall, there was 14-27% increment in seed
weight when delayed after 2 August.
Effect of nutrient management on yields of cowpea
Fertilizer treatments did not show any significant effect on yield and yield components
study (Figure 5, Table 4 ). On the contrary, experiment conducted in Rampur during
2007 had shown that application of 10 t FYM ha-1 produced greater yield, higher
numbers of pods per plant, seeds per pod, and seed size as compared to chemical
fertilizers of 20:40:20 kg NP2O5K2O kg ha-1 (Yadav et al 2008). Also, studies
elsewhere had shown that combined effect of N:P2O5:K2O and FYM increased both
grain yield and macronutrients uptake (Purohit 2003).
205
24-25 March 2015
Table 3: Pod length and harvest index of cowpea var. Surya as affected by sowing
dates and nutrient management at Rampur (2008-2009).
S
N
1
2
3
4
1
2
3
Treatments
Sowing time
2 August
12 August
22 August
1 September
Mean
P value
LSD (<0.05)
Fertilizers (F)
20:40:20 NPK kg/ha
10 t FYM/ha
10:20:10 NPK kg/ha+5 t
FYM/ha
P value
DxF
CV, %
2008
Pod length, cm
HI
2009
Pod length, cm
HI
17
17
17
19
17
0.018
1
0.67
0.52
0.44
0.38
0.5
0.002
0.1
18
17
17
19
18
0.027
1
0.42
0.3
0.33
0 .3 8
0.36
0.092
0.1
18
17
0.51
0.5
18
18
0.35
0.37
17
0.5
18
0.35
0.45
0.4
4
0.61
0.53
7
0.26
0.01
2
0.2
0.27
10
Figure 4: Seed weight of cowpea var. Surya as affected by sowing dates.
206
24-25 March 2015
Table 4: Pods per plant and seeds per pod of cowpea var. Surya as affected by
fertilizer management at Rampur.
S
N
1.
2.
3.
Treatments
2008
Nutrients
management (N)
20:40:20
NP2O5K2O
kg ha-1
FYM 10 t ha-1
10:20:10
NP2O5K2O kg ha1
+ FYM 5 t ha-1
P value -
Pods plant-1
2009 2010
Mean
2008
Seeds pod-1
2009
2010
Mean
7
8
7
8
6
6
7
7
12
12
14
14
13
13
13
13
8
8
7
13
14
13
13
0.38
0.26
5
0.55
7
0.344
<.001
0.86
0.13
0.67
0.941
0.735
<.001
Year (Y)
LSd (<0.05)
Figure 5: Grain yield and seed weight not affected by nutrient management.
Conclusion
Under light textured soil in subtropical condition, yield and yield parameters not
affected by nutrient management. Highest grain yield when sown during first week of
August. Reasonable grain yield and improved seed size during late sown crop indicated
the possibility of delaying sowing date until the last week of August. Seed size was
improved with the subsequent delay in sowing time, thus increase market value. The
non significance effect among fertilizer treatments on grain yield suggest that half of
207
24-25 March 2015
the nutrient requirement of the crops could be supplied from farmyard manure.
However, additional year data is required for the final confirmation of the results.
Acknowledgement
Sincere thanks to Director, Crops and Horticulture, NARC for his valuable support and
guidance. The authors would like to acknowledge the hard work of field technician Mr
KN Ghimire, technical officer Mr BP Wagle and all staff of NGLRP Rampur for their
support in smooth conduction of the experiment.
References
FAOSTAT. FAOSTAT | © FAO Statistics Division. Rome, Italy.
Cisse N and EA Hall. 2010.Traditional Cowpea in Senegal, a Case
Study.http://www.fao.org/ag/AGP/agpc/doc/publicat/cowpea_cisse/cowpea_ci
sse_e.htm
Davis DW, EA Oelke, ES Oplinger, JD Doll, CV Hanson and DH Putnam. 2010.
Alternative Field Crops Manual.
http://www.hort.purdue.edu/NEWCROP/AFCM/cowpea.html
Purohit HS, LL Somani and V Sharma. 2003. Integrated nutrient management in
cowpea-wheat crop sequence. Intern. J. of trop. Agric. 21:119-131
(http://cat.inist.fr/)
Yadav NK, A Sarker, R Darai and BN Adhikari. 2004. Food legumes Research and
production in Nepal. Poster presented in 4th IFLRC held on 18-22 Oct 2005,
New Delhi, India
Yadav NK, R Shrestha and R Sah. 2008.Response of sowing dates and fertility
management on cowpea varieties at Rampur. In: Annual Report. 2007/08,
National Grain Legumes Research Program, Rampur, Chitwan
TJAI. 2010. Cowpea A Versatile Legume for Hot, Dry Conditions. Thomas Jefferson
Agricultural Institute, Columbia, access 2010.
(http://www.jeffersoninstitute.org/pubs/cowpea.shtml)
208
24-25 March 2015
SF-21
E
m
Roshan B Ojha
Himalayan College of Agricultural Science and Technology (HICAST)
Abstract
Farm Yard Manure (FYM) is an integral component of agricultural input in small holder
Nepalese farming communities where mixed cropping system (agriculture and livestock
integration) is practiced. Despite of quality of FYM produced in farm level appropriation
of right dose in farmers' field is not achieved yet. So, to quantify appropriate level of FYM
in farmer field this experiment was conducted at research farm of IAAS from October
2012 to May 2013 catching major two crop growing seasons i.e. winter and spring season
in which broccoli and Mung bean were cropped, respectively. Six treatments (0, 10, 20,
30, 40, 50 t ha-1 FYM) were replicated four times. In each plot 100 earthworms were
released in one square meter earthworm inoculation unit. Soil organic carbon (SOC) and
earthworm growth rate was significantly influenced by FYM levels of 30 t ha-1 in both
seasons. EC1:5, nitrate nitrogen, ammonium nitrogen also achieved highest at this dose in
winter and spring seasons. Hence, once application of 30 t ha-1 FYM is sufficient to
maintain earthworm population and soil properties in the field growing cole crops
followed by legumes in rotation.
Keywords: Earthworm population, farm yard manure (FYM), soil organiccarbon.
Introduction
Farm Yard Manure is a chief source of fertilizer applied by Nepalese farmers. Along
with other chemical fertilizers blending of farm yard manure (FYM) is a common
practice. In case of small farmholder FYM is ultimate source of fertilizer in their field.
Apart from the quality of FYM prepared in farmers' field, right amountof FYM is not
quantified in order to achieve maximum productivity via eN hancing soil properties.
Soil properties like physical (bulk density, porosity, infiltrability hydraulic
conductivity), chemical (pH, EC, available nitrogen, soil organic carbon, available
phosphorous and potassium) plays very crucial role in soil fertility and hence
productivity. In our context appropriate dose of FYM in relation tosoil properties at
farmers' level is not studied. Hence, this study was carried out to access the soil
chemical properties at different farm yard manure levels applied in the field.
Field experiment was carried out in research farm of Institute of Agriculture and
AnimalScience (IAAS)in 2012/13 Six treatments (0, 10, 20, 30, 40 and 50 FYM t ha-1)
were applied in the field with four replications. Experiment was designed in a simple
randomized complete block design. Moisture content of FYM was 75%. FYM was
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24-25 March 2015
applied on the field on fresh weight basis. Two season trials were conducted covering
winter season (Oct – Jan) and dry-wet transitional period (Feb – June). In the first
season broccoli was planted whereas in second season Mung Bean . In every plot 100
earthworms were also released by making small 1 sq.m earthworm inoculation unit.
Soil of 15 cm depth was sampled and its chemical properties were analyzed in lab by
using standard procedure. EC1:5, NH4+ and NO3- were analyzed by using vernier
sensors. Earthworms were manually counted after each season. No additional FYM
was added in second season. To maintain moisture and temperature for earthworm,
mulching and irrigation was regulated daily.
Data were analyzed by using MSTAT version C. Data were first subjected for testing
homogeneity and linearity in SPSS version 16. All data were found linear and
homogenous and then after two-way ANOVA was carried out for significance test at
5% level of significance. Means were separated by using Duncan's Multiple Range
Test (DMRT).
Different level of FYM in the field shows pronounced effect on soil chemical
properties. Changes in some of the chemical parameters were observed.
Electrical conductivity
Electrical conductivity did not differ significantly with the levels of FYM. The lowest
value (28.5 µS cm-1) of EC was obtained from 0 FYM t ha-1 and the highest value
(61.50 µS cm-1) of EC from 30 t ha-1 in winter season. In spring season the lowest
(41.25 µS cm-1) EC was obtained from 20 FYM t ha-1 and the highest (61.75 µS cm-1)
was recorded from 30 FYM t ha-1.
Electrical Conductivity (µS cm-1)
80
y = -0.026x2 + 1.719x + 28.44
R² = 0.899
EC1 (µS/cm)
EC2 (µS/cm)
Poly. (EC1 (µS/cm))
70
60
50
40
30
20
10
0
0
10
20
30
40
50
60
Farm Yard Manure (t ha-1)
Figure 1: Electrical conductivity as affected by different levels of Farm Yard Manure
at Rampur, Chitwan, Nepal 2012/2013.Length of solid bar in the graph
represents the error bar with standard error. 1 and 2 in the graph indicates
winter and spring seasons respectively.
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24-25 March 2015
Electrical conductivity, in the winter season, increased with FYM doses but it started to
decreaseafter 30 t ha-1 of FYM application. In the spring season EC was almost
constant with FYM levels. EC was only increased at 30 FYM t ha-1.Increase in EC of
the soil might be due to the decomposition of larger organic fragment and other
intermediate products during decomposition of FYM. Production of acid and acid
forming substance during decomposition of OM may have reacted with sparingly
soluble salts already present in the soil and converted these into soluble forms and
hence increased their solubility.
Parvathi et al. (2013) noted that soil EC did not significantly differ with the application
FYM and other source of organic manures during the first year of experiment. Values
of EC did notdiffer significantly with the application of different sources and doses of
organic manures, including FYM (Chawala and Chhabra 1991, Stalin et al. 2006). In
contrast, Yilmaz and Alagoz (2010) reported a significant increase in the electrical
conductivity with increase in doses of FYM. They use four levels of FYM dose i.e. 0,
10, 20, and 40 t FYM ha-1 and observed the increase in EC level from each treatment
significantly. Sarwar et al. (2008) also observed an increasing trend of EC in sole
composting (FYM) than with chemical treatments.
Nitrate nitrogen and ammonium nitrogen
Nitrate nitrogen and ammonium nitrogen are the available forms of the nitrogen in the
soil. Change in the total nitrogen pool might results from change in the available
nitrogen pool of the soil. Mineralization of nitrogen from FYM via various modes
depends upon the time of application of FYM (Gupta and Laik 2002). Relative content
of available nitrogen in the soil depends upon several factors such as temperature
during mineralization, microbial activity, C:N ratio of decomposable substances, soil
organisms and so on.
Nitrate-nitrogen and ammonium-nitrogen were not significantly affected by the levels
of FYM applied. The highest 115.75 ± 2.074 mg kg-1 and 136.22 ± 2.502 mg kg-1
nitrate-nitrogen was found from 30 t FYM ha-1 in winter and spring seasons
respectively which were not significantly different from other doses of FYM (Table 1).
This was in line the findings of Gupta and Laik (2002) that higher mineral nitrogen
was found from the treatments 30 t FYM ha-1 than 5 and 45 t FYM ha-1. But Iqbal et al.
(2012) found the highest nitrate-nitrogen from an application of 50 t FYM ha-1.
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24-25 March 2015
Table 1:Effects of Farm Yard Manure on nitrate nitrogen, and ammonium nitrogen in
winter and spring seasons at Rampur, Chitwan, Nepal, 2012/2013.
Treatments
NO –- N
NH + – N
3
4
(FYM
-1
(mg
kg
)
(mg
kg-1)
t ha-1)
winter season
spring season
winter season
spring season
0
114.2
135.4
730.0
794.0
10
110.7
129.2
715.4
780.2
20
114.7
129.4
767.3
775.0
30
115.7
136.2
705.2
746.9
40
112.2
131.9
728.7
762.8
50
112.5
129.3
778.1
797.4
LSD
ns
ns
ns
ns
CV, %
3.66
3.79
5.55
5.99
SEM (±)
2.0748
2.5026
20.4735
23.2445
The highest (778.1 ± 20.10 mg kg-1) ammonium-nitrogen was obtained from 50 t FYM
ha-1 in winter season, but that did not significantly differ from the other treatments. In
spring season also treatment 50 t FYM ha-1 recorded the highest (797.4 ± 23.24 mg
kg-1) ammonium-nitrogen content in the soil. That ammonium content was higher than
the nitrate in the FYM applied soil might be due to formation of humic acid during
mineralization which reduced the volatilization loss of NH3.
Nitrate is one of the most mobile ions in the soil which can be easily leached (Lee and
Jose 2005) from the upper layer (15 cm depth) and accumulated in the lower soil
profile (Rnoal et al. 2006). So, leaching of nitrate ions might cause the lower nitrate
concentration than ammonium ion. Additionally, in the aerobic condition plants absorb
nitrogen in the nitrate form. So, the activity of plant roots and microbes (Iqbal et al.
2012) was greater in the upper layer. Hence, nitrate nitrogen was in lower
concentration than ammonium. Plants absorb only 50% of N applied to the soil
(Craswell and Godwin 1984) and large amount of nitrogen are leached out.
Ammonium content of the soil was relatively higher as compared to the Nitratewhich
contradicts with the findings of Gupta and Laik (2002). He observed the highest
mineralization of NO3--N from 30 t FYM ha-1 applications, which was at par with the
release of NH4--N in two seasons, summer and winter. Another possible reason for
higher content of ammonium than nitrate was the secretion from earthworms.
Earthworms secrete ammonium (Syers and Springet 1984) and uric acid was estimated
to be 18-92 kg ha-1 annually. Earthworm population increased with the increase in
FYM dose. Hence, available nitrogen pool was also affected.
Also, the ammonium content of the soil was found higher than nitrate in the control
plots over the treated plot. In the control plot also earthworms were released. Uptake of
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24-25 March 2015
nitrate nitrogen by the plant roots and earthworm secretions might be the possible
reason to found the higher ammonium nitrogen than nitrate nitrogen.
Soil Organic Carbon
With respect to the initial soil OM there was an increase in the OM content in both the
seasons but overthe two successive seasons there was a decrease in organic matter
content in each treatment.
60
% OC in winter seasony rate = -1.505x - 4.129
Change in organic carbon levels (%)
R² = 0.187
% OC in spring season
40
20
0
0
10
20
30
40
50
-20
-40
Farm Yard Manure (t ha-1)
Figure 2: Percent changes in soil organic carbon in winter and spring seasons with
respect to initial organic matter at Rampur, Chitwan, Nepal (2012/2013).
There was an increase in the Organic C content with the application of FYM and
composts in each year but organic C decreases as the applied fertilization with FYM
and composts in successive years. Decrease in Organic C content was noted (Gondek
and Filipek-Majur 2006) in the soil of every organic manures application (FYM and
other composts) after third year with the experiment.Decrease in organic matter content
in two successive seasons might be due to rate of decomposition of active pool of
organic carbon (Brady and Weil 2008);as there was no addition of the FYM in the
successive season.
Earthworm Growth rate
Earthworm growth rate increases with increasing doses of FYM. Compared with first
season, earthworm growth rate increases in second season. First season is winter
season; temperature is not favorable for earthworm growth. Regular supply of moisture
and favorable temperature eN hance earthworm growth rate. Negative growth rate was
observed in control plot in both seasons, also found from treatment 10 t FYM ha-1 in
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24-25 March 2015
first season but positive growth rate was observed in second season. In control plot
earthworm did not get any food results decrease in earthworm population. Either
mortality rate of earthworm is higher in control plot or earthworms were migrated to
nearby field.
12
Earthworm growth rate (first season)
Earthworm growth rate (second season)
10
y second season= 1.989x - 2.114
R² = 0.887
Linear (Earthworm growth rate (first season))
8
Linear (Earthworm growth rate (second season))
6
yfirst season = 1.859x - 3.552
R² = 0.962
4
2
0
0 t/ha
10 t/ha
20 t/ha
30 t/ha
40 t/ha
50 t/ha
-2
-4
Figure 3: Earthworm growth rate influenced by different levels of FYM at Rampur,
Chitwan (2012/13).
Conclusion
Observed soil chemical parameters show good response at 30 t FYM ha-1. The highest
level of nitrate nitrogen, ammonium nitrogen also found at treatment 30 t FYM ha-1.
Earthworm growth rate increases with increasing level of FYM however no significant
difference obtain between treatment 30, 40 and 50 t FYM ha-1. Electrical conductivity
shows linearity from treatment 30 t FYM ha-1 in either season. Hence, once application
of 30 t FYM ha-1in first season and its residual level in second season is sufficient to
eN hance soil chemical properties and helps to maintain earthworm growth rate and
finally soil fertility for two cropping seasons. Moisture and temperature management in
field is very crucial for earthworm growth and it is very tedious management practice
in the field which cannot be maintained at farm level. So, earthworm inoculation in
field should be verified further.
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24-25 March 2015
References
Brady NC and RR Weil. 2008. 14th edition. Nature andProperties of Soils. Pearson
Education Inc. Prentice Hall. India. New Delhi.
Chawala KL and R Chabbra. 1991. Physical properties of gypsum amended sodic soil
as affected by long-term use of fertilizers. J. Ind. Soc. Soil Sci. 39:40-46.
Craswell ET and DC Godwin. 1984. The efficiency of nitrogen fertilizers applied to
cereals in different climates. Advance Plant Nutr. 21:51-55
Gondek K and B Filipek-Mazur. 2006. Selected soil properties and availability of some
microelements from soil with compost supplement. Polish J. soil sci.
XXXIX/I: 81-90
Gupta AP and R Laik. 2002. Periodic mineralization of nitrogen under FYM amended
soil. 17th WCSS. Paper No. 928. Symposium no. 16.
Iqbal M, AG Khan, AU Hussain, M W Raza and M Amjad. 2012. Soil organic carbon,
nitrate contents, physical properties and maize growth as influenced by dairy
manures and nitrogen rates. Int. J. Agric. and Biol. 14-1-2029.http://www.fspublishers.org
Lee KH and S Jose. 2005. Nitrate leaching in cottonwood and loblolly pine biomass
plantations along a nitrogenous fertilization gradient. Agric. Ecosyst. Environ.
105:615-623.
Parvathi E, K Venkaiah, V Munaswamy, MVS Naidu, TG Krishna and TNVKV
Prasad. 2013. Long-term effect of manure and fertilizers on the soil physical
and chemical properties of an alfisol under semi-arid rainfed conditions. Int. J.
Agric. Sci. 3(4):500-505.
Rnaol YS, LF Min, SD Rang, GT Wen, WJ Guol, SB Ling and JS Ling. 2006. Effects
of long-term fertilization on soil productivity and nitrate accumulation in
Gansu Oasis. Agric. Sci. China. 5:57-67.
Sarwa G, HSchmeisky, N Hussain, S Muhammad, M Ibrahim and E Safdar. 2008.
Improvement of soil physical and chemical properties with compost
application in rice-wheat cropping system. Pak. J. Bot. 40(1):275-282
Stalin P,S Ramanathan, R Nagarajan and K Natarajan.2006. Long-term effect of
continuous manorial practices on grain yield and some chemical properties in
rice-based cropping system. J. Ind. Soc. Soil Sci. 54(1):30-37.
Syers JK and JA Springett. 1984. Earthworm ecology in grassland soils. In: Earthworm
ecology, second edition. (Ed.) J. E. Satchell. Chapman and Hall, London.
Yilmaz E and Z Alagoz. 2010. Effects of short-term amendments of farm yard manure
on some soil properties in the Mediterranean region – Turkey. J. Food, Agric.
Environ. 8:859-862.
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SF-22
Phosphorus Speciation in Nitisol from Ethiopian Highlands
Hari R Upadhayay1,3, Soraya C França2 and Pascal Boeckx3
1
Isotope Bioscience Laboratory (ISOFYS), Faculty of Bioscience Engineering, Ghent
University, Belgium
2
Department of Environmental Science and Engineering, Kathmandu University, Dhulikhel,
Nepal
3
Department of Plant Protection, Faculty of Bioscience Engineering, Ghent University, Belgium
Abstract
Phosphorus (P) is considered as a primary limiting nutrient for faba bean (Vicia faba L.)
production in Nitisol (Western and South-western Ethiopian highlands) due to strong
adsorption of P to Al and Fe (hydr)oxides. The objective of this research was to
differentiate the P into various pools on the basis of its plant availability with respect to
different depths. The soil was collected in the bulk as well as at three depths from an
agricultural field. A modified Hedley sequential P fractionation was carried out to
differentiate phosphorus into different fractions. Sum of all the P fractions [Pt(sum)]
ranged from 648 to 1024 mg P kg-1 at 25 and 5 cm depth, respectively. Concentration of
Fe in the soils extracted via dithionite-citrate (Fed) ranged from 37 to 41 g kg-1. The
amounts of Al extractable by dithionite-citrate (Ald) and ammonium-oxalate (Alox)
were not different with depth and had an average value of 3.13 and 2.31 g kg-1
respectively up to 30 cm depth. For all soil layers largest P fractions were found in
slowly available pool (SAP) (57-57%) followed by the less readily available pool
(LRAP) (28-37%) and readily available phosphorus (RAP) (5-6%). Sum of organic
phosphorus (sum-Po) accounted 20-24% of Pt(sum) that decreased with depth and the
amount of NaHCO3-Po and NaOH-Po part of LRAP contributed 11 to 14% and 44 to
48% of that sum-Po, respectively, suggesting that NaOH-Po was the dominant fraction.
The soil has high concentration of RAP 32 to 59 P mg kg-1. This research showed that
the amount of available P is well above the optimum concentration for adequate faba
bean production in Nitisols of Ethiopian highland.
Keywords: Inner-sphere complex, phosphorus adsorption capacity (PAC), phosphorus
pool, Sesquioxides.
Introduction
Nitisols is one of the most productive soils of Ethiopia. It accounts for about 13.5% of
the total identified soil types and 12% of the total area coverage of the country which
rank first (23%) in terms of area converge of arable lands (Regassa 2009). This soil is
dominant in Western and Southwestern Ethiopian highlands where rainfall intensity is
high. Several authors have reported that between 70 and 75% of the agricultural soils
of the highlands plateau region of Ethiopia is P deficient due to strong adsorption of
H2PO4- to Al, Fe and Mn (hydr)oxides. Under low P fertilizer inputs, soil P availability
is usually the major factor limiting the rate of N2-fixation in legumes and in the
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24-25 March 2015
absence of AMF infection, supplementary P fertilization is generally necessary for the
maintenance of N2-fixation rates by Rhizobium at the level of required to economically
viable legume crop production. On the other hand, most of the phosphate fertilizer in
Nitisols ends up in fixed pools, having a recovery of only approximately 10-20%. In
this perspective, the use of phosphate fertilizer is not sustainable to overcome the P
deficiency in the soil and to secure future food supply. Therefore improved use
efficiency of low P fertilizer inputs and recycling of soil P are important for resource
conservation and environmentally safe agriculture.
Availability of P for plant utilization is not a function of its concentration in the soil,
but rather on the rate of its release from the soil surface into the soil solution. The
ability of soil P to meet plant demand depends on the release of phosphate ions by
desorption or dissolution form the solid phases of the soil. The term available-P is
often used to express the amount of soil P in solution that can be extracted or mined by
plant roots and utilized by the plant for growth and development during its life cycle.
In soil without recent P application, it is estimated that 98% of the P taken up by plants
is released from soil particles during the growth period (Fardeau 1996). The concept
that water-soluble P added to soil in fertilizers or mineralized P and not used by the
crop to which it was applied became mostly fixed in soil in forms unavailable to future
crops was not supported by work after 1950s. The new concept ‘P equilibria in soil’
which explains the changes in the extractability of soil and fertilizer P and the decrease
in plant availability of added P with time (Syers et al. 2008). These equilibria primarily
involve adsorption and absorption processes that may be largely reversible with time.
For P, which in the short- and long-term will be plant available; the current concept is
that this P is held by soil components with a continuum of bonding energies i.e. P
pools.
Phosphorus in the soil solution, the first pool, is immediately available for uptake by
plant roots and is present in solution in ionic forms. The second pool represents Pi that
is only weakly bonded to the surfaces of soil components. This Pi is readily available
because it is in equilibrium with Pi in the soil solution and is readily transferred to the
soil solution as plant roots take up Pi. The P in the third pool is less readily available
for plant uptake, but it can become available over time. This P is more strongly bonded
to soil components, or is present within the matrices of soil components as absorbed P
(i.e. P adsorbed on internal surfaces). Pi in the fourth pool is only very slowly
available, often over periods of many years. It has a low or very low extractability. It is
P that is very strongly bonded to soil components, or is P that has been precipitated as
slightly soluble P compounds, or it is part of soil mineral complex, or it is unavailable
due to its position within the soil matrix. When the P removal by the plant exceeds the
amount of applied or mineralized P, this labile (readily and less readily) Pipool become
the main source of available P for plants. However, the availability of soil P fractions
for plant uptake varies with soil types and the type of plant, and even the so-called
recalcitrant P fraction can be depleted by cropping (Pheav et al. 2003, Vu et al. 2008,
Wang et al. 2007).
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Low-input systems rely on mineralization of soil organic P (Po) or dissolution and
release of P from soil minerals to provide a small amount of soluble P over the growing
season. Increasing plant access to decreasingly available P resources may significantly
improve P nutrition in these systems. However, it is critical to understand the physical
and chemical properties of Nitisols that control the dynamics of inorganic phosphorus
(Pi) tie-up and supply. The major soil Pi transformations are the fixation of P in
sparingly soluble forms by precipitation and sorption reactions and the solubilization of
P by mineral dissolution and desorption reactions. Soil Po transforms primarily
mineralization-immobilization reactions mediated by soil microorganisms and P uptake
by plant roots alone or in association with mycorrhizal fungi. Better understanding of
these processes lead to better P management and better maintenance of soil quality in
Nitisols. Therefore in this research we differentiate the soil phosphorus into different
fractions and pools to test the hypothesis that phosphorus is limiting nutrient for faba
bean production in Nitisols of Dedo , Ethiopia.
Methodology
Soil sampling
Soil was collected on 23 June 2009 from an agricultural field at Dedo latitude 07°
28’48’ N and longitude 36° 52’ 19’’ E in South-Western Ethiopia. The field is located
at the elevation of 2160 masl. Geologically, the area is associated with
JimmaVolcanics with abundant rhyolites and trachybasalt (Solomon et al. 2002). The
mean annual temperature in the region is 20.2°C while an average yearly rainfall is
around 1920.4 mm with bimodal distribution. Soil samples were collected at three
replicates within the fields. In each replicates, soil samples were collected from three
depths 0-10, 10-20 and 20-30 cm along with bulk soil. The soil was tentatively
classified as Nitisolsaccording to World Reference Base classification. The air-dried
soil sample was taken to Isotope Bioscience Laboratory (ISOFYS), Gent University,
Belgium. According to analytical protocols the soil was grinded to sieve through a 0.5
mm sieve (32 meshes) for the soil pH measurement, sequential phosphorus
fractionation and textural analysis but passed through 0.15 mm (100 meshes) sieve for
other analysis.
Soil Analyses
Particle size distribution was determined by pipette method. The percentage of sand (>
50 μm), silt (2-50 μm) and clay (<2 μm) were calculated on a dry weight basis. A
textural class was identified according to USDA textural triangle.Soil pH in water (1:2
wt/vol) and 0.01 M CaCl2 (pHCaCl2) (1:2 wt/vol) was measured by immerging the
electrode in clear supernatant solution.Total carbon (TC) and N analysis was done in
Elemental Analyzer-Isotope Ratio Mass Spectrometry (EA-IRMS) .
Fe, Al and Mn were extracted from 0.5 g soil by using dithionite-citrate (DC) method
of Soil Conservation Service, U.S. Department of Agriculture 1972. Acid ammonium
oxalate Fe (Feox), Al (Alox) and Mn (Mnox) were estimated after extraction with 10 ml
of acid oxalate solution (pH 3) added to 0.25 g of soil in a 50 ml centrifuge tube,
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24-25 March 2015
shaken on a reciprocal shaker for 4 h in the dark. The extracted solutions were
analyzed using Inductive Coupled Plasma Mass Spectrometer (ICP-MS) (VRIAN
Vista MPX with SPS5 Sample preparation system). The concentration was expressed
in g kg-1 soil.
Determination of the total phosphorus (PT) in soil requires the solubilization of P
through the decomposition or destruction of mineral and Po containing materials in the
soil. Wet acid digestion procedure developed by Bowman (1988) was used to
determine PT.
Phosphorus fractions that take part in both short and long-term transformation can be
examined with sequential extractions, which first remove labile P and then the more
stable forms. The sequential P fractionation followed the flow diagram of Figure 1
based on Tiessen and Moir (1993) with some modification. For Resin-Pi, two strips
(1×6 cm) of BDH no. 55164 2S anion exchange membrane were shaken in 30 ml of
deionized water in centrifuge tube containing soil. The resin strips were soaked in 20
ml of 0.5 M HCl after removing them from the centrifuge tube and shaken for 16 h.
The soil containing tubes were ultra-centrifuged (21191× g) at a temperature 0 to 2°C.
The supernatant was discarded and 30 ml of 0.5 M NaHCO3 was added to the residues,
shaken (16 h), centrifuged again and the supernatant were kept in clean polyethylene
bottles in a refrigerator prior to P measurement. The procedures for NaHCO3 were
repeated with 0.1 M NaOH and with 1 M HCl. After extraction in the 1 M HCl, 10 ml
of concentrated HCl (32%) was added to the reside and allowed to react for 10 minutes
at 80°C, whereupon another 5 ml of concentrated HCl was added and the mixture was
hand shaken every 15 min and kept at room temperature for 1 h. The samples were
centrifuged, and the supernatant was decanted in a 50-ml volumetric flask. The soil
was washed with 10 ml deionized water, centrifuged, and washed twice with deionized
water. Deionized water was added to reach total volume of 50 ml. Inorganic P in the
extracts was determined colorimetrically with the molybdate-ascorbic acid
methodology (Tiessen and Moir 1993) but Pi in the NaHCO3 and NaOH extracts was
determined after acidifying 10 ml aliquot in a 40 ml centrifuge tube with 6 ml and 1.6
ml respectively of 0.9 M H2SO4 at 4°C for 30 min to precipitate OM. Total P in
extracts (Pt) was also determined using the method of molybdate-ascorbic acid after
digestion of the NaHCO3, NaOH and conc. HCl extracts by ammonium persulphate
(Tiessen and Moir 1993). For each extract, the amount of organic P (Po)was calculated
as the difference between total and Pi. The soil residue after extraction with
concentrated HCl was transferred to 75 ml digestion tubes containing 5 ml
concentrated H2SO4, first dispersing the soil by 10 ml deionized water. When
temperature reached 360°C, the tubes were removed from heat and cooled down. 0.5
ml H2O2 was added before reheating for 30 min. H2O2 addition was repeated until
liquid was clear. P was determined in clear solution after shaking. Phosphorus fractions
can be grouped mainly into three different pools (Figure 2). Readily available
phosphorus (RAP) is defined as the sum of resin-Pi and NaHCO3-Pi fractions. Less
readily available phosphorus (LRAP) is the sum of NaHCO3-Pi, NaOH-Pi and Po and
diluteHCl-Pi. Similarly slowly available phosphorus (SAP) accounted for HClc-Pi and
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24-25 March 2015
Po and residual Pi. Both phosphorus fractions and pools were expressed as fraction
(part of sum of total P fractions (Pt(sum)) and as concentration (mg P kg-1 soil).
Phosphorus Adsorption Capacity by pedotransfer function
The soil phosphate adsorption capacity (PAC) can be estimated from a pedotransfer
function (PTF). The underlying assumption of using a pedotransfer function is that
hydrous oxides of iron (Fe) and aluminum (Al) are significant components of tropical
soils and they are usually highly reactive because they have large specific areas with a
high proportion of reactive sites. Acid ammonium oxalate extractable aluminium (Alox)
and iron (Feox) together with dithionate-citrate extractable iron (Fed) in mmol kg-1 were
used as input parameters in a pedotransfer function. Thus, PAC was estimated by using
the following formula:
Equation 1
PAC cal = (0.22 ± 0.03) × Alox + (0.12 ± 0.03) × Feox + (0.02 ± 0.01)(Fed − Feox )
Soil texture
The result of particle size analysis showed that soil had a high clay content varying
from 42 to 53% while silt varied from 40 to 48% (Table 1). The clay content in the 2030 cm layer was 25% higher than the 0-10 cm layer. The clay content in the studied
soil increased with the depth indicates the clay migration from the upper layers. This
result is consistent with the result of Solomon et al. (2002) and Fritzsche et al.(2007)
in Ethiopia. High Clay content in the soil is obvious since the soil is developed on
basaltic parent rock. The basic basaltic parent rocks have capability to produce up to
80% clay.
Soil pH
The pH is a “master variable” and knowledge of pH in soil is needed to understand
important chemical process such as phosphate mobility, metal ion equilibria, and rate
of precipitation and dissolution reactions. The pHH2O ranged from 5.5 to 5.6. The
pHCaCl2 was found around 5 but it was an average 0.5 pH unit lower than pHH2O (Table
1). However, pHH2O is subject to large variation within the field owing to seasonal
changes in soil moisture and ionic concentration of soil solution. Therefore,
measurement of soil pH in the solution of 0.01 M CalCl2, is preferred since it is less
affected by seasonality, soil to solution ratios junction potential or long-term storage of
air-dried soils than pHH2O.
Total Carbon and Nitrogen
Apparently, soil fertility is intimately linked to soil organic matter (OM) content,
which influences soil physical, chemical and biological properties, as well as
indigenous soil nutrient supply. Total carbon (TC) ranged from 3.0 to 3.6% (Table 1).
TC significantly correlated with the RAP and LRAP (S1). We found overall values of
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24-25 March 2015
TC to be high in the soil possibly due to association of OM via mineral-organic
associations (MOAs). Sorption of dissolved organic matter derived from the oxidative
decomposition of lignocellulose to Al and Fe oxyhydroxides involves strong
complexation bondings between surface metals and acidic organic ligands, particularly
with those associated with aromatic structures. This fraction is also less biodegradable
than the polysaccharide-derived hydrophilic fraction. However, value of TC can be
compared with the OC (2.65-4.50%) in the eutricNitisol in Southern Ethiopia.
Additionally, nitrogen content is constant up to 15 cm (0.34%) and thereby decreased
to 0.30% at 25 cm. There is no significant effect of depth on the carbon and nitrogen.
Extractable Fe, Al and Mn
Concentration of Fe in the soils extracted via dithionite-citrate (Fed) ranged from 37 to
41 g kg-1 (Table 2). There is no significant difference of Fed with the soil depth. Fed
values of the soil were within the range of Thai Ultisols developed on basalt (26-74 g
kg-1) (Wiriyakitnateekul et al. 2005) and Nitisols in Ethiopia (27-59 g kg-1) (Fritzsche
et al. 2007), however, higher than HumicNitisols from southern Ethiopian highland
(2.5-6.7 g kg-1) (Solomon et al. 2002). Moreover, oxalate-extractable Fe (Feox) ranged
from 9.7 to 10.0 g kg-1 (Table 2). The values of Feox/Fed ranged from 0.26 at the
surface 10 cm layer to 0.24 at the 20-30 cm layer in the soil. In this soil, the amount of
Fed is larger than that of Feox because of the nature of extractants. Dithionite-citrate
method removes organically complexed Al, Fe, and Mn, amorphous inorganic Al, Fe,
and Mn compounds, non crystallinealumino-silicates as well as finely divided
hematite, goethite, lepidocrocite, and ferrihydrite(Fox et al. 1990). On the other hand,
acid-oxalate reagent is known to dissolve allophane and gels, ion and aluminum
organic complexes, hydrated oxides of iron, and aluminium (ferrihydrite, ferroxyhite)
through the processes of protonation, complexation and reduction. In addition, the ratio
of Feox/Fed has been taken as an indicator of the maturity or crystallinity of free ion
oxides in soil. This ratio is higher than Thai Ultisols and Oxisols developed on basalt
(median Feox/Fed = 0.06) (Wiriyakitnateekul et al. 2005) but within the range of soil
from central Ethiopia (0.10-0.47) (Fritzsche et al. 2007). Decreasing Feox/Fed with
increasing depth reflects the transformation of ferrihydrite to better crystalline oxides.
The higher ratio of Feox/Fed in the top layer indicates the effect of organics in impeding
the crystallization of Fe oxides. Similar trends was found in Kuantan series from
Malaysia (Anda et al. 2008), they also concluded that the OM impede the
crystallization of Fe-oxides in the soil.The amounts of Al extractable by dithionitecitrate (Ald) and ammonium-oxalate (Alox) were not different with depth and had an
average value of 3.1 and 2.3 g kg-1 respectively up to 30 cm depth (Table 2).
Extractable Aldmay be present in the structure of iron oxides, in kaolin, or other clay
minerals and Al-OM complexes. These values were similar to the soil developed on
basalt (median Ald 3.5 and Alox 1.3 g kg-1) in Thailand, highly weathered Alabama
Ultisols (average Ald 0.31 and Alox 0.15%) (Shaw 2001) and central Ethiopian Nitisols
(Alox 2-4 g kg-1) (Fritzsche et al. 2007).
Mn concentrationsextracted by using three selective dissolution methods namely
dithionite-citrate (Mnd), ammonium-oxalate (Mnox) and acid hydroxylamine (Mnhyd)
221
24-25 March 2015
was shown in Figure 3. The total Mnhyd, Mnd and Mnox content of present study in the
range of 3.0-3.3, 3.4-3.7 and 2.0-2.2 g kg-1 soil respectively. Mnhyd and Mnox are
significantly correlated with the different P fractions (S1).Mn extracted by acid
hydroxylamine and ammonium oxalate methods is similar to the Mn concentration
(0.9-2.9 g kg-1) reported in the Brazilian Latosols Schaefer et al. 2008) and Mnd and
Mnox were within the same range of Nitisols in Ethiopia (Regassa 2009). The total Mn
content of most soils ranges between 0.2 and 5 g kg-1(Chon et al. 2008). However,
Guest et al.(2002) found that DC extractions removed between 31 and 45% of the
total-extractable Mn from the moist and well-aerated Indiana Ultisols and Alfisols.
Mnd, Mnox and Mnhyd were in general, very similar and well correlated (S1)Similar
result was found by Chon et al.(2008) in Korean soil.
Dithonite is a strong reductant that reduce and extract Mn oxides in more recalcitrant
Mn oxide minerals, perhaps those in small concretions or accumulations, as well as any
Mn substitute in Fe oxide minerals (O (Chon et al. 2008). Only 88-90% of DC
extractable Mn was extracted by NH2OH-HCl, suggesting the presence of NH2OH-HCl
resistant Mn oxides, because this extract is weaker reductant than DC (Chon et al.
2008). Moreover, acid hydroxylamine method that we followed is similar to that used
by Neaman et al.(2004) who achieved nearly total Mn dissolution (85-100%). The
presence of greater than 9.5 g kg-1 amorphous iron oxides in the studied soil as well as
lower Mnhyd than Mnd indicate the abundance of lithiophorite or other more recalcitrant
Mn minerals in the soil. In the opinion of Dixon and Skinner (1993), lithiophorite is
typical of highly weathered soils. Lithiophorite formed on basalt eluvium and including
numerous black Mn-containing nodules was revealed in dark red soil in Hawaii
(Vodyanitskii 2009).
Prediction of PAC from pedotransfer function
Phosphorus adsorption capacity can be predicted from much cheaper and less time
consuming pedotransfer function based on data obtained from dithionate-citrate and
ammonium oxalate extractable Fe and Al (Table 2). PAC estimated from the
pedotransfer function varied from 1550 to 1590 mg P kg-1 soil which is an average 1.5
times higher than the total phosphorus. Estimated PAC increased up to 20 cm. The
estimated PAC using pedotransfer function is higher than cultivated Oxisols and
Ultisols (400 mg P kg-1 ) in Hawaii to maintain 0.10 mg P L-1 in the equilibrating
solution which they believe to be adequate for most crop production. Similarly,
Agbenin (2003) found total P sorbed by the soils ranged from 103 mg kg-1 in the top
soil to 460 mg kg-1 in the subsoil, in the savannaAlfisols. Several authors have
observed significant correlation between total Fe2O3 and P adsorption (Richter et al.
2009, Singh and Gilkes 1991, Torrent et al. 1992), but Quang et al.(1996) has not
found any correlation between Fed and P adsorption. The recognition of the importance
of gibbisite or related Al-hydroxides in P adsorption is patchy in tropical soils, have
been reported mostly from Brazilian Oxisols (Fontes and Weed 1996). However, this
PTF does not consider the clay minerals and Mn oxides as input parameters but we
found significantly strong correlation of P fractions with clay and Mn oxides (S1)
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24-25 March 2015
Soil Phosphorus and pools
Total P measured after wet digestion of soil ranged from 844 to 1242 mg P kg-1 soil
(Table 2). The total P concentration in the 20-30 cm layer is 32% less than the top layer
(0-10). The total P contents of the studied soils are comparable to the levels found in
different soil orders and in different ecosystems from Cameroon, 1025.6 ± 23.1 mg kg1
soil (Tchienkoua and Zech 2003), the United States, 240-1200 mg kg-1 soil (Bowman
et al. 1998) and Ethiopia, 874-1426 mg kg-1 soil (Solomon et al. 2002). Bowman
(1988) found the precision and accuracy of wet acid digestion method that we followed
is similar to that of HClO4 method and gives soil PT values that are approximately 94%
of
those
obtained
with
Na2CO3
fusion.
Moreover,
when
phosphoantimonylmolybdanum blue complex is measured at a wavelength of 712 nm,
color interference from the yellow organic matter is negligible (Tiessen and Moir
1993).
The P fractionations data (Table 3) obtained from the modified Hedley procedure by
Tiessen and Moir (1993) suggested that P was mainly associated with occluded or
precipitated P compounds or the part of soil mineral complex. For all soil layers, the
largest P fraction was found in slowly available pool (SAP) (57-67%) followed by the
less readily available pools (LRAP) (28-37%) (Figure 4).The RAP pool accounted for
little (5-6%) of the Pt(sum). RAP proportions are similar to those found in Latosol in
Brazil (1-7%) (Araújoet al. 2004), humicNitisols in Ethiopia (2% except resin-Pi)
(Solomon et al. 2002) and A horizon of an acidic Brazilian Oxisols (3%) (Cardoso et
al. 2006). The resin extractable Pi fraction is regarded as freely exchangeable P and
thus easily accessible to plants. Hence, resin-Pi could reasonably be used as an index of
P bioavailability. Resin-Pi fraction ranged from 4.5 to 14.3 mg kg-1 and the NaHCO3-Pi
from 27.6 to 44.7 mg kg-1 soil. Moreover, NaHCO3-Po and NaOH-Po decreased with
soil depth and the amounts of NaHCO3-Po and NaOH-Po contributed 12 and 47% of the
total Po respectively, suggesting that NaOH-Po was the dominant fractions. NaHCO3-Po
is important buffering fraction for resin-Pi. This fraction is the most labile of organic P
fractions and Tiessenet al.(1984) had reported that resin-Pi was largely controlled by
the mineralization of Po and that 80% of the availability in resin-Pi was accounted for
by variations in bicarbonate Po (S1). In addition, both discrete annual burning of
biomass during land preparation that converts a fraction of organic P into mineral
forms and repeated tillage which also accelerates organic-matter decomposition affect
NaHCO3-Pi concentration in the soil. Sum total Po (Sum-Po) fractions varied from 20 to
24% of Pt(sum) while on average, 33 to 44% of LRAP was organic (NaHCO3-Po and
NaOH-Po). The ratio of TC to Po ranged from 177 at the top layer (0-10 cm) to 215 at
the bottom layer (20-30 cm). The Pi associated with Ca (dilute HCl-Pi) contributed 5 to
8% of Pt(sum). Moreover, in acid soil, it is more likely that the extraction solution pH,
buffered to 8.5 like in our NaHCO3 procedure, promotes desorption of P. In soils,
containing Al- and Fe bound P, the concentration in solution increases as the pH
increases because at high pH, the higher concentration of OH- ions decreases the ability
of PO4-P to compete for sorption sites. Nevertherless, the combined resin and
bicarbonate extracts, and the chemical nature of their action, help to define the readily
223
24-25 March 2015
plant available phosphorus pool. They reflect the ligand exchange (with HCO3-) and
dissolution reactions which regulate soil solution P. Thus, RAP is P that can most
readily transfer to the soil solution to replace P taken up by crop roots.
Value of NaOH-Pi, part of the LRAP represented third largest fraction following HClcPi and residual-Pi in the soil. This is an agreement with the data of Tiessen and
Moir(1993) for BrazalianOxisols but disagreement with the result of Lilienfeinet
al.(2000) from the cerradoOxisols where largest proportions of P have been found in
fractions extracted with NaOH and Rheinheimer and Anghinoni (2001) also had
observed similar proportion in subtropical soils. These fractions (NaOH-Pi and Po) are
supposed to be bound to Fe and Al oxides, kaolinite and organic P associated with
humic and fulvic acids (S1). These fractions denote the P reserve (135-266 mg P kg-1
soil) that is plant available when converted to RAP through biological and chemical
transformation. However, Buehler et al.(2002) claimed that the NaOH-Pi fraction was
in dynamic equilibrium with RAP even in the short term. Similarly, Beck and Sanchez
(1994) also concluded that NaOH-Po was the dominant source of plant available P in
the non-fertilized Peruvian Ultisol. Moreover, NaOH-Po contributed large part of total
Po in this study. Both NaHCO3-Po and NaOH-Po are not significantly different with
depth since under crop cultivation residues mixed well in the soil. However, the TC:Po
of this soil is < 200 in upper 15 cm (Table 3), mineralization of Po could readily occur
leading to increase in the level of available Pi, provided that P thus released is not fixed
in unavailable forms by Fe, Al and Mn oxides and hydroxides or clay. The top layer
had lower C:Po ratios than the deeper ones, a reflection of the lower accumulation of
organic matter in the surface layer. Moreover, the fractions of RAP and LRAP
significantly correlated with TC so that the management of organic carbon could be
sustainable way to supply P requirement for legume prouction.
The low input subsistence agriculture practiced in Dedo area of Ethiopia depends on
the continuous supply of P from soil reserves along the production cycle. The common
crops (maize, teff, bean etc.) take up a variable amount of P, depending on the biomass
accumulation, which varies according to rainfall, but on average P absorption is around
5 kg ha-1 in each growing cycle (Araújo et al. 2004). However, the soil has high
concentration of RAP 32 to 59 mg kg-1 corresponding to 96 to 177 kg ha-1,
respectively calculating from the depth 30 cm and 1 g cm-3(Fritzsche et al. 2007,
Solomon et al. 2002) density of soil. This amount of P is well above the optimum
concentration (12-34.4 kg P ha-1) for adequate faba bean production in Ethiopia
(Agegnehu and Fessehaie 2006). Assuming that these quantities would be available for
plant uptake, the soils could be cropped for a few years before the supply depleted. An
even longer period of cultivation without fertilizer would be possible if the deeper
layers and the replenishing of RAP by LRAP were considered. As the supply of
available P to crops in tropical soils not under fertilization has been reported to come
largely from organic pools (Beck and Sanchez 1994), both NaHCO3-Po and NaOH-Po
fractions buffer the resin-Pi to a large extent thought mineralization. However, the
magnitude of the contribution of this pool to available P might depend on other soil
factors such as Fe and Mn oxides (S1), as well as the ability of the crop to utilize P
224
24-25 March 2015
from fractions normally not available. Specially, SAP is thought to be a non-available
fraction for plants and normally do not undergo short-term changes under cropping.
This includes more resistant inorganic and organic P forms. The large amount of P in
the SAP followed by LRAP emphasize the need to develop sound management
strategies to utilize native soil P more effectively, which can perhaps be achieved by
manipulation of plants, such as mycorrhizal annual plants (Cardoso and Kuyper 2006)
as well as agro-forestry system, associated with micro-organisms (Richardson 2001).
Extraction
Fraction name
Extracted P
0.5 g of soil
Resin Strip
Resin-Pi
Freely exchangeable P
0.5M NaHCO3
NaHCO3-Pi
NaHCO3-Po
Weakly adsorbed P
0.1M NaOH
NaOH-Pi
NaOH-Po
P associated in Fe and
Al hydrous oxides
1M HCl
Dilute
HCl-Pi
Stable Ca associated Pi
Conc. HCl
HClc-Pi
HClc-Po
Stable Fe and Al associated
Pi and stable Po
H2SO4+H2O2
Residual-Pi
Highly recalcitrant Pi
Figure 1: Flow diagram of modified Hedley P fractionation method modified by
Tiessen andMoir (1993).
P
Watersoluble P in
fertilizer
and
Losses
P in
Soil
solution
Resin-Pi
NaHCO3-Pi
NaOH-Pi & Po
NaHCO3-P0
Dilute HCl-Pi
Readily
available pool
Less readily
available pool
225
HClc-Pi & Po
Residual-Pi
Slowly
available pool
24-25 March 2015
Figure 2:Simple schematic representations of phosphorus pools in the plant-soil
systems. Soil analysis to estimate P in the readily available pool includes that
in the soil solution (Partially adapted from Syers et al. 2008).
4.0
d
d
cd
bcd
3.5
bc
b
Mn (g kg-1 soil)
3.0
2.5
a
a
a
2.0
1.5
1.0
Mnd
Mnox
0.5
Mnhyd
0.0
0-10
10-20
20-30
Depth (cm)
Figure 3:Comparison of extractable Mn concentration by dithionite-citrate (Mnd),
ammonium-oxalate (Mnox) and acid hydroxylamine (Mnhyd) methods with
the function of depth. Bars headed by same letter(s) are not significantly
different (p<0.05).
226
24-25 March 2015
P fractions and pools (%)
100
RAP
90
LRAP
80
SAP
Resin-Pi
70
NaHCO3-Pi
60
NaHCO3-Po
50
NaOH-Pi
40
NaOH-Po
30
Dilute HCl-Pi
20
HClc-Pi
10
HClc-Po
Residual-Pi
0
0-10
10-20
Depth (cm)
20-30
Figure 4: Percentage of inorganic and organic P fractions and P pools in three
different soildepths.
Table 1: Physical and chemical characteristics (mean± SE; n=3) of the soil with depth.
Within rows, numbers followed by the same letter (s) are not significantly
different (p<0.05) by Tukey HSD test.
Parameters
Clay, %
Silt, %
pHH2O (1:2)
pHCaCl2 (1:2)
TC, %
TN, %
Depth, cm
10-20
49 ± 1.8ab
43 ± 1.3a
5.58 ± 0.02a
4.99 ± 0.01a
3.4 ± 0.21a
0.34 ± 0.03a
0-10
42 ± 2.5a
48 ± 2.9a
5.57 ± 0.05a
5.06 ± 0.03a
3.6 ± 0.09a
0.34 ± 0.03a
227
20-30
53 ± 2.5b
40 ± 1.9a
5.65 ± 0.06a
5.00 ± 0.04a
3.0 ± 0.23a
0.30 ± 0.04a
24-25 March 2015
Table 2: Dithionate-citrate and ammonium oxalate extractable Fe and Al with soil
depth. Comparison of total phosphorus (PT) and predicted PAC from Fed,
Feox and Alox. Within columns, values followed by the same letter are not
significantly different at p<0.05 by Tukey HSD test.
Depth
(cm)
0-10
10-20
20-30
Fed
38.57 ±
1.12a
40.37 ±
2.82a
41.10 ±
4.71a
Concentration, g kg-1
Feox
Ald
9.94 ±
3.12 ±
0.29a
0.07a
9.95 ±
3.23 ±
0.49a
0.06a
9.69 ±
3.06 ±
0.65a
0.12a
Alox
Feox/
Fed
PAC,
mg kg-1
1548 ± 6.5
a
2.25 ± 0.04a
0.26a
2.33 ± 0.03a
0.25a
1589 ±6.4b
2.35 ± 0.13a
0.24a
1587±11.3
b
PT ,
mg kg-1
1242 ±
137.4a
1006 ±
149.1a
844 ± 152.8a
Table 3:Concentration of phosphorus (P) (mean ± SE; n=3) in the various extracts and
ratio readily available P (RAP): sum Po and sum of all the P fractions (Pt(sum))
at three depths in Dedo Ethiopia
Depth, cm
P fractions
(mg P kg-1soil±SE)
0-10
10-20
20-30
Resin-Pi
14.3 ± 2.5a
8.7 ± 3.3a
4.5 ± 2.3a
NaHCO3-Pi
44.7 ± 16.5a
31.3 ± 14.0a
27.6 ± 13.7a
NaHCO3-Po
28.0 ± 4.2a
24.5 ± 5.7a
16.5 ± 4.1a
NaOH-Pi
168.8 ± 28.2a
103.6 ± 28.3a
69.0 ± 15.4a
NaOH-Po
97.9 ± 11.6a
94.5 ± 20.7a
66.9 ± 19.1a
Dilute HCl-Pi
81.6 ± 6.1b
55.0 ± 7.4ab
33.3 ± 5.6a
HClc-Pi
255.1 ± 9.6b
211.4 ± 8.7a
196.4 ± 7.0a
HClc-Po
78.0 ± 5.1a
75.5 ± 9.0a
65.5 ± 8.2a
Residual-Pi
255.5 ± 8.8b
203.8 ± 10.0a
168.8 ± 10.6a
Pt(sum)1
1023.9 ± 38.2b
808.3 ± 42.2a
648.5 ± 32.7a
PT
1242 ± 137.4a
1006 ± 149.1a
844 ± 152.8a
Sum-Po2
203.9 ± 19.0a
194.5 ± 24.2a
148.9 ± 30.3a
RAP3
59.1 ± 18.7a
40.1 ± 16.5a
32.8 ± 14.3a
RAP: Pt(sum)
0.06 ± 0.02a
0.05 ± 0.02a
0.05 ± 0.02a
TC:Po
177 ± 12.2a
178 ± 13.6a
215 ± 26.8a
1. Pt(sum) = sum of fractional P;
2. Sum-Po = NaHCO3-Po+ NaOH-Po+ HClc-Po;
3. RAP = Resin-Pi+ NaHCO3-P i
For a given P fraction, significant differences are indicated by different letters (p<0.05, HSD, with
sequential Tukey corrections) among the depths for a given fractions (rows); n=3.
228
24-25 March 2015
Table 4: Correlations matrix of P fractions and soil parameters. Number indicated in
the matrix are values of the Pearson correlation coefficient, r
Variables
(mg kg-1)
pHCaC
Clay
(%)
Fed
Feox
Ald
Alox
Mnd
Mnox
Mnhyd
Fed-Feox
0.22
0.85**
-0.67*
-0.74*
0.78*
-0.09
-0.29
0.45
0.70*
0.66
-0.76*
0.53
0.75*
-0.24
-0.65
0.50
-0.45
-0.19
0.23
0.60
0.64
-0.64
0.40
0.91**
-0.57
-0.77*
0.76*
-0.14
-0.17
0.44
0.76*
0.70*
-0.78*
0.33
0.83**
-0.67*
-0.69*
0.69*
-0.09
-0.39
0.48
0.65
0.69*
-0.70*
-0.11
0.91**
-0.54
-0.87**
0.84**
-0.23
0.17
0.39
0.93**
0.72*
-0.87**
0.40
0.76*
-0.94**
-0.56
0.35
0.07
-0.27
0.72*
0.71*
0.88*
-0.54
0.70*
0.57
-0.66
-0.34
0.08
-0.02
-0.61
0.61
0.40
0.82*
-0.31
0.07
0.53
-0.30
-0.46
0.28
-0.17
0.23
0.29
0.56
0.68*
-0.44
0.38
0.66
-0.82**
-0.49
0.43
0.13
-0.37
0.59
0.52
0.72*
-0.49
0.48
0.83**
-0.41
-0.75*
0.65
-0.34
-0.21
0.33
0.70*
0.71*
-0.75*
(1:2)
Resin-Pi
NaHCO3-Pi
NaHCO3-Po
NaOH-Pi
NaOH-Po
DiluteHClPi
HClc-Pi
HClc-Po
Residual-Pi
RAP
Fe, Al and Mn oxides, g kg-1
TC
(%)
l2
*, ** significance atp<0.05 andp<0.01 respectively.
Conclusion
Soil analysis indicated that the soil is at the margin for faba bean production with
respect to soil pH. In addition, abundance of manganese equal to Al was found in the
soil and believed that the Al(OH)3 preserved in the lithophorite could contribute
substantial phosphorus sorption in the soil. The phosphorus sorption capacity
calculated on the basis of Fed, Feox, and Aloxindicated that the soil can absorb 1.5 times
more phosphors than the total phosphorus. The soil contains high total P concentration
irrespective of consensus that soil is low in phosphorus. Readily available P was found
5 to 6% of Pt(sum) which is sufficient for faba bean production for few more years. It
also showed that sum-Po decreased with depth and the amount of NaHCO3-Po and
NaOH-Po part of LRAP contributed 11 to 14% and 44 to 48% of that sum-Po,
respectively, suggesting that NaOH-Po was the dominant fraction. Moreover, the
fractions of RAP and LRAP significantly correlated with TC so that the management
of organic carbon is very important for sustainable faba bean production. Finding large
amount of P in the SAP followed by LRAP emphasize the need to develop sound
management strategies to utilize native soil P more effectively, which can perhaps be
achieved by manipulation of plants, such as mycorrhizalfaba bean as well as
agroforestry system, associated with micro-organisms. Transfer of P from subsoils
through biocycling may sustain adequate P levels in surface soil and provided that P
export is not high, low-input systems in this soil may be sustainable.
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SF-23
Yield Trend and Soil Fertility Status After a 36-Years Rice-Rice-Wheat
Experiment
Nabin Rawal1, Dev R Chalise1, Dinesh Khadka2 and Khim B Thapa1
1
National Wheat Research Programme (NARC), Rupandehi, Nepal
2
Soil Science Division (NARC), Khumultar, Lalitpur, Nepal
Abstract
A long-term soil fertility experiment under rice-rice-wheat system has been conducted
by NWRP, Bhairahawa to evaluate the long-term effects of inorganic fertilizer and
manure applications on soil properties and grain yield of crops since 1978.The
with 9
experiment was laid out in Randomized Complete Block Design
treatments replicated 3 times. From 1990 onwards, periodic modifications have been
made in all the treatments splitting the plots in two equal halves of 4m x 3m (12 sq.m.)
leaving one half as original. In the original treatments, the recent data revealed that the
use of FYM @10 t ha-1 gave significantly higher yield of 3243 kg ha-1 in normal rice and
2091 kg ha-1 in wheat whereas control plot gave the lowest grain yield of 563 and 447 kg
ha-1 in rice and wheat respectively. Similarly, in the modified treatments, the recent data
indicatedthat the use of FYM @10 t ha-1 along with inorganic N and K2O @50 kg ha-1
each produced significantly highest yield of 4061 kg ha-1 in normal season rice, 3094 kg
ha-1 in wheat and 2071 kg ha-1 in early rice. The control plot with an indigenous nutrient
supply only supported normal rice, wheat and early rice yields of 563, 447 and 267 kg
ha-1, respectively after 36th year completion of rice-rice-wheat system. A sharp decline in
rice yields was noted in minus P treatment in normal season rice whereas in early rice it
was almost zero whereas wheat yield decline was noted in both P and K missing plots.
The application of P2O5 and K2O caused a partial recovery of yield in phosphorus and
potassium deficient plots. The soil analysis data showed an improvement in soil pH
(7.7), soil organic matter (3.87%), total nitrogen content (0.14%), available phosphorus
(409 P2O5kg ha ) and exchangeable potassium (133 K2O kg ha ) with the use of FYM
@10 t ha-1 along with inorganic N and K2O @50 kg ha-1. The findings showed that the
productivity of the crops can be increased and sustained by improving nutrient through
the integrated use of organic and inorganic manures in long-term in Nepal.
Keywords: Early rice, farm yard manure (FYM), long-term soil fertility, soil fertility
wheat yield.
Introduction
Rice and wheat are the most important food crops of Nepal and they are mostly grown
in sequence especially in Terai region of Nepal. In Nepal, most of the land is under the
rice and wheat, mostly in the Terai plain, meets about 75% of the country’s total food
demand. Productivity and profitability are quite low. A doubling of the crops
production in the next 25 years is needed to meet Nepal’s estimated population growth.
Increasing the productivity of land through intensive cropping depletes nutrient
reserves of the soil at a faster rate. An unbalanced fertilizer application may disturb
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24-25 March 2015
nutrient availability to crops, leading to a reduction in yield. Improving productivity
and increasing cropping intensity is required to meet future food needs. Adequate soil
fertility will be essential to improve and sustain yields.The productivity of land under
such a system is unlikely to be sustained unless new merging nutrient deficiencies or
imbalances are identified and corrected promptly. Example can be cited of zinc
deficiency in rice and boron in wheat. Long-term experiment is valuable for evaluating
the effects of continuous cropping on the capacity of a system to sustain nutrient
supply and the productivity. The long term experiment was initiated under rice-ricewheat system in 1978/79 at National Wheat Research Program (NWRP), Bhairahawa
to evaluate the effects of long term application of mineral fertilizer and organic manure
on soil properties and grain yield of the crops in the long run under rice-rice-wheat
system.
The major objectives of long term soil fertility experiment were as follows:
• To study effects of continuous application of mineral fertilizer and organic
manure on crop yields
• To examine and explain yield trends of rice and wheat
• To analyse soil fertility status after 36 years of the experiment
Site, treatments and crop management
The experimental site is situated at Bhairahawa in the western Terai region of Nepal at
the latitude of 27°32’ and the longitude of 83°28’ with an elevation of 120 masl.
Temperature ranges from a minimum of about 7°C in winter to the maximum of about
45 0C in summer season. In general, the site receives ample rainfall during the rainy
season, which starts from June and continues up to September. The mean annual
rainfall is about 1800 mm. The soil of the experiment plot was silty loam with a pH of
8.0, organic matter (OM) of 1.783%, Olsen P of 9.75 ug-1, exchangeable K of 126 ug g1
soil and bulk density of 1.6 g cc-1and there is a hard pan just below the plow layer.
The soils in the experiment area are classified as Typic Heplaquepts.
The experiment was laid out in randomized complete block design with 9 treatments
which were replicated 3 times. The plot size was 6 X 4 m2 up to 1990. From 1990
onwards, periodic modifications have been made in all the treatments splitting the plots
in two equal halves of 4m x 3m leaving one half as original (Table 1). Wheat was sown
in rows of 25 cm apart and rice was transplanted at 20cm x 20cm plant to plant
spacing. Farm yard manure was applied at 7-10 days before seeding. Half dose of N
and full dose of P and K were applied as basal. Remaining 50% nitrogen was top
dressed at 21-25 days after seeding in wheat and 25-30 days after transplanting in rice.
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24-25 March 2015
Table 1: Original and modified treatments of LTSFE (R-R-W)at NWRP, Bhairahawa
1
Original treatment
N:P2O5 :K2O: kg ha-1
0: 0:0 - R & W
2
100:0:0- R & W
3
100:30:0 - R
100:40:0 - W
4
100:0:30- R & W
5
100:30:30 – R
100:40:30 - W
6
100:0:0 – R
100:40:30 - W
100:30:0 - ER
7
50:0:0 - R & W+ 30 cm
stubble incorporation
50:20:0 - R & W +30 cm
stb. incorporation
8
50:20:0 - R & W+ 30 cm
9
F Y M 10 t ha-1 - R & W
50:20:20 - R & W + 30 cm
50:20:0 - R & W+ 30 cm
F Y M 10 t ha-1+ 50 kg N - F Y M 10 t ha-1+ 50 kg N + 50
R&W
kg K20 - R & W
Tr. No.
Modified Tr. (1991)
0: 0:0 - R & W
100:30:30 - R
100:40:30- W
100:30:0 - R
100:40:0 - W
100:100:30
One time - ER
100:30:30 – R
100:40:30 - W
Modified Tr.(1995 onward )
100:50:100- R & W
100:30:30 - R
100:40:30- W
100:30:30- R
100:40:30 - W
100:30:30 – R
100:40:30 - W
100:30:100 – R
100:40:100 - W
100:0:0 – R
100:40:30 – W
100:30:0 - ER
50:20:0 - R & W +30 cm stb.
incorporation
Measurement of crop parameters
Data were recorded on days to heading, days to maturity, spikes m−1, grains spike−1,
spike length, 1000 grain weight, biological yield, grain yield and harvest index.
Number of spikes in one meter square area at four different places were counted in
each subplot and converted into number of spikes sq.m. Number of grains spike−1 was
recorded by counting the number of grains of 5 randomly selected spikes from each
subplot and average number of grains spike−1 was calculated. A random sample of
1000 grains from each treatment was collected and weighed with digital balance for
1000 grain weight. For biological yield, 6 sq.m area from each subplot was harvested,
sun dried, and weighed into kgha−1. For grain yield, the biomass of 6 sq. marea from
each subplot was sun dried, threshed, cleaned and grains were weighed into kgha−1.
Soil sampling and analysis
Soil samples were collected from each of the experimental plots. Each soil sample was
randomly collected from the 0 to 20 cm deep plough layer using an auger. For this, the
air-dried samples were crushed and passed though a 2mm sieve. Soil pH was
determined by a pH meter after extraction from a soil: water ratio of 1:2. Organic
matter was determined using the Walkley and Black dichromate method (Nelson and
Sommers 1982) and total N using Kjeldhal’s method (Bremner and Mulvaney 1982)
For available P determination, modified Olsen’s (Olson and Sommers 1982);
exchangeable K (Knudsen et al. 1982) was estimated by 1M ammonium acetate
extraction followed by flame photometric determination.
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24-25 March 2015
Recorded data were compiled and tabulated in Ms-Excel. Data for each parameter over
two year period was subjected to analysis of variance using a randomized complete
plot design according to MSTATC (Steel and Torrie 1980) and GENSTAT. Treatment
means were compared using least significant difference (LSD) test at P ≤ 0.05.
Grain yields of wheat and rice in rice-rice-wheat system were affected by the
application of different combination of manures and fertilizer treatments. In the
original treatments, the recent data revealed that the use of FYM @10 t ha-1 gave
significantly higher yield of 3243 kg ha-1 in normal rice and 2091 kg ha-1in wheat
whereas control plot gave the lowest grain yield of 563 and 447 kg ha-1in rice and
wheat respectively. Similarly, in the modified treatments, the recent data indicated that
the use of FYM @10 t ha-1 along with inorganic N and K2O @50 kg ha-1each produced
significantly highest yield of 4061 kg ha-1in normal season rice, 3094 kg ha-1 in wheat
and 2071 kg ha-1in early rice. The control plot with an indigenous nutrient supply only
supported normal rice, wheat and early rice yields of 563, 447 and 267kg ha-1,
respectively after 35th year completion of rice-rice-wheat system.
Yield trend of normal season rice and early rice
A severe yield decline was observed with the advancement of the year in treatments T2
and T4. Grain yield fell to almost zero in early rice, indicating severe P deficiency in
the soil. Phosphorus deficiency clearly reduces yield. The results show that yield trends
for the NK treatment (T4) were similar to the control (no-fertilizer treatment) by year
35 of the experiment. In both treatments in which P was included (T3 and T5) and in the
FYM treatment (T9), grain yield declined up to 2008/09 and then slightly increased
then after. This trend is difficult to explain. Possibly it could be the result of changes in
P dynamics (sorption and desorption of P in the soil).
Grain yield (kg/ha)
2500
2000
1500
1000
500
0
2003/042004/052005/062006/072007/082008/092009/102010/112011/122012/132013/14
Year
T1=0: 0:0 - R & W
T5=100:30:30 – R
100:40:30 - W
T9=F Y M 10 t/ha - R & W
Figure 1: Effect of long term application of T1, T5 and T9 on early rice.
236
24-25 March 2015
Grain yield (kg/ha)
2500
2000
1500
1000
500
0
T2=100:0:0- R & W
Year
T4=100:0:30- R & W
T3=100:30:0 - R
100:40:0 - W
T5=100:30:30 – R
100:40:30 - W
Figure 2: Effect of long term application of T2, T3, T4 and T5 on early rice.
Grain yield (kg/ha)
The results show that neither the present dose of NPK nor FYM can sustain
productivity in this system. These results corroborate those of Flinn and Datta (1984),
who reported a yield decline under the full recommended dose of fertilizer. In many
fertilizer experiments, Nambiar and Abrol (1989) have also found a declining trend
with adequate NPK. FYM alone could not supply N and K requirement of rice crop.
The response of P was not clearly seen in early rice, although the combined analysis
showed that the NPK treatment resulted in a better yield than the NP treatment. There
was residual effect of P applied to wheat seen in early rice. Generally 15–20% of
applied P is utilized by the rice crop, and the remainder gradually becomes available to
the succeeding crop. Similar result also has been reported by Regmi (1991).
2500
2000
1500
1000
500
0
Year
T4=100:0:30- R & W
T6=100:0:0 – R
100:40:30 - W
T5=100:30:30 – R
100:40:30 - W
Figure 3: Effect of long term application of T4, T6 and T5 on early rice.
237
24-25 March 2015
Grain yield (kg/ha)
6000
5000
4000
3000
2000
1000
0
T1=0: 0:0 - R & W
Year
T5=100:30:30 – R
100:40:30 - W
T9=F Y M 10 t/ha - R & W
T9M=F Y M 10 t/ha +
50 kg N + 50 kg K20 - R & W
Figure 4: Effect of long term application of T1, T5, T9 and T9 on normal rice.
Grain yield (kg/ha)
The results indicated that yield trends for the NK treatment (T4) were similar to the
control (no-fertilizer treatment). Compared to yields of early rice, yields of normalseason rice were affected less by the fertilizer treatments but recommended dose of
NPK and FYM treatments gave the higher yield than other treatments (Figure 4). Yield
trends were similar to early rice, however, even thoughthe magnitude of the yield
decline was less severe in normal-season rice. A severe yield decline was observed in
the treatment without P (T4); grain yield fell to zero by year 35 similar to early rice. A
residual effect of P applied to wheat was seen in normal season rice. The P applied to
wheat was not fully utilized by the subsequent early rice crop, so the normal-season
rice crop also obtained some benefit from the P application in wheat. Significant
differences in grain yield were seen between the NPK and NP treatments, indicating
that the yield reductions in this experiment were also due to the K deficiency.
6000
4000
2000
0
Year
T2=100:0:0- R & W
T3=100:30:0 - R
100:40:0 - W
T4=100:0:30- R & W
T5=100:30:30 – R
100:40:30 - W
Figure 5: Effect of long term application of T2, T3, T4 and T5 on normal rice.
238
24-25 March 2015
Grain yield (kg/ha)
6000
5000
4000
3000
2000
1000
0
Year
T4=100:0:30- R & W
T6=100:0:0 – R
100:40:30 - W
T5=100:30:30 – R
100:40:30 - W
Figure 6: Effect of long term application of T4, T6 and T5 on normal rice.
With the increase in potassium level there was increase in the grain yield of normal
rice. Both the NPK (recommended dose) and FYM treatments could not sustain grain
yields in the long run. The yield increase with the modified (T9M) possibly resulted
from replacement of the original (T9). A increase of 818 kg/ha grain yield of normal
ricewas observed due to the application of 50 kg ha-1both N and K2O to FYM treatment
in the latest year 2013/14.
Yield trend of wheat
After 35 years of the experiment, significantly higher yield of wheat was found in T5,
T9 and T9M as compared to other treatments. There was fluctuation in grain yield of
wheat which could be due to variation in rainfall, temperature, etc. during crop
growing period. The data revealed that the grain yield of wheat was higher in case of
treatment T9M (FYM 10 t ha-1 and nitrogen and K2O 50 kg ha-1 each which is followed
by FYM application alone (T9) and the recommended fertilizer dose (T5).
The results shows that yield trends of wheat for N treatment (T2), NK treatment (T4)
and NP treatment (T3) were similar to the control (no-fertilizer treatment) by end of 35
years of the experiment. There was very low grain yield in all P missing treatments (T1,
T2, T4, and T7). This shows P is one of the most limiting factors in wheat crop. In all
treatments in which one or more primary nutrients were lacking, resulted decline in
wheat grain yield.
239
Grain Yield (Kg/ha)
24-25 March 2015
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
Year
T1=0: 0:0 - R & W
T5=100:30:30 – R
100:40:30 - W
T9=F Y M 10 t/ha - R & W
T9M=F Y M 10 t/ha +
50 kg N + 50 kg K20 - R & W
Figure 7: Effect of long term application of T1, T5, T9 and T9M on wheat.
Grain Yield (Kg/ha)
3500
3000
2500
2000
1500
1000
500
0
Year
T4=100:0:30- R & W
T6=100:0:0 – R
100:40:30 - W
T5=100:30:30 – R
100:40:30 - W
Figure 8: Effect of long term application of T4, T6 and T5 on wheat.
240
24-25 March 2015
The grain yield of wheat was found higher in T5 (recommended dose in both rice and
wheat) followed by T6 (recommended dose in wheat only). The significant differences
in grain yield were seen between the NPK and NP treatments, indicating that the yield
reductions in this experiment were also due to the K deficiency.With the increase in
potassium level, there was increase in the grain yield of normal wheat.
The results show that neither the present dose of NPK nor FYM can sustain
productivity in this system. These results corroborate those of Flinn and De Datta
(1984), who reported a yield decline under the full recommended dose of fertilizer.
Nambiar and Abrol (1989) have also found a declining trend with adequate NPK. FYM
alone could not supply N and K requirement of wheat crop. The yield increase with the
modified (T9M) possibly resulted from replacement of the original (T9) due to balance
dose of NPK and other micronutrients contained in FYM.
3500
Grain Yield (kg/ha)
3000
2500
2000
1500
1000
500
0
Year
T2=100:0:0- R & W
T3=100:30:0 - R
100:40:0 - W
Figure 9: Effect of long term application of T2, T3, T4 and T5 on wheat.
241
Grain yield (kg/ha)
24-25 March 2015
4000
3000
2000
1000
0
1011
2012
2013
2014
Year
T2=100:0:0- R & W
T5=100:30:30 – R
100:40:30 - W
T5M=100:30:100– R
100:40:100 - W
Figure 10: Effect of long term application of T2, T3, T4 and T5 on wheat.
Soil fertility status
There was a significant effect of manures and fertilizers on soil pH, soil organic matter,
nitrogen content, available phosphorus and exchangeable potassium.
Table 2: Effects of manures and fertilizer on pH, organic matter, nitrogen,
phosphorus and potassium contents of soil after 36 years of experiment,
NWRP, Bhairahawa, Nepal.
Treatme
nts
T1
T2
T3
T4
T5
T6
T7
T8
T9
F test
LSD
(0.05)
CV, %
Initial
(1978/79
AD)
pH
Organic
Matter, %
Nitrogen,
%
P2O5,
kg ha-1
K2O,
kg ha-1
Origin
al
8.25
8.25
8.16
8.23
8.21
8.20
8.23
8.18
7.87
**
0.16
Modifi
ed
8.11
8.18
8.17
8.14
8.16
8.21
8.17
8.15
7.95
ns
-
Origin
al
1.27
1.67
2.15
1.67
2.30
2.15
2.02
2.06
4.10
***
0.89
Modifi
ed
1.89
2.18
2.33
1.89
2.39
1.65
2.13
1.86
4.12
**
0.99
Origin
al
0.08
0.09
0.10
0.09
0.11
0.10
0.10
0.10
0.16
***
0.03
Modifi
ed
0.09
0.10
0.11
0.09
0.11
0.09
0.10
0.93
0.16
**
0.03
Origin
al
11.5
11.7
93.7
14.7
44.4
10.7
12.3
38
503.5
***
45.63
Modifi
ed
123.8
50.0
70.5
40.8
57.2
34.0
28.8
34.4
403.7
***
49.86
Origin
al
94.3
76.0
34.9
103.4
71.5
62.3
76.0
71.5
117.1
*
40.57
Modifi
ed
117.1
80.6
76.0
53.2
103.4
62.3
66.9
76.0
137.8
*
40.67
1.1
1.1
23.9
25.2
14.7
15.8
32.1
30.8
29.8
28.4
8.0
1.025
0.088
242
9.8
126
24-25 March 2015
Conclusion
The control plot with an indigenous nutrient supply still supported rice yield of 563
kg/ha and wheat yield 447 kgha-1 in normal season after 36 year completion of ricerice-wheat system. There was very low grain yield in all P missing treatments (T1, T2,
T4, and T7) in rice. This shows P is one of the most limiting factors in rice. The
deficiency of both P and K was clearly seen in P and K missing plots. FYM alone
could not supply N and K requirement of rice crop. Addition of 50 kg N and 50 kg
K2O ha-1in FYM treatment (T9) increased 818, 1003 and 537 kg/ha grain yield of
normal rice, wheat and early rice respectively. A fertilizer management strategy that
ensures sufficient nutrient supply with the use of organic and inorganic sources for
high and stable overall productivity of rice–rice-wheat system is needed.
Acknowledgments
I would like to thank the Wheat Coordinator, NWRP, Bhairahawa for providing
facilities and proper guidance during the course of this research. The authors express
deep appreciation to all the staffs of NWRP, Bhairahawa who had contributed in
continuing this experiment in the past. Thanks also goes to the present staffs of NWRP
without whose assistance, the experiment would not have reached this stage.
References
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DR (eds.). Method of soil analysis. Chemical and microbiological properties.
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Knudsen D, GA Peterson and PF Pratt. 1982. Lithium, sodium and potassium. In: Page
AL, Miller RH, Keeney DR (eds.) Method of soil analysis, chemical and
microbiological properties. ASA &SSSA, Madison. Pp. 228–238
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overview. Fertilizer News. 34: 11-20.
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matter. In: Page AL (ed.). Method of soil analysis, chemical and
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(eds.) Method of soil analysis. Chemical and microbiological properties. ASA
and SSSA, Madison. Pp. 403–430
Regmi AP. 1991. Long-term fertility trial under rice–rice–wheat rotation. Paper
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SF-24
Long-term oil ertility rial in ice - heat ystem in egional
gricultural esearch tation, Khajura, Banke: esults of oil nalysis
ata from 1998 to 2006 and 2014 AD
Gautam Shrestha
Regional Agricultural Research Station, NARC, Khajura, Banke
Abstract
Long-term soil fertility trial (LTSFT) was initiated in the Regional Agricultural Research
Station, Khajura, Banke since 1978. The experiment was designed in Randomized
which consisted nine treatments with different fertilizer
Complete Block Design
doses and with three replications. Soil analysis results from rice – wheat system collected
through 1998 to 2006 and 2014 were used. Results revealed treatments had significant
effect in soil organic matter (p value = 0.0046) and soil available phosphorus (p value =
0.013) content. Soil pH trend long-termwas significant (p value < 0.05) positive in all
treatments except two i.e. control and only nitrogen (100 kg ha-1) applied treatments Soil
organic matter (SOM) trend line along the time was significantly positive for all
treatments (p value<0.001) except (100:00:30 N P2O5 K2O kg ha-1), (100:30:30
N P2O5 K2O kg ha-1) and (50:00:00 N P2O5 K2O kg ha-1). With negative R squared value,
to fit along the time line. Soil
soil available phosphorus content showed non-linear
available potassium trend line was falling-off along the time line in all treatments except
control treatment. Soil organic matter had significant (p value<0.001) positive contribution
in soil pH, soil available phosphorus and soil available potassium content. Soil pH had
significant (p value<0.001) negative contribution in soil available phosphorus and positive
contribution in soil available potassium content.
increase the current dose of potassium fertilizer in rice – wheat system in Khajura
condition.
Keywords: Cropping system current dose of potassium, long-term soil fertility, nutrient
management.
Introduction
Rice – wheat is one of the main cropping systems followed in South and East Asia
(Timsina and Connor 2001). As both crops are main diets (FAO 2014), these crops are
cultivated for centuries and will continue for many generations ahead. So, sustainable
maintenance and increase in the productivity of these crops determine the food security
of this region (Ladha et al. 2000).
Different studies have been conducted on different aspects of rice – wheat cropping
system to increase productivity including method of planting (Sudhir et al. 2011),
water management (Lin et al. 2006), fertiliser application (Gami et al. 2001, Yadav et
al. 1998), weed management (Pittelkow et al. 2012), tillage methods (McDonald et al.
2006, Saharawat et al. 2010) and combination of these factors (Sudhir et
244
24-25 March 2015
al.2014,Timsina et al. 2001, Wade et al. 1998, Zhao et al. 2013). Additionally,
greenhouse gas emission from the rice – wheat system has received concern in the
context of climate change (Bhatia et al. 2010).
Long-term experiments are conducted in different countries to monitor the effect of
different soil nutrient management practices in the local soil fertility and productivity
(Gami et al. 2001, Han et al. 2010, Poulton 2006, Regmi et al. 2002, Vanlauwe et al.
2005). Furthermore, release of nutrients, carbon sequestration (Shibu et al. 2010) and
possible build-up of toxic elements in the soil are slow process, so need long-term
experiments (Diacono and Montemurro 2010).
Long-term experiments are continued in rice – wheat cropping system at different
stations of Nepal Agricultural Research Council (NARC). Gami et al. (2001) did data
analysis of soil analysis results from 1994 to 1999 from rice – wheat experiment at
Regional Agricultural Research Station (RARS), Parwanipur, Bara, Nepal. Soil organic
carbon did not change with the application of 100 kg nitrogen, 13.1 kg phosphorus, and
25 kg potassium per hectare. In contrast, with similar amount of chemical fertiliser
application at National Wheat Research Programme (NWRP), Bhairahawa in rice –
rice – wheat cropping system, soil organic carbon content increased during 1988 to
1998 (Regmi et al. 2002). Furthermore, at Masodha, Uttar Pradesh, India, data analysis
from 1977 to 1996 revealed soil organic carbon content increased by 44% in the field
with 120 kg nitrogen, 35 kg phosphorus and 33 kg potassium per hectare (Yadav et al.
1998). Similarly, in Punjab intensive farming with application of 120 kg nitrogen per
hectare resulted 1.1% increase in soil carbon content during 1981 to 2006 (Benbi and
Brar 2009). In contrast, at Nashipur, Bangladesh soil analysis results from 1994 to
1997 revealed decrease in the soil organic carbon content in all treatments including
with 135 kg nitrogen per hectare in both irrigated and rainfed condition (Timsina et al.
2001). At Panjab Agricultural University, Ludhiana, from long-term experiment started
since 1971, soil analysis in 2005 revealed application of 120 kg nitrogen, 30 kg
phosphorus and 30 kg potassium nutrient per hectare resulted into 1.7 to 5.3 g soil
organic carbon per kg soil (Kukal and Benbi 2009).
In rice – wheat system, soil pH decreased over time in all treatments at Nashipur,
Bangladesh condition (Timsina et al.2001). Similarly, in Punjab, India, soil pH
declined from 8.5 in year 1981 to 7.7 in the year 2006 (Benbi and Brar, 2009).
Furthermore, Choudhary et al. (2011) found declining soil pH trend line with canal
water application at Ludhiana, India condition. In contrast, soil pH was increased from
7.0 to 7.3 with farmyard manure application at Parwanipur condition (Gami et al.
2001).
Soil available phosphorus content was higher in farmyard manure treated plots
compared to 100:13.1:25 kg N:P:K per hectare at Parwanipur (Gami et al. 2001) and
Bhairahawa (Regmi et al. 2002) condition. In contrast at Masodha, India soil available
phosphorus increased by five fold in phosphorus applied (dose of 35 kg phosphorus per
hectare) plots (Yadav et al. 1998).
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24-25 March 2015
In the case of soil available potassium content, in Parwanipur condition it was
declining in plots with 100:13.1:25 kg N:P:K application per hectare application
compared to farmyard manure applied (4 t ha-1on the basis of dry weight) plots with
positive balance (Gami et al. 2001). At Bhairahawa soil available potassium declined
over the period in all treatments including plots with only farmyard manure treatement
(Regmi et al. 2002). In contrast, at Masodha, soil available potassium increased in all
treatments including potassium fertiliser not applied plots as well (Yadav et al. 1998).
This work focused on determining influence of different fertiliser doses in rice – wheat
system in the soil chemical properties. It will help to make models and predict future
soil fertility at Khajura condition. Additionally, future guidance to improve soil
productivity will be gained.
Long-term experiment was initiated in Regional Agricultural Research Station
(RARS), Banke since 1978. Long-term experiment was conducted in paddy – wheat
system. Different nine doses of chemical fertiliser treatments were applied to determine
the influence on soil properties. Soil chemical parameters were determined from the
soil sampled after each crop harvest.
Agronomic practice
In rice-wheat cropping system, a released rice variety seedling was transplanted at the
20 cm x 20 cm cropping distance. During the winter, a released wheat variety seed was
sown at 25 cm row to row distance. Each plot was 25 square metres in size. The land
remained fallow in between two crops. There were total nine treatments with three
replications arranged in Randomized Complete Block (RCB). Nutrient treatment
details for both paddy and wheat are given in the Table 1. Goat manure from goat shed
in the farm was used as farmyard manure and applied before land preparation. For
chemical fertilisers, phosphorus and potassium were applied as basal dose. Half dose of
nitrogen was applied as basal dose and other half was applied as top dressing after first
irrigation. Irrigation was applied as per the crop, climate and environmental conditions.
Table 1: Nutrient treatment details for paddy and wheat crop.
Nitrogen (N)
Phosphorus (P)
Potassium (K)
Treatment
kg per hectare
1
0
0
0
2
100
0
0
3
100
30
0
4
100
0
30
5
100
30
30
6
50
20
20
7
50
0
0
8
50
20
0
9
Farm Yard Manure (FYM) application of 10 ton per hectare
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24-25 March 2015
Soil analysis
Soil was analysed for soil pH, soil organic matter content (modified Walkley black
method), soil available phosphorus (sodium bicarbonate method), and soil available
potassium (ammonium acetate method). Initial soil fertility status of the plots before
planting rice in 1998 is given in Table 2.
Table 2: Initial soil properties measured before planting rice in 1998 in rice – wheat
system.
Treatment
Soil
Soil organic
Soil available
Soil available
(N:P2O5:K2O kg
pH,
matter
phosphorus,
potassium,
ha-1)
Units
content,%
P2O5 kg ha-1
K2O kg ha-1
00:00:00
7.8
1.976
56.6
37.6
100:00:00
7.4
1.842
30.9
32.3
100:30:00
7.4
1.675
100:00:30
7.2
1.809
25.7
100:30:30
7.4
2.010
36.0
35.9
50:20:20
7.6
1.976
56.6
50:00:00
7.5
1.842
30.9
50:20:00
7.5
1.239
123.6
FYM 10 t ha-1
7.4
2.345
72.1
Data analysis
Statistical analysis was done using Rstudio software version 0.98.1102. Role of
different treatments in the crop performance were determined using Analysis of
Variance (ANOVA). Post hoc analysis was performed using highly significant
difference (HSD).Trend lines were drawn for each soil characteristics. Further,
regression analysis was conducted among soil parameters. Graphs were drawn using
Sigmaplot version 12.2.0.45.
Analysis of variance
Treatments had no significant effect on soil pH (Table 3). Similar, results were shown
by Gami et al. (2001) in Parwanipur condition with pH difference of 0.6 units between
full dose of nitrogen phosphorus and potassium nutrients application from chemical
fertiliser and only Farm Yard Manure applied plots. According to Timsina et al.
(2001), compared to initial soil pH (Table 2), soil pH declined in all treatments (Table
3). Timsina et al. (2001) studied different level of nitrogen (0, 90,135 kg nitrogen
nutrient per hectare) and water management (rainfed and irrigated) in rice – wheat
system in Nashipur, Bangladesh from 1994 to 1997. They found that soil pH declined
over time in all treatment combinations. It was may be due to flood irrigation which
contain carbonates (CO3 ) which need to be buffered by soil (Timsina and Connor
2001). Additionally, use of urea and diammonium phosphate as nitrogen source causes
release of hydrogen ion (H+) during uptake of ammonium ion (NH+4) by plants (Wei et
al. 2006). Similarly, harvest of crops from the field removes base cations with
247
24-25 March 2015
remaining net effect of increase in soil acidity (Allison 1973). Furthermore, plant roots
release though weak organic acids contributes to decrease in soil pH (Jones 1998).
Soil organic matter content was significant high in treatment with only Farm Yard
Manure applied plots (10 t ha-1) i.e. 27% more than in control (no fertiliser) plots
(Table 3). In contrast, Yadav et al. (1998) reported 70% higher soil organic matter
content in treatment with 120 kg nitrogen, 35 kg phosphorus and 33 kg potassium
application compared to control (no fertiliser), The result showed only 5% higher soil
organic matter content in treatment with 100 kg nitrogen, 30 kg phosphorus, and 30 kg
potassium applied through chemical fertilisers as compare without fertiliser input
(Table 3). While comparing Table 2 and Table 3, soil organic matter content decreased
1998 to 2014. It was on par with Shibu et al. (2010) who revealed decreased organic
matter content in different long-term experiments in India and through Yang's model
prediction as well.
In accordance with Gami et al. (2001), soil available phosphorus content was
significant high in only Farm Yard Manure applied plots (10 t ha-1) about 40% high
compared to no fertiliser (Table 3). In agreement with Gami et al. (2001) and Regmi et
al. (2002) Farm Yard Manure applied plots contain 20% more soil available
phosphorus than full dose of chemical fertiliser applied (100 kg nitrogen, 30 kg
phosphorus and 30 kg potassium nutrient ha-1). It might be due to addition of Farm
Yard Manure which contributed to phosphorus balance in the system due to microbes
which got food from Farm Yard Manure (Hedley et al. 1982). Soil available
phosphorus content increased during 1998 to 2014 as obtained in Table 2 and Table 3.
Treatment had no significant effect on soil available potassium content (Table 3).
Similar results were shown by Gami et al.(2001) and Yadav et al.(1998) at Parwanipur
condition, most probably due to application of insufficient amount of potassium
fertilizer .
Table 3: Analysis of variance for soil data from 1998 to 2006 and 2014 and mean ±
SE for each treatment.
Treatment
(N:P2O5:K2O
kg ha-1)
00:00:00
100:00:00
100:30:00
100:00:30
100:30:30
50:20:20
50:00:00
50:20:00
FYM 10 t ha-1
p- value
HSD value
CV,%
Soil pH
Soil organic matter
content, %
7.0 ± 0.06
7.0 ± 0.05
7.0 ± 0.06
7.0 ± 0.06
6.9 ± 0.06
7.0 ± 0.06
7.0 ± 0.06
7.0 ± 0.05
7.0 ± 0.05
0.8936
-6.06
1.101 ± 0.098 b
1.173 ± 0.063 ab
1.169 ± 0.069 ab
1.198 ± 0.089 ab
1.150 ± 0.054 b
1.202 ± 0.078 ab
1.097 ± 0.051 b
1.227 ± 0.099 ab
1.518 ± 0.110 a
0.013
0.354
52.19
248
Soil available
phosphorus, P2O5
kg ha-1
57.50 ± 6.55 b
62.37 ± 7.14 b
73.09 ± 6.47 ab
65.02 ± 7.12 b
75.13 ± 6.87 ab
71.38 ± 6.64 ab
59.31 ± 6.47 b
68.93 ± 6.66 ab
94.83 ± 6.69 a
0.0046
29.62
73.9
Soil available
potassium, K2O
kg ha-1
106.59 ± 4.63
98.33 ± 4.19
102.86 ± 4.87
105.99 ± 3.32
106.00 ± 4.17
103.26 ± 4.32
108.55 ± 5.32
103.55 ± 4.83
118.00 ± 4.61
0.159
-32.18
24-25 March 2015
Trend analysis of different nutrients
Soil pH
Though looking at Table 2 and Table 3, soil pH declined over time, on an average soil
pH had increasing trend in all treatments (Table 4). Gami et al. (2001) obtained 0.3
units increase in soil pH during five years in organic manure applied plots compared to
initial soil pH of 7.0 in 1994. Organic manure addition contributed 16.5% of increase
soil pH. Soil pH increase might be contributed by the ground water containing calcium
salts which was applied as irrigation water.
Table 4:Linear model fit and descriptive values of soil pH in different treatments.
Treatment
(N:P2O5:K2O kg
ha-1)
00:00:00
100:00:00
100:30:00
100:00:30
100:30:30
50:20:20
50:00:00
50:20:00
FYM 10 t ha-1
Adjusted Rsquared
0.011
0.021
0.092
0.085
0.077
0.157
0.101
0.054
0.165
Linear model fit
along the years
(x)
y = 0.02x – 31.96
y = 0.02x – 36.74
y = 0.04x – 69.75
y = 0.04x – 68.38
y = 0.04x – 67.45
y = 0.05x – 92.39
y = 0.04x – 67.45
y = 0.03x – 52.56
y = 0.05x – 82.34
Soil pH
p- value
0.210
0.140
0.012
0.015
0.020
0.001
0.009
0.043
<0.001
Maximum
Minimum
7.8
7.8
7.8
7.8
7.8
7.8
8.1
7.7
7.9
6.1
6.1
5.9
6.0
5.9
6.0
6.1
6.1
6.1
Soil organic matter content
At Khajura, Nepalgunj condition Farm Yard Manure application significantly (p value
< 0.001) contributed 23% increase in soil organic matter from 1998 to 2014 (Table 5).
These results were similar to Regmi et al. (2002) who did find significant soil organic
matter build up in control (without fertiliser input). It is because atmosphere is source
of carbon for plants not soil (Marschner and Marschner, 2012) however Gami et
al.(2001) got contrast result with the application of 4t Farm Yard Manure per ha.
Organic matter might have increase due to addition of crop residue stubbles which are
left and incorporated in the soil. Additionally, no excessive mechanical tillage prevents
organic matter loss as carbon dioxide. Because of the small size of the plots, no
mechanical tillage was used only manual spade tillage was performed. The possible
contribution in soil organic matter content was least in 100 kg nitrogen application per
hectare plots because with availability of nitrogen, soil carbon is used more by microorganisms which is released as carbon dioxide (Fog 1988). In the case of 50 kg
nitrogen and 20 kg phosphorus application per hectare, possible build-up of soil
organic matter was the highest amongst others, might be due to lesser availability of
nitrogen nutrient for micro-organisms with lesser input and phosphorus input increases
the plant biomass including root. In contrast, Shibu et al. (2010) based on Yang's
model study predicted decline in soil organic carbon content in India condition.
249
24-25 March 2015
Table 5: Linear model fit and descriptive values of soil organic matter in different
treatments.
Treatment
(N:P2O5:K2O
kg ha-1)
00:00:00
100:00:00
100:30:00
100:00:30
100:30:30
50:20:20
50:00:00
50:20:00
FYM 10 t ha-1
Soil organic matter,%
Adjusted Rsquared
Linear model fit
along the years (x)
p-value
0.272
0.258
0.281
- 0.002
- 0.017
0.224
-0.017
0.382
0.230
y = 0.11x – 217.14
y = 0.07x – 135.09
y = 0.08x – 153.58
y = 0.02x – 44.58
y = 0.003x – 4.25
y = 0.08x – 157.44
y = 0.01x – 6.41
y = 0.13x – 258.09
y = 0.11x – 225.21
< 0.001
< 0.001
< 0.001
0.353
0.858
< 0.001
0.791
< 0.001
< 0.001
Maximum
Minimum
5.2
3.6
3.5
4.4
2.8
4.1
2.8
5.3
5.5
0.2
0.5
0.5
0.3
0.2
0.3
0.4
0.2
0.4
Soil available phosphorus
There is no significant linear model fit of soil available phosphorus in different years
(Table 6). The negative R squared value reveals non-linear model fit. In contrast,
Regmi et al. (2002) revealed significant increase of soil total phosphorus content over
time in full dose of chemical fertilisers input and Farm Yard Manure treatments.
Table 6: Linear model fit and descriptive values of soil available phosphorus in
different treatment.
Treatment
(N:P2O5:K2O
kg ha-1)
00:00:00
100:00:00
100:30:00
100:00:30
100:30:30
50:20:20
50:00:00
50:20:00
FYM t ha-1
Adjusted
R-squared
Linear model fit along
the years (x)
0.004
– 0.017
– 0.018
– 0.015
– 0.005
– 0.012
– 0.017
– 0.018
– 0.008
y = 2.00x – 39510.80
y = 0.60x – 1136.56
y = 0.22x – 356.94
y = 0.83x – 1582.98
y = 1.59x – 3112.11
y = 1.11x – 2148.70
y = 0.37x – 685.70
y = – 0.15x – 363.87
y = 1.34x – 2594.86
pvalue
0.273
0.765
0.906
0.680
0.405
0.551
0.834
0.937
0.471
Soil available phosphorus,
P2O5 kg ha-1)
Maximum
Minimum
164.9
9.2
195.8
9.2
175.2
9.2
195.8
9.2
206.1
15.5
206.1
9.2
164.9
9.2
175.2
9.2
247.3
20.6
Soil available potassium
Soil available potassium content declined in all treatments except no fertiliser applied
plots (Table 7). Regmi et al.(2002) got significant increase of available potassium with
100 kg nitrogen, 30 kg phosphorus and 30 kg potassium per hectare and with Farm
Yard Manure (10 t ha-1). In contrast to these findings, Gami et al.(2001) revealed
declining soil available potassium in 120 kg nitrogen, 13.1 kg phosphorus and 25 kg
potassium per hectare whereas increment of soil available potassium in Farm Yard
Manure (4 t ha-1 dry weight) . Furthermore, Yadav et al.(1998) reported soil available
potassium increase to in all treatments including treatments without potassium fertiliser
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24-25 March 2015
input. A possible reason for the decrease in the soil potassium availability is
simultaneous application of ammonium based and potassium fertiliser in the soil. It
causes more fixation of ammonium in the soil which is used by heterotrophic microorganisms. Moreover, these organisms also need potassium for their metabolism hence
both nutrients are less available for plant uptake (Allison 1973). Additionally, use of
100 kg nitrogen and 30 kg phosphorus demands for higher amount of potassium
fertilisation than 30 kg potassium applied. It is because plants need almost equal
amount of potassium for growth and development as nitrogen need (Marschner and
Marschner 2012). Hence, potassium was extracted from the soil (Samra and Swarup
2002) and was declining.
Table7: Linear model fit and descriptive values of soil available potassium in
different treatment.
Treatment
(N:P2O5:K2O
kg ha-1)
00:00:00
100:00:00
100:30:00
100:00:30
100:30:30
50:20:20
50:00:00
50:20:00
FYM 10 t ha-1
Adjusted Rsquared
Linear model fit along
the years (x)
- 0.018
- 0.017
- 0.008
0.003
0.064
0.025
0.010
0.046
0.103
y = 0.12x – 124.73
y = – 0.28x + 661.15
y = – 1.00x – 2112.46
y = –1.52x + 3147.54
y = – 2.44x + 4994.10
y = – 1.85x + 3808.82
y = – 1.82x + 3763.18
y = – 2.51x + 51339.34
y = – 3.30x + 6723.19
pvalue
0.929
0.811
0.461
0.099
0.032
0.126
0.218
0.061
0.008
Soil available potassium,
K2O kg ha-1)
Maximum
Minimum
281.6
37.6
196.3
32.3
249.1
40.8
158.4
48.4
166.6
10.1
212.3
53.7
307.2
50.4
223.1
59.1
223.1
11.0
Regression analysis
Role of soil pH
Soil pH had significant negative contribution in soil available phosphorus (slope =
24.66) (Figure 1). As soil acidity decreases, the phosphorus species concentration
changes from higher concentration of H2PO4-and HPO4-2 to higher concentration of
PO4-3. However, PO4-3 is not taken up by the plants but H2PO4- and HPO4-2(Marschner
and Marschner, 2012). Sodium bicarbonate (NaHCO3) extraction method easily
removes H2PO4 from soil colloidal surface and less easily HPO4-2. Soil pH had
significant positive contribution in the soil available potassium (slope = 12.22) (Figure
1). With decreasing soil acidity, colloidal exchange surfaces are free from hydrogen
ion hence, more possible to adsorb potassium ion. At lower soil pH, exchange surfaces
are held by hydrogen ions (H+) which causes loss of potassium ion from soil surface
(Brady and Weil, 1999).
251
24-25 March 2015
(a)
(b)
Figure 1: Regression relation between soil pH and soil available phosphorus (a) and
soilavailable potassium (b)
Role of soil organic matter content
Soil organic matter content had significant positive contribution in soil pH (slope =
0.17, soil available phosphorus (slope = 12.90) and soil available potassium (slope =
10.88) (Figure 2). As a buffering agent soil organic matter prevents increment of
hydrogen ion concentration in the soil solution. As a source of plant nutrients it
provides nutrients like phosphorus (Shen et al. 2011) and potassium. Additionally,
organic matter, as a colloidal surface, holds nutrient ions formed from breakdown of
chemical fertiliser inputs which become available for plant use later on (Allison 1973).
252
24-25 March 2015
(a)
(b)
(c)
Figure 2: Regression relation between soil organic matter content and soil pH (a), soil
available phosphorus (b) and soil available potassium (c) content.
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24-25 March 2015
Conclusion and recommendations
Soil organic matter content plays significant role in soil pH maintenance and soil
nutrient availability (especially soil phosphorus and soil potassium). Hence, to
maintain soil organic matter content, farmers should apply adequate amount of
farmyard manure before planting each crop. Declining soil potassium content can be
improved by application of higher amount of potassium fertiliser. Alternately,
potassium fertiliser and ammonium based fertiliser should be applied at different time.
Addition of crop biomass also contributes potassium content in soil.
Acknowledgements
Author acknowledges the contributions made by Late Dr. Ek Mohan Bhattarai and
other scientists who have initiated and continued Long-term experiment in Khajura,
Banke. Author is obliged to former Regional Director, Dr. Yam Raj Pandey for
providing all the support for carrying out the research in RARS Nepalgunj . Author is
indebt to Regional Director, Dr. Ishwori Prasad Gautam for encouragements to
preparing this paper. Author is also grateful to Mr. Sher Bahadur Ale for assisting to
carryout field experiment in Khajura for more than a decade.
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Establishment method effects on crop performance and water productivity of
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and water effects on productivity, and nitrogen-use efficiency and balance for
rice–wheat sequences of Bangladesh. Field crops research. 72:143-161.
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256
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SF-25
Response of Tribeni Organic Complexal to Potato and Rice
Shree P Vista, Shambhu Raut, Dinesh Khadka, Laxman Lakhe and Bishnu H Adhikary
Abstract
Organic matter is the heart of the soil and it is the foundation of all living entities
in soil. Considering this value as centre point, a research was conducted using
tribeni organic complexal with 8 different treatments and 3 replications in both
potato and rice. The field trial was laid out in Randomized Complete Block
Design in the clayey soils of Khumaltar, Lalitpur. Results revealed that plant
height, no. of stem per plant and tuber yield differed significantly with the
treatments. Plant height and tuber yield were observed highest in the soil treated
with recommended dose of NPK plus 20t FYM ha-1, followed by full dose of
chemical fertilizer plus Tribeni organic complexal (TOC) @675 kg ha-1. High
dose of TOC (1800 kg ha-1) applied without chemical fertilizer showed less
response to yield and other yield attributing parameters.High doses of TOC (1800
kg ha-1) produced 54.7 % higher tuber yield (13.35 t ha-1) compared to those
produced by non-treated control crop (7.31 t ha-1). However, its use with chemical
fertilizer showed good response to crop yield and rest of the parameters. Similarly,
plant height, no. of tillers, grain and straw yield of rice differed significantly with
the treatments. Application of 900 kg ha-1 of TOC along with recommended dose
of chemical fertilizer recorded higher yield of both grain and straw of rice. Hence,
this revealed that 900 kg of TOC can substitute FYM equivalent to10 ton. But sole
application of TOC did not show good result in rice grain production (3.68 t ha-1),
it is almost at par with the control plot (3.45 t ha-1).
Keywords:
Chemical fertilizer, rice production, tribeni organic complexal, tuber
yield.
Introduction
Indiscriminate use of chemical fertilizers has resulted to soil acidity and deterioration
of the soil physical and chemical properties in the present context(Karki and Dacayo
1990). Well decomposed organic manure is said to be as good as lime to buffer soil
acidity as it improves soil physical and chemical properties(Haynes and Naidu 1998,
Yang et al. 2004). Therefore, Ministry of Agriculture Development, Government of
Nepal is promoting organic based fertilizers to restore soil fertility in long run. In this
line, this report is being prepared after testing organic manure supplied by Tribeni BioEnergy for their permanent registration. The product supplied by this agency was
tested initially with potato crop and later with rice crop to study the effect of the
product on these two crops. Organic matter is the heart of the soil and it is the
foundation of all living entities in soil.
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24-25 March 2015
The recommended dose of the product Triveni Organic Manure (TOM) supplied by
Tribeni Bio Energy for potato and rice was 30 kg kattha-1. An experiment was carried
out with 8 different treatments and 3 replications in both potato and rice. The field trial
was laid out in Randomized Complete Block Design in the silt loamsoils of Khumaltar,
Lalitpur. The details of treatments in the said experiments are presented in Table-1.
Table 1: Treatments composition applied in the field experiment.
TN
Potato
1
Control
Rice
Control
-1
2
100:100:60kg N:P2O5:K2O ha +20 t FYM
100:30:30kg N:P2O5:K2O ha-1+10 t FYM
3
100:100:60kg N:P2O5:K2O ha-1+900 kg TOMha-1
4
5
6
7
50:50:30kg N:P2O5:K2O ha-1+1575kg TOMha-1
8
1800 kg TOMha-1
1800 kg TOMha-1
For potato, Janakdev variety was used for the trial. It was planted on 5thFalgun, 2069
(February 16, 2013) and harvested on 22 Baisakh, 2070 (May 5, 2013). Plant spacing
and population were maintained as per the standard. The crop was raised with the best
management practices and all required observations were made as per time and
requirements.Similarly for rice, Khumal-11 variety was planted in the experiment.
Seedlings of 32 days old were transplanted on 14thAshad, 2070 (June 28, 2013) and
harvested on 24thKartik, 2070 (November 10, 2013). All parameters were observed as
per requirements and the data were analyzed using MSTAT statistical packages.
Data of potato and rice are presented in Table2 and Table3, respectively. Plant height,
no. of stem per plant and tuber yield differed significantly with the treatments.
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24-25 March 2015
Table2: Effect of TOM on yield and yield attributing parameters of potato (2069/70).
Treatments
Plant ht, cm
Tubers sq.m-1,
Stem plant-1,
Tuber yield,
nos.
Nos.
t ha-1
d
1
16.67
112.667
4.133
7.310c
a
2
37.33
211.333
4.667
26.93a
3
28.80bc
174.667
5.667
20.26ab
b
4
30.13
181.000
5.933
19.22ab
bc
5
29.07
185.667
5.667
19.17ab
ab
6
33.67
235.667
5.667
22.73ab
cd
7
21.93
156.667
5.667
12.55bc
d
8
21.27
142.667
5.133
13.35bc
Grand Mean
27.36
175.042
5.317
17.69
LSD
9.671
----6.876
P- Value
**
ns
ns
**
CV,%
14.35
23.77
22.36
31.22
Plant height and tuber yield were observed highest in the soil treated with
recommended dose of NPK plus 20t FYM ha-1, followed by full dose of chemical
fertilizer plus Tribeni organic manure (TOM) @675kgha-1. High dose of TOM (@1800
kgha-1) applied without chemical fertilizer showed less response to yield and other
yield attributing parameters (T8). High doses of TOM (1800 kgha-1) produced 54.7 %
higher tuber yield (13.35 t ha-1) compared to those produced by non-treated control
crop (7.31 t ha-1). However, its use with chemical fertilizer showed good response to
crop yield and rest of the parameters (Table 2).
Similarly, plant height, no. of tillers, grain and straw yield of rice differed significantly
with the treatments. Application of 900 kgha-1 of TOM along with recommended dose
of chemical fertilizer recorded higher yield of both grain and straw of rice (T3). Hence,
this reveals that 900 kg of TOM can substitute 10 t of FYM. Application of NPK
fertilizer enhances mineralization organic matter and availability of readily available
nutrients for the potato. Similar results on sweet potato has been reported by
Agbede(2010).But sole application of TOM (T8) did not show good result in rice grain
production (3.68 t ha-1), it is almost at par with the control plot (3.45 t ha-1) (Table 3).
It could be that the nutrient content in the TOM is slowly available to the crop.
Overall Economic Analysis
One kg of TOM cost NRs 20.00 on retail. Farmers can purchase at NRs. 20.0 at any
place within Nepal. Cost of 900 kg of TOM is about 18000 and the cost of FYM per
doko is NRs. 40.0 for 25 kg. Ten ton of FYM will cost around NRs. 16000.0 but
additional labour cost for transportation will exceed NRs. 4000.0 Therefore, TOM can
be comparatively labor efficient to FYM. Hence, it can be recommended for wider
distribution.
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24-25 March 2015
Table3: Effect of TOM on yield and yield attributing parameters of rice (2070/71).
Treatments
Plant ht,cm
86.20c
95.47a
95.40a
95.47a
93.53a
95.53a
91.60ab
87.53bc
92.592
Panicle
length, cm
19.73
20.40
20.47
20.33
19.80
20.27
20.13
19.53
20.08
Tillers
sq.m-1, nos.
185.7b
284.3a
291.0a
273.0 a
274.7 a
267.0 a
236.3ab
185.3b
249.67
Grain Yield,t
ha-1
3.450c
6.920a
6.843a
5.757ab
6.670a
5.780ab
4.740bc
3.687c
5.48
Straw yield,
t ha-1
8.937c
15.38a
16.34a
14.16ab
14.33ab
14.76ab
10.98bc
9.433c
13.04
1
2
3
4
5
6
7
8
Grand
Mean
LSD
P- Value
CV,%
4.32
**
2.66
----Ns
2.52
61.43
**
14.05
1.459
**
15.64
3.841
**
16.82
Conclusion
Since the quantity of FYM in the present context is also a question as well as TOM
response to crop as a supplement with chemical fertilizer showed better response. Low
dose of TOM (900 kgha-1) applied along with recommended dose of NPK fertilizer is
suggested to apply in rice for increased economic rice production. Research evidence
showed that it is not only applicable for increased rice production but also for tuber
production of potato. It does have good effect in crop yield vis-a-vis economical and
hence, it is recommended for wider dissemination and adoption.
References
Agbede TM. 2010. Tillage and fertilizer effects on some soil properties, leaf nutrient
concentrations, growth and sweet potato yield on an Alfisol in southwestern
Nigeria. Soil and Tillage Research.110: 25-32.
Haynes RJ andR Naidu. 1998. Influence of lime, fertilizer and manure applications on
soil organic matter content and soil physical conditions: a review. Nutrient
Cycling in Agroecosystems.51: 123-137.
Karki KB and JB Dacayo. 1990. Assessment of Land Degradation in Southern Lalitpur
of Nepal-Extended Summary. 14th Congress of International Society of Soil
Science. Kyoto, Japan.
Yang C, L Yang, Y Yang and Z Ouyang. 2004. Rice root growth and nutrient uptake
as influenced by organic manure in continuously and alternately flooded paddy
soils. Agricultural Water Management.70: 67-81.
260
24-25 March 2015
3.
SM-1
Nematodes and Soil Fertility
Pradipna R Panta
Natural Resource and Agriculture Management Centre, Balaju, Kathmandu, Nepal
Abstract
Nematodes can be used as bio-indicators of soil health because they are ubiquitous and
have diverse feeding behaviors. A handful of soil contains 50 different species of
nematodes residing in soil
nematodes and millions of individual can occupy in 1 sq.m
that do not feed on higher plants some feed on fungi or bacteria; others are carnivorous or
omnivorous. It is common belief that nematodes are pathogenic but most nematodes are
non-pathogenic and a rich source of organic carbon in marine, freshwater and terrestrial
agricultural practices; they eN hanced microbial activity in soil and play a pivotal role in
decomposition of soil organic matter, mineralization of plant nutrients and nutrient cycle
Bacterial feeding nematodes have a higher carbon: nitrogen (C: N) ratio and while preying
bacteria they take N proportion excessively high than their body structure. The excess in
turn excreted as ammonia The excreted amount is later available in the soil for uptake by
plants and microbes. research was conducted in 1993- 1995 while doing a master thesis
on plant nematodes as well as research on pest disease / Plant quarantine. Soil sample were
collected in the top 15cm of a field soil mineralized. Nematodes were identified using
Baerman Funnel and floatation and sieving method and soil nematodes were classified on
the basis of colonizer-persister (c-p) then determined the rates of N mineralization by
bacterial feeding nematode species of different body size In two years of field experiment
in vegetable and in particularly tomato field of Kathmandu, it is found that N availability in
tomato field eN hanced by an abundance of microbial feeding nematodes. However, the
constraining factor is soil moisture availability. If soil moisture through irrigation or other
means continue we can increase microbial activity and decomposition of crop
residues.There are other constraints and vary with cropping system and climatic condition
but management of soil to enhance activity of bacteria and fungal feeding nematodes can
eN hance soil fertility.
Keywords: Bacteria, bio-indicators of fungi, nematodes, soil fertility, soil health.
Introduction
Nematodes can be used as bio-indicators of soil health because they are ubiquitous and
have diverse feeding behaviors. A handful of soil contains 50 different species of
nematodes and millions of individual can occupy in 1sq m. Of the nematodes residing
in soil that do not feed on higher plants some feed on fungi or bacteria; others are
carnivorous or omnivorous.
It is common belief that nematodes are pathogenic but most nematodes are nonpathogenic and a rich source of organic carbon in marine, freshwater and terrestrial
agricultural practices; they enhanced microbial activity in soil and play a pivotal role in
261
24-25 March 2015
decomposition of soil organic matter, mineralization of plant nutrients and nutrient
cycle (Ingham et al.1985, Hunt et al 1987, Griffiths 1990).
Bacterial feeding nematodes have a higher carbon: nitrogen (C: N) ratio and while
preying bacteria they take N proportion excessively high than their body structure. The
excess in turn excreted as ammonia (Lee and Atkinson 1977, Rogers 1989). The
excreted amount is later available in the soil for uptake by plants and microbes.
Soil sample were collected fromfield soil mineralized. Nematodes were identified
usingfloatation and sieving methods and soil nematodes were classified on the basis of
colonizer -persister (c-p) then determined the rates of N mineralization by bacterial
feeding nematode species of different body size (Ferris et al. 1996, Ferris andLau
1995).
Infield experiment in vegetable and in particularly tomato field of Kirtipur and Thimi,
it is found that N availability in tomato field enhanced by an abundance of microbial
feeding nematodes. However, the constraining factor is soil moisture availability. If
soil moisture through irrigation or other means continue we can increase microbial
activity and decomposition of crop residues. There are other constraints and vary with
cropping system and climatic condition but management of soil to enhance activity of
bacteria- and fungal feeding nematodes can enhance soil fertility.
Decomposed organic materials release nutrients essential for plant uptake. The soil and
food web includes three energy pathways, i.e., root, bacterial and fungal. Energy flow
via living roots rely on herbivores; energy flow via litter and detritus are through a
decomposer food web depending on microorganisms and microbivores. After
decomposition, solid web food divided into either bacterial channel or fungal channel.
Bacterial channel tend to have a faster rates of decomposition than those of fungal
channel.
Soil nematodes occupy key positions and most trophic level in soil food webs and can
be identified easily to trophic groups by morphological and anatomical characteristics.
Bacterivores, fungivores and herbivores are key intermediaries and are representing
distinct pathways.
Decomposition channels based on soil ecosystem type and nutrient forms (C: N ratios)
(Ferris et al.1996, Ingham et al. 1985). Although the bacteria and fungi are primary
decomposers, microbes too can immobilize inorganic nutrient in the soil (Hunt et al
1987). When the bacteriovores and fungivores prey these microbes, they give off
carbon-di-oxide and Ammonia, affecting C and N mineralization (Ingham et al 1985).
Nematodes disseminate microbial population throughout the soil (Freckman 1998) that
assists the colonization of substrates and mineralization of nutrients. Nematode
metabolic activities may also stimulate specific bacterial growth by releasing growth
limiting nutrients such as nitrogen and vitamins. However overgrazing of bacterial or
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24-25 March 2015
fungal population by nematodes can result the reduction of decomposer activities but
predators prey on these bacteriovores and fungivores nematodes, improving nutrient
cycling and allowing more nutrients to be released (Yeates 1994).
Therefore Nematode play a crucial roles in soil nutrient cycling. Nematode do
excretion may contribute up to 19 per cent of soluble N in soil. This is due to the fact
that nematodes (C: N ratio of 8 -12) have a lower N content than the bacterial (C:N
ratio of 3 -4) they consume (Wasilewska 1985). In addition the growth efficiency of
nematode (<25%) is smaller than those of the bacteria (>30 %) (Hunt 1987). Therefore,
nematode excretes a majority of both the assimilated C and N and they consumed from
the bacterial. Bacteria on the other hand, usually respire most of the assimilated C, but
immobilized most of the assimilated N. Therefore, the contribution made by nematodes
to N mineralization is relatively high compared to bacterial soil ecosystem.
Besides its role in N mineralization, the abundance of many free-living nematodes
especially bacteriovores, omnivores, and predatory nematodes, also were found to be
correlate with concentration of many other soil nutrients in fallow field (Wasilewska
and Bienkowski 1995), suggesting the possibility of nematodes mineralizing many
other soil nutrients. The abundance of many bacteriovores genera followed predators
and omnivorous and correlated significantly (p<_ 0.10) with the most soil nutrient
concentration. However, a few significant correlations occurred with genera in
fungivore and herbivore groups.
Field description
The research was conducted at Kirtipur of Kathmandu district and Thimi of Bhaktapur
district. The experimental was design as a split plot with either tillage on bare soil or
tillage followed by surface mulch as wheat straw as main plots and soil amendments
including fertilizers, Dhaicha, barley hay, and swine manure. Soil amendments
treatments were different in Kirtipur and Thimi.
Description of data source, number of study sites and number of samples:
Ecosystem
Number of sites
Plot 1. Cropland
(Kirtipur)
Plot 2.
Cropland(Thimi)
6
Number of
Samples
42
4
16
263
Reference
As per the
prescribed book of
De Goede&
Bongers (1992)
24-25 March 2015
Nematode extraction and analysis
Nematodes were extracted from 500 cm3 of soil, using a combination of a,Oostenbrink
elutriator with 400 mesh sieve and sugar centrifugation (Byrd et al .1976). Total
numbersof nematodes/500 cm3 of soil were identified from each treatment–replicate
combination and nematodes wereidentified to trophic group using esophageal and
general morphology (Bongers and Ferris 1989). Once trophic groupanalyses were
accomplished, samples were preserved, using the hot formalin technique, for
identification to genus.
Maturity indices were calculated (Bongers 1990)MI = __vifi_ /n, Where viis the C-P
value for the nematode family i, fi is the frequency of the nematode family of the
nematodei, and n is the total number of individual nematodes in the sample
Bio- diversity richness
Nematode diversity, andrichness, wasmeasured with following indices:
The Shannon diversity index (H_ = −_Pi (ln Pi ), where Pi is the proportionof the
genus n in the total nematode community,n); the Margalef formula for nematode
communityrichness {Margelef = G−1/ln n}, where G is the totalnumber of genera in
sample, Thus for all indices, genera were used ratherthan species for calculation.
Soil Energy Pathway
To measure the soil energy pathways of crop land ecosystem, percentage of abundance
and percentage of biomass of the bacterivorous, frugivorous and herbivorous
nematodes were calculated. The sum of the percentages of the trophic groups of each
soil sample equals 100%. The calculation of mean nematode biomass (fresh weight,
μg) of each genus in each sample was as follows:
B=
D2/L
1.6*106
Where B is the mean biomass per individual, D is the greatest body diameter (μm) and
L is the nematode length (μm). The values of D and L were measured directly using
Bongers scale.Nematodes were monitored in a decomposition experiment in a tomato
field from planting to harvest.
Nematode Identification
Bacterivorous nematodes were predominant in these tomato field soils (Table 1)
Fungivorous nematodes included the genera A phelenchoidesspp.,Aphelenchusspp.,
Filenchusspp., and occasionallyPsilenchus. Omnivorous nematodes Eudorylaimus,
Prismatolaimus, Aporcelaimus, Mesodorylaimus, observed and occasionally
Tylencholaimus, also reported. Predatory nematodes were rare, and included
Mylonchus. Plant parasitic nematodes were mainly of M. incognita, Pratylenchus,
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24-25 March 2015
Tylenchorhynchus, Hoplolaimusand occasionally Trichodorus, andXiphinema (Table
1)
Table 1: Effect of Sites (Kirtipur and Thimi ) on nematode population.
Plot 1(Kirtipur)
Bacterivores
Rhabditis
Heteroceph
alous
Acrobelus
Plectus
Diplogaster
oidesDiplos
caster
Plant
Parasites
Meloidogyne
Heterodera
Tylenchorhy
nchus
Xiphinema
Paratylenchus
Plot 2(Thimi)
Fungivores Omnivores Predators
Mylonc
Eudoryl
Aphelenc
hus
aimus
hoides
Monon
Mesodor
Filenchus
chus
ylaimus
Tylencho
laimus
Plant
Bacteriv
Parasites
ores
Meloido
Rhabditis
gyne
Heteroce
Heterod
phalous
Acrobelus era
Tylenchorhy
Plectus
Diplogas nchus
Xiphine
teroides
ma
Diplosca
Paratyle
ster
nchus
Fungi
vores
Aphel
encho
ides
Filen
chus
Omnivores
Eudorylai
mus
Mesodoryl
aimus
Tylenchola
imus
Predators
Mylonchus
Mononchus
Number of specific genera change over time soil amendments. Rhabditid and
cephalobid nematode populations were higher initially after amendment of soils with
Hay or swine manure (Table 2 and 3). Populations of Diploscapter spp. were more
abundant in soils amended with swine manure than hay and fertilizers (Tables 2 and 3).
Most of the common bacterivorous nematodes in the Rhabditidae and Cephalobidae
decreased from planting time to harvest in both plots (Tables 2 and 3).Soil fertility
amendments affected gall indices caused by root-knot nematode on tomato roots.
Numbers of bacterivorous nematodes were initially more numerous after soil
amendment with swine manure in soils amended with fertilizers.
Soil amendments
Nematodes were monitored in a decomposition experiment in a tomato field from
planting to harvest. Litter bag containing decomposition materials were buried
underneath soil and biological diversity and nematode richness were compared to
before bag burial (Table 2).
Bacterial feeding nematode population were reached a peak after 3 weeks of bag burial
and N content in the litter bag was reduced, indicates a period that were available for
plant uptake. Thus barely hay, and swine manure enriched the soil ecosystem, ensuring
active nutrient cycling.
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24-25 March 2015
7000
No. of Bacteriovores nematode/500 cm 3
6000
5000
4000
Barley Hay
swine manure
3000
fertilizers
2000
1000
0
Plot iPlantation
Plot1, Harvest
Plot2, Plantation
Plot 2, Harvest
Figure 1: Impact of Soil Amendments.
The incidence of fungivores reached its peak in 10 weeks after bag burial, indicating
residues with a mixture of C:N ratios were available inside the bag initially.
2000
No. of Fungivores nematode/500 cm 3
1800
1600
1400
1200
Barley Hay
1000
swine manure
800
fertilizers
600
400
200
0
Plot iPlantation Plot1, Harvest Plot2, Plantation Plot 2, Harvest
Figure 2: Impact of Soil Amendments.
266
24-25 March 2015
The omnivores population increased significantly but predatory species remain
constant indicates the nutrient and energy transferred to a higher level in the food web.
The succession of nematode in different level after barley hay burial is consistent with
enhanced soil nutrient cycling and energy flow. Thus the amended soil not only furnish
nitroger for plant uptake but also play a role in boosting nematode grazers that can
further mineralize other residues in soil with greater C:N ratios. The herbivores
nematode in the experiment was found significantly lower.
Table 2: Effects of Soil Amendments.
Plot 1(during plantation)
Nematode
c-p
Group
Value
Bacterivores
Rhabditidae
1
Cephalobidae
2
Others
Fungivores
2
Aphelenchoides
Omnivores
Eudorylaimus
4
Mesodorylaimus 5
Others
Parasites
Meloidogyne
3
Tylenchidae
3
Others parasites 3
Fertilizers
Swine
manure
Barley
hay
Plot 1 (during harvest)
Fertilizers
Swine
Barley
manure hay
85
235
2
170
2180
1669
143
505
884
717
36
1078
80
114
12
56
278
230
35
157
122
202
9
207
17
18
160
39
60
29
82
9
102
15
64
12
1
105
31
4
80
17
9
190
29
1820
1500
64
1903
1410
205
1922
1180
208
Table 3:Effect of Soil Amendments.
Plot 2(Plantation)
Nematode
Group
Bacterivores
Rhabditidae
Cephalobidae
Acrobeloides
Others
Fungivores
Aphelenchoides
Othhers
Omnivores
Eudorylaimus
Mesodorylaimus
Others
Parasites
Meloidogyne
Tylenchidae
Others parasites
c-p
Value
Fertilizers
Animal
manure
Dhaicha
Plot 2 (Hharvest)
Fertilizers Animal
manure
Dhaicha
1
2
30
140
610
940
60
240
350
162
460
335
240
212
2
20
113
10
215
10
287
30
137
22
219
38
244
4
5
70
18
90
36
102
43
116
19
130
33
205
87
3
0
0
0
0
0
0
3
5
30
0
33
24
53
103
37
12
19
24
3
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24-25 March 2015
Percentage of nematodes in two plots
The ability of amendments to enhance nematode involved in nutrient cycle was
examined in two plots. The total number of bacterivores nematodes were increased and
more less similar by ammendments (barley hay) in plot 1 (from 11% to 48%) with
relatively short history of vegetable crop rotation and in plot 2 (12% to 47%) with long
history vegetable production. It was also observed that the percentage of fungivorous
nematode were the greatest in plot 2 than plot 1(Table 4).
Table 4: Effects of amendment and time on the percentage of nematodes in different
trophic groups.
Plot 1.
Total Community %
Planting
Amendments Bacteriovore Fungivore
Plant
Others
parasites
(Omnivorous
etc)
Fertilizers
48.49
25.60
20.63
5.27
Swine
83.21
10.52
2.10
4.14
manure
Hay
53.68
35.79
7.5
2.9
Harvest
Fertilizer
5.51
1.49
90.55
2.43
Swine
8.4
5.2
84.43
1.92
Manure
Hay
12.52
3.62
81.15
2.69
Plot 2
Bacterivores Fungivores Plant
Others
Planting
Parasites
Fertilizer
47.38
28.17
0
24.43
Animal
82.06
11.30
0
6.6
Manure
Dhaicha
39.74
36.79
4.87
18.58
Harvest
Fertilizer
62.22
15.72
6.54
15.49
Animal
58.69
15.73
13.86
11.70
Manure
Dhaicha
39.75
24.87
5.60
29.76
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24-25 March 2015
Fertilizers
Swine Manure
Hay
83
53
48
36
26
21
10
2
Bacteriovores
Fungivores
8
5
Plant parasites
4
3
Others
Figure 3: Percentage of Abundance of Nematode in Different Trophic Group.
Fertilizers
Swine Manure
90
6
8
84
Hay
81
13
Bacteriovores
2
5
4
2
Fungivores
Plant parasites
2
3
Others
Figure 4: Percentage of Abundance of Nematode in Different Tropic Group (Harvest).
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24-25 March 2015
Nematode populations were affected by amendments. In this research, rhabditid
nematodes comprised the majority of bacteriovores nematodes after planting but
population decline significantly over ime.Diploscapster population increased
significantly in soils amended with swine manure. Fungivores nematodes were found
in soil with swine and animal manure and barley hay, thus suggesting a bacteria
dominated decomposition food web.
Table 5: Probability values for nematode composition in plot 1 and plot 2.
Trophic
Group
Probability>F (Plot 1)
Amendment Time
Amendment
by Time
Probability>(Plot 2)
Amendment Time
Bacteriovores
Fungivores
Omnivores
Predators
Combined
Maturity
Indexa
Diversity
Index2
Richness3
< 0.01
< 0.01
0.31
0.04
0.01
<0.01
0.28
0.02
0.08
0.01
<0.01
0.30
<0.01
0.032
0.04
<0.01
<0.01
0.22
0.02
<0.01
<0.74
<0.01
0.49
0.14
<0.01
<0.02
0.67
0.19
0.02
<0.01
0.24
<0.01
0.06
0.16
<0.01
0.09
0.79
0.23
0.53
0.44
<0.01
0.03
Amendment
by time
Abundance of M.incognita species occurred with the addition of organic amendments.
This research result is obtained from very short period of time and the susceptibility of
the tomato crop to M.incgnita as majority of researchers have observed that
pratylenchus and M.incognita were not affected by organic soil amendments.Plant
parasitic nematodes (Meloidogyne) unaffected by soil amendmentsTillage did not
affect the nematode community as tillage occurred in both plots twice in a year. But
omnivore’s populations were decreased by cultivation.The patterns of soil energy
pathways were similar whether expressed as relative abundance or relative biomass.
However, the percentage values of bacterivorous biomass in each type of ecosystem
exceeded the percentage values of their abundance. Specifically, both the percentages
of nematode abundance and biomass results suggest that energy pathways are
bacterial-dominated in crop land ecosystems.
In summary, the author identified nematodes associated with crop land of Kirtipur and
Thimi. Also, researcher documented the abundance of nematode in crop land after soil
amendments and bacterial fungal energy pathways. Moreover, the research result
suggests that soil amendments increase omnivorous and predatory nematodes which
are natural enemies to plant parasitic nematodes. Increased predatory nematodes also
increase cycle of plant nutrients. Increased plant growth following manure and
hayamendments observed during the course of research.
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24-25 March 2015
Conclusion
The concept of soil ecosystem management is still at a developmental stage in Nepal.
While the research furnishes the importance of specific nematode genera to ecosystem
processes such as nutrient cycling, the bacteriovores responded quickly after
amendments. It is possible of maintaining a healthy soil ecosystem through the proper
management of nematodes. This research utilized information about below-ground
processes in agro ecosystems. The uses of below-ground ecosystem biodiversity
indices are especially appropriate for agro ecosystems. By utilizing diversity indices,
useful information about the soil food web can be obtained. However, much
information still be added to advance our understanding of soil health for ecosystem
management. So there is a need to combine the nematode research with soil quality
parameters and greater efforts are needed to identify soil amendments that will provide
suppression of plant parasitic nematodes while not reducing population of
bacteriovores and fungivores nematodes important for nutrient cycling.
References
Bongers T.1990. The maturity index: an ecological measure of environmental
disturbance based on nematode species composition. Oecologia. 83: 14–19
Bongers T and H Ferris. 1999. Nematode community structure as a bio-indicator in
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Byrd JD, KR Barker, H Ferris, CJ Nusbaum, WE Griffin, RH Small and CA
Stone.1976. Two semi-automatic elutriators for extracting nematodes and
certain fungi from soil. J. Nematol.8: 206–212.
Ferris H and S Lau. 1995. Respiration and metabolic rates based on carbon dioxide
production. Soil Biol. Biochem. 27: 319-330.
Ferris H, M Eyre, RC Venette and SS Lau. 1996. Population energetics of bacterialfeeding nematodes: Stage-specific development and fecundity rates. Soil Biol.
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Freckman
DW.
1998.Bacteriovorous
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and
organic
matter
decomposition.Agr.Ecosyst.Environ.24:195-217
Griffiths BS. 1990. Microbial-feeding nematodes and protozoa in soil: Their effects on
microbial activity and nitrogen mineralization in decomposition hotspots and
the rhizosphere. Plant and Soil. 164: 25-33.
Hunt HW, DC Coleman, ER Ingham, RE Ingham, ET Elliott, JC Moore, SL Rose, CPP
Reid and CR Morley. 1987. The detrital food web in a shortgrass prairie.
Biology and Fertility of Soils. 3: 57-68.
Ingham RE, JA Trofymow, ER Ingham and DC Coleman. 1985. Interactions of
bacteria, fungi and their nematode grazers: Effects on nutrient cycling and
plant growth. Ecological Monographs. 55: 119-140.
Lee DL and HJ Atkinson. 1977. Physiology of Nematodes. Columbia University Press,
New York. 215 pp. R Marchant and WL Nicholas. 1974. An energy budget for
the free-living nematodePelodera (Rhabditidae). Oecologia. 16: 237-252.
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Rogers WP. 1989. Nitrogenous components and their metabolism: Acanthocephala and
Nematoda. In: M. Florkin, and B. T. Scheer (Editors), Chemical Zoology Vol.
III. Academic Press, New York. Pp. 379-428.
WasilewskaL and P Bienkowski. 1985. Experimental study on the occurrence and
activity of soil nnematodes in decomposition of plant material.
Pedobiologia.28:41-57
Yeates GW, T Boigers, RGM DeGoede, DW Freckman and SS Gerogieva. 1993.
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272
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SM-2
Efficacy of Azolla pinnata in Rice (Oriza sativa L.) Production in the
Central Region of Nepal
Bishnu H Adhikary , Sanukeshari Bajracharya , Robinson Adhikary2,
Kailash P Bhurer3and Shree P Vista
IAAS, Lamjung Campus, Tribhuvan University, Sundabazar, Lamjung, Nepal
3
Regional Agricultural Research Station (NARC), Parwanipur,Nepal
2
Abstract
Azolla pinnata, a floating water fern
and wi dly found in both hills
and
tropical Terai of Nepal, has unique character of fixing di-nitrogen (N2)
in association with Anabaena azollae that can be utilized as a nitrogen
substitute or sometimes can replace chemical nitrogen required to rice crop. A
number of past research evidences prove that Azolla has been found beneficial
for increasing rice yields. Most recently, this species of Azolla has been
collected from different parts of the country and maintained in the Soil Science
Division, NARI, Khumaltar , Lalitpur district and Regional Agriculture
Research Station (RARS), Parwanipur, Bara district of Nepal. Field
experiments of Azolla on rice were carried-out during the year 2014/15 in
Parwanipur, Bara and Khumaltar, Lalitpur with different rice varieties in two
different agro-ecological zones to evaluate the effects of Azolla pinnata in rice
production. Experiments were conducted in a Randomized Complete Block
Design (RCBD) and replicated three times with the plot size of 10 sq. m.
Different six treatments such as combination of Azolla and PK fertilizers,
Azolla application with or without incorporation, NPK fertilizers alone and
crop without any Azolla and fertilizers (control) and with the compost
application. --The results indicated that rice yields were increased with Azolla
application. Highest rice yield (8.07 t ha-1) was produced when the crop was
inoculated with Azolla pinnata (incorporation) along with P2O5 and K2O
fertilizers at 40 and 30 kg ha-1 in Khumaltar condition in Khumal-4variety
which was approximately 25 % higher over the non-treated crop (control plot).
Similarly, highest rice yield (4.4 t ha-1) was produced by Sabitri variety when
the crop was fertilized with 100:40:30N:P2O5:K2O kg ha-1 followed by the crop
inoculated with Azolla (non-incorporation) and 40:30P2O5:K2O kg ha-1 (3.35
t ha-1) which was almost 25 % higher grain yield to those produced by nontreated crop (2.68 t ha-1) in Parwanipur, Bara. The combined analysis of the
two sites result revealed that approximately 12 % yield increment over then
on-treated crop (control) was observed when the crop was inoculated with
Azolla pinnata (incorporated) applied along with 40:30 kg ha-1of P2O5 and
K2O. Similarly, application of Azolla pinnata (non-incorporation) produced
approximately 14 % higher grain yield at the same level of P and K
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24-25 March 2015
fertilization over the control plot.
also
This paper discusses and highlights the importance of Azolla in rice farming in
detail.
Keywords: Azolla pinnata, chemical nitrogen, di-nitrogen, incorporation, rice
yield.
Introduction
Nitrogen (N) as a plant nutrient is generally considered a basic and vital nutrient for
increased growth and grain production of rice (Oriza sativa L.) crop. Nepalese rice
farmers generally use urea-N [ CO. (NH2)2] or ammonium sulphate [(NH4)2.SO4)] to
nurish and fertilize their crops. Nepal imports chemical fertilizers, including Nfertilizer every year from outside the country and pay millions of Dollars for
purchasing them. These fertilizers moreoften difficulty to reach the farmers and
sometimes not available in the cropping season and also, are very costlier. To
overcome from such problems Azolla could be an alternative source of fertilizer-N
which is also considered as Natural source of N-fertilizer which can help replace the
fertilizer-N to some extent and if managed properly it can supplement a big amount of
nitrogen (N) as high as 50 kg N ha-1 with a single crop of Azolla just within a month
or two (Adhikary et al.1997 b). Research evidences have proved that it can increase
rice yields by 50 % only by the use of Azolla alone.
Azolla is considered as a natural N-factory because it can fix atmospheric di-nitrogen
(N2) with the help of Azolla-Anabaena symbiosis. It can be used as a green manure in
rice paddies. It is raised in-situ or ex-situ application and incorporated. It also can be
grown as a dual crop with rice and incorporate at weeding time or non-incorporated till
the rice harvest (Lumpkin and Plucknett 1980). Evidences show that it can accumulate
as high as 10.5 kg N ha-1day-1.Other reports indicated that 2.7 kg N ha-1 day-1 could be
easily produced by Azolla under field condition (Talley et al.1977). Ladha and
Watanabe (1987) studied bio-chemical basis of Azolla-Anabaena symbiosis.
Nitrogenase enzyme which occur in heterocystous cells of Anabaena is capable of
reducing di-nitrogen (N= N) to ammonia (NH3) which is taken-up by the Azolla and
after its incorporation this nitrogen is supplied to the growing rice plants. Lumpkin and
Plucknett (1982) reported that Azolla contains 1.96-5.3 % nitrogen (N), 0.16-1.54 %
phosphorus (P) and 0.31-5.97 % potash (K). Adhikary et al. (1996, 2003) reported that
it can enrich the soil with organic matter (OM) 2.8-2.9 % and 0.19-0.27 % N in soil
after Azolla incorporation. They further reported that Azolla microphylla, a species of
Azolla, can produce as high as 59.2 kg N ha-1from a single crop of Azolla.
In Nepal, Azolla pinnata and Azolla filiculoides are available species which are found
wildly grown across the country which have the potentiality of producing as high as
30.1 kg and 39.1 kg N with a single crop of Azolla, respectively.In past, several
experiments with Azolla on rice were conducted by Soil Science Division (SSD),
NARC, Khumaltar during the years 1991-1994 and reported that application of Azolla
increased rice yields satisfactorily. The experimental results revealed that 57 kg of
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24-25 March 2015
urea-N combined with 10 t ha-1 of Azolla (30 kg N from Azolla) produced the similar
yield to that obtained from 87 kg urea-N (SSD 1993).Split application of phosphorus
(P) on Azolla greatly determines the nitrogen (N) fixation and N content of Azolla
(Adhikary et al 1997a, 1997b). FAO (1988) reported that an extensive survey on
Azolla was conducted in Nepal in the year 1982 and reported that Azolla pinnata was
found wildely occurring in all the mid-hills and Terai regions of Nepal. Experimental
results revealed that Azolla pinnata application increased rice yields by 25 % which
was equivalent to 30 kg urea-N, rice yields increased by 40 % over the control when
the Azolla was incorporated twice during the rice growing period. Adhikary et al.
(2014) reviewed and reported the Azolla production technologies and its utilization in
rice farming in Nepal in detail. Talley et al. (1977) achieved rice yields increased by
112 % over the control crop by incorporating one 60 kg N ha-1 layer of Azolla
filiculoides into the paddy soils.The objective of this experiment was to study and
evaluate the efficacy of Azolla pinnata, an indigenous species to Nepal, in rice in the
two different agro-ecological regions of Nepal.
Field experiments were conducted in the Agronomy farm, Khumaltar and Regional
Agricultural Research Station (RARS), Parwanipur during the year 2014/15 to study
and evaluate the effects of Azolla pinnata and its application methods to the rice crops
(Oriza sativa L). A total of six different combination treatments were taken into the
study. The details of treatments has been shown in the Table 1. Randomized Complete
Block Design (RCBD) with 3 replications was employed in the experiment. Plot ize of
10 sq.m (2 m x 5 m) and spacing of 20 cm x 20 cm (PP x RR) was maintained. All
amount of compost and PK fertilizers were applied basally in the concerning plots but
nitrogen fertilizer (N) was splitted 2 times, one as basal dose and the other as topdress to the rice crop. Azolla @ 300 kg ha-1 was inoculated after transplanting of rice
and was either incorporated at the weeding time (40 days of transplanting) or not
incorporated depending upon the treatments used in the concerning plots. Khumal-4
variety of rice was used in Khumaltar, Lalitpur and Sabitri variety in Parwanipur,
Bara. Plant growth parameters and yield components were taken into the study. All the
studied parameters were analysed statistically following MSTAT package. Azolla
plant samples, soil samples before crop planting and after crop harvest were analysed
at Soil Science Division laboratory at Khumaltar, Lalitpur. Kjeldahl Distillation,
Olsen’s method and Flame Photometer methods were employed for nitrogen (N),
phosphorus (P) and potash (K) analysis.
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24-25 March 2015
Table 1: Different treatment combination used in the field experiment.
Treatm
-ents
Azolla pinnata use
Fertilizer and compost Remark
use
T1
T2
Control (no Azolla).
Azolla applied @300 kgha-1 and
incorporated after one month of
inoculation.
(nonAzolla
@300
kgha-1
incorporation).
Azolla applied @300 kgha-1 and
incorporated after one month of
inoculation.
Azolla not applied.
Azolla not applied.
No fertilizers.
40: 30 kgha-1 P2O5: K2O.
T3
T4
T5
T6
40: 30 kgha-1 P2O5: K2O.
No fertilizers applied.
100:40:30
kgha-1 is the
recommended
dose
of
fertilizer for
rice.
100:40:30 kgha-1N:P2O5:
K2O.
Compost 10 t ha-1
Azolla response in Khumaltar condition
Growth and grain production of rice were observed greatly affected by the use of
different treatments in Khumaltar condition. Plant heights, tiller number, panicle
length, straw yield and grain yields were significantly affected. The highest plant
height of 142.5 was observed when the crop was supplied with Azolla (nonincorporated) along with only P and K fertilizer at 40 and 30 kg ha-1 (T3) followed by
Azolla incorporation at the same level of P and K fertilizers (140.1 cm) (T2). Control
plot produced only 127.4 cm of plant height (T1). The longest panicle (26.4 cm) was
produced by the crop treated only with compost (T6) followed by Azolla incorporation
(T4) but lacked NPK fertilizers (26.3 cm). The shortest panicle length was produced
(24.1 cm) by non-treated control crop (T1). The highest thousand grain wt. (22.7g)
were produced by the crop treated with Azolla (incorporated) applied along with P and
K fertilizer at 40 and 30 kg ha-1 followed by the crop treated with recommended dose
of N:P2O5:K2O fertilizers at 100:40:30 kg ha-1 (20.0 g) (T5). Highest straw yield of 13.4
t ha-1 was produced by the crop treated only with NPK fertilizers (100:40:30 kg ha-1
N:P2O5:K2O) (T5) followed by the crop treated with Azolla (incorporated) along with P
and K fertilizers at 40:30 kg ha-1 (T2). Lowest straw yield (10.4 t ha-1) was produced by
control crop (T1) (Table 2). On the contrary, the highest grain yield (8.07 t ha-1) was
produced by the Azolla treated crop (incorporated) fertilized along with P and K
fertilizer (T2) at 40:30: kg ha-1 followed by the crop (7.92 t ha-1) treated only with full
dose of NPK fertilizers (100:40:30 kg ha-1) (T5). Lowest grain yield (6.97 t ha-1) was
produced by the control crop. No significant differences were observed between Azolla
treated crop, compost or NPK treated crops but were significantly different to that
produced by the control crop.
Azolla response in rice in Parwanipur, Bara condition
The trend in the growth and grain production of rice in Bara was found quite different
in most of the parameters. The highest plant height (108.1 cm) was observed when the
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24-25 March 2015
crop was supplied with full dose of NPK fertilizers (100:40:30 N: P2O5:K2O kg ha-1)
(T5, Table 3) followed by treated with the Azolla (incorporated) applied along with P
and K fertilizers at 40:30 kg P2O5:K2O ha-1 (100.3 cm) (T2) and where Azolla was used
but not incorporated at the same level of P and K fertilizers (99.3 cm) (T3). The highest
tiller numbers (260.7) were produced by the compost treated crop (T6) followed by the
crop treated only with 100:40:30 N: P2O5:K2O kg ha-1.
Table 2: Response of treatments on the plant growth and grain yield of rice at
Khumaltar, Lalitpur during the year 2014/15.
Treatments
Plant
Tillers
Panicle
1000
Straw
Grain
height,
per hill,
length,
grain
yield,
yield,
-1
cm
nos.
cm
weight, g
t ha
t ha-1
T1
127.4 c
365.0 d
24.1 b
18.0 a
10.4 b
6.97 b
T2
140.1 ab
373.3 c
25.3 ab
22.7 a
12.4 ab
8.07 a
T3
142.5a
391.0 ab
26.1 a
19.5 a
11.8 ab
7.72 a
137.7
393.0 a
26.3 a
19.7a
11.3 ab
7.55 ab
T4
abc
391.0 ab
25.3 ab
20.0 a
13.4 a
7.92 a
T5
135.8
384.7 b
26.4 a
18.8 a
11.1 ab
7.70 a
T6
abc
129.9 bc
Grand mean
135.57
383.0
25.61
19.81
11.79
7.66
CV, %
4.68
0.940
2.91
15.12
10.87
4.42
F-test
ns
**
*
ns
ns
*
LSD (0.05)
11.54
6.53
1.35
5.45
2.33
0.614
Means in a column with a common letter(s) are not significantly different at 95 % level of
confidence.
Table 3: Response of treatments on the plant growth and grain yield of rice at
Parwanipur,Bara during the year 2014/15.
Treatments
Plant
Tillers
Panicle
1000
Straw
Grain
height,
per hill,
length,
grain
yield,
yield,
cm
nos.
cm
weight, g
t ha-1
t ha-1
T1
95.1 b
173.7 c
24.0 b
21.0 b
4.2 b
2.68 c
T2
100.3 ab
245.7 a
26.4 ab
23.9 a
5.0 b
2.71 c
T3
99.2 ab
240.3 ab
25.3 ab
25.0 a
6.0 b
3.35 b
96.6 b
193.3 bc
25.0 ab
25.5 a
5.6 b
2.81 c
T4
108.1 a
253.7 a
27 5 a
26.3 a
9.1 a
4.40 a
T5
96.2 b
260.7 a
24 2 b
25.2 a
4.7 b
3.06 bc
T6
Grand mean
99.27
227.8
25.42
24.51
5.81
3.17
CV, %
3.94
11.78
6.43
5.44
16.08
7.66
F-test
*
**
ns
**
**
**
LSD (0.05)
9.14
48.85
2.97
2.42
1.70
0.441
confidence.
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24-25 March 2015
Application of Azolla (incorporated) along with P and K fertilizer (T2) produced 245.7
tillers and Azolla (not incorporated) along with same level of P K fertilizers produced
240 tillers per hill in the rice crop (Table 3). The longest panicle (27.53cm) was
produced by the application of full dose of NPK fertilizers alone (T5) followed by the
crop (26.5 cm) treated with incorporated Azolla applied along with P and K fertilizers
at 40:30 kg ha-1 (T2). The shortest panicle was produced by the compost treated crop
(24.9 cm) (T6) followed by the control crop (24.1 cm) but they were not observed
significantly different in each other for panicle length (Table 3). Highly significant
differences were observed among the treatments in the weight of 1000 grains. The
highest 1000 grain weight of 26.3 g were recorded by the application of NPK alone
(T5) followed by Azolla alone (incorporated) (25.5 g). Highly significant effect of
treatments was observed in straw production. The highest straw yield (9.1 t ha-1) was
produced by the crop treated only with NPK full dose (T5) followed by the crop treated
with Azolla (not incorporated) (6.1 t ha-1)(T3). Non- significant difference was
observed among the treatments in straw production except with the crop treated with
full dose of NPK fertilizers (Table 3). The trend was found quite similar to grain
production too. The highest grain production (4.4 t ha-1) was recorded when the crop
was supplied with full dose of NPK fertilizers (T5) followed by the crop treated with
Azolla (non- incorporated) along with PK fertilizers at 40:30 kg ha-1 (3.4 t ha-1) (T3)
(Table 3). The lowest grain yield (2.7 t ha-1) was produced by the control crop followed
by the crop treated with Azolla (incorporated) applied along with P and K fertilizers
(2.7 t ha-1).
Two sites combined results
There was no significant difference in straw production among the treatments except
the crop treated with full dose of NPK fertilizers. The highest straw yield (11.3 t ha-1)
was produced with full dose of NPK fertilizers (100:40:30 kg N:P2O5:K2O ha-1)
followed by the crop treated with Azolla (not incorporated) applied along with PK
fertilizers at 40:30 kg ha-1 (Table 4). The lowest straw yield (7.4 t ha-1) was obtained in
control treatment (T1) followed by the crop treated only with 10 t ha-1 of compost (8.0 t
ha-1), (T6, Table 4). This trend was quite similar to grain yield. The highest grain yield
of 6.2 t ha-1 was produced by the application of 100:40:30 kg N: P2O5: K2O alone (T5)
followed by the crop treated with non-incorporated Azolla along with P and K
fertilizers at 40:30 kgha-1 (5.5 t ha-1). The lowest grain yield (4.8 t ha-1) was produced
by non-treated crop followed by incorporated Azolla (5.2 t ha-1)(T4) (Table 4). The
highest yield increment of 27.8% over the control crop was observed followed by
Azolla (non-incorporated) applied along with P and K fertilizers (14.7%). Application
of Azolla (incorporated) along with PK fertilizers produced only a yield increment of
11.8% over the non-treated control crop followed by the crop treated only with 10
t ha-1 of compost (11.6%) (T6, Table 4). Soil test results indicated that Khumaltar soils
are found better in nutrient and OM content to those of Parwanipur soils (Table 5).
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Table 4: Combined analysis for the response of treatments on straw and grain yield of
rice during the year 2014/15 (means of Parwanipur and Khumaltar)
Treatments
T1
T2
T3
T4
T5
T6
Grand mean
CV, %
F-test
LSD (0.05)
Straw yield, t ha-1
7.38 b
8.74 b
8.95 b
8.52 b
11.30 a
7.95 b
8.80
12.74
**
1.49
Grain yield, t ha-1
4.82 c
5.39 b
5.53 b
5.18 bc
6.16 a
5.38 b
5.41
5.44
**
0.502
Yield increment, %
00.00
11.82
14.73
7.46
27.80
11.61
confidence.
Table 5: Soil Test results of the experimental plots before crop Planting and after crop
harvest at Khumaltar and Parwanipur, Bara.
Treatments
T1
T2
T3
T4
T5
T6
Composite sample
Azolla plant
Organic matter,
%
2.99 (1.42)
2.95 (0.82)
3.41 (1.21)
3.91 (0.76)
3.12 (1.02)
3.50 (0.91)
NA
NA
Nitrogen,
%
0.13 (0.07)
0.13 (0.06)
0.14 (0.07)
0.15 (0.07)
0.13 (0.07)
0.13 (0.07)
0.125 (0.06)
Phosphorus,
kgha-1
149.3 (115.3)
174.3 (112.6)
170.6 (111.6)
133.3 (98.0)
129.3 (132.6)
150.6 (111.3)
146 (191)
Potassium,
kgha-1
344.3 (142.3)
272.3 (137.6)
294.6 (169.6)
335.3 (169.3)
353.0 (209.6)
320.3 (160.3)
358.0 (277.0)
Conclusion
The results of this investigation revealed that Azolla could be an alternative
supplementary source of fertilizer-N. Further, Azolla alone can increase rice yield at
least by 12-14% without any additional fertilizer-N but recommended dose of P and K
fertilizers are needed to meet the nutrient requirement of the crop. Results also
indicated that applications of 10 t ha-1 of compost alone on rice was comparable with
Azolla applied rice crops either incorporated or non-incorporated at the recommended
level of P and K fertilizers. Research from this experiment and other evidences
indicated that farmers are advised to apply Azolla in their rice fields along with 50% of
recommended dose of N and full dose of P and K fertilizers. Azolla could play a vital
role as a natural -nitrogen source in organic rice farming which is better than other
green manuring crops for paddy under adequate water management.
Acknowledgement
Authors are very grateful to Renuka Shrestha, Chief, Agronomy Division, NARC for
her sincere support in conducting the experiment in Khumaltar. Similarly, the staffs of
RARS Parwanipur site who were involved in this experiment are highly acknowledged
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for their tireless work in completing overall works of this experiment. Mr. Shree
Krishna K.C. (Technical Officer) from SSD Khumaltar, Lalitpur is highly appreciated
for his dedicated works in conducting and supervising the field works of this
investigation.
References
Adhikary BH, RC Gauli, BB Baniyahhetri and DB Ranabhat. 2003. An overview of
Azolla utilization and its importance in rice production. Pp. 247-253. In: Proc.
of the 23rd National Summer Crops Research Workshop. Rice Research
Reports. National Rice Res. Program, NARC, Hardinath, Dhanusha, Nepal
held on 2-4 July, 2002.
Adhikary BH, T Attananda, P Swatdee, S Vangnai and P Sripichitt.1996. Enhancing
effect of nitrogen and phosphorus on Azolla microphylla in rice production in a
acid sulphate soil. Kasetsart J. (Nat.Sci.). 30 (4): 539-546.
Adhikary BH, T Attananda, P Swatdee, S Vangnai and P Sripichitt. 1997b. Effects of
Azolla cultivation methods and phosphorus on Azolla microphylla and its
effect on rice. Pp. 215-225. In: Proc. of the 35th Kasetsart University
Conference. Bangkok, Thailand.
Adhikary BH, T Attananda, P Swatdee, S Vangnai and P Sripichitt. 1997a. Growth and
nitrogen production rates of Azolla microphylla as affected by its cultivation
methods. An economic perspective in rice cultivation in Thailand. Kasetsart J.
(Nat.Sci.). 31:134-140.
Adhikary BH; MK Thakur; Robinson Adhikary and Santosh Neupane. 2014. A review
on Azolla production and utilization in rice farming in Nepal. Pp. 266-276. In:
Proc. of the 27th Nat. Sum. Crops Res. Workshop. Giri et al. (eds.), NARC held
on 18-20 April 2013 held at National Maize Research Program, Chitwan,
Nepal.
SSD. 1993. Soil microbiology and bio-fertilizer programme. Pp. 44-50. In: Annual
Report for the year 1992/93. Soil Science Division, NARC, Khumaltar,
Lalitpur, Nepal.
FAO.1988. Biofertilizers: Azolla.Bio and organic fertilizers: prospects and progress in
Asia. RAPA, FAO, Bangkok, Thailand. Pp. 37-42.
Ladha JK and I Watanabe. 1987. Biochemical basis of Azolla-Anabaena azollae
symbiosis. Pp 47-57. In: Proc. of the workshop on Azolla use. Azolla
utilization. Held on 31 March – 5 April, 1985. Fujian, China.
Lumpkin TA and DL Plucknett. 1982. Azolla as a green manure use and management
in crop production. 230 p.
Talley SM, BJ Talley and DW Rains. 1977. Nitrogen fixation by Azolla in rice fields.
In Alexander Hollaender (ed.), Genetic Engineering for nitrogen fixation,
plenum press, Newyork. Pp. 259-281.
Lumpkin TA and DL Plucknett. 1980. Azolla: Botany, physiology and use as a green
manure. Eco.Bot.34: 111-153.
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SM-3
Symbiotic Characterictics of Nepalese Bradyrhizobium Isolates from
Soybean (Glycene max) and Mungbean (Vignaradiata) Crops
Chandra P Risal1 and Balaram Rijal 2
1
Senior Soil Scientist, Soil Management Directorate, Hariharbhawan, Lalitpur
2
Soil Scientist, Soil Management Directorate, Hariharbhawan, Lalitpur
Abstract
Symbiotic nitrogen fixation is the main route for sustainable input of nitrogen into
ecosystems. Nitrogen fixation in agriculture can be improved by inoculation of
legume crops with suitable rhizobia. Knowledge of the biodiversity of rhizobia and
of local populations is important for the design of successful inoculation strategies.
Soybeans and mungbeans are major nitrogen-fixing crops in many parts of the world
including Nepal. The strains with vigor symbiotic characteristics and efficiencies are
more important for inoculation from sustainable agricultural perspectives. The
subject of symbiotic effectiveness and competitiveness of rhizobia in Nepalese
context assumes more significance as it has diverse topographic and climatic
describe the symbiotic effectiveness of native
conditions. In this study,
soybean and mungbean nodulating Bradyrhizobium from different agro-ecological
regions in Nepal. We found 10 genotypes among the soybean Bradyrhizobium strains
and 11 genotypes among the mungbean Bradyrhizobium strains in different Regions of
Nepal. Of all the population of Bradyrhizobium strains studied, we found 28 % strains
produced novel phylogenetic origin. Furthermore, 80 % of the novel strains originated
from the Hill and Mountain regions with more than 1500 m asl altitude level. We
found native B. yuanmingense strains isolated from mungbean (Vigna radiata cv.
Kalyan) plant root nodules were effective symbiotic partner of mungbean plant.
However, the same species isolated from soybean (Glycine max cv. Cobb) root nodules
were not effective symbiotic partner of soybean plant.
Keywords:
Bradyrhizobium, mungbean, nitrogen fixation, soybean symbiotic
efficiency.
Introduction
Soybean and mungbean are the main legume crops in Nepal. However, the average
yield is much lower than the world average, and improving crop performance is a
major challenge. The effectiveness of symbiotic N2 fixation might be an important
factor for increased productivity through successful management of the soybean and
native bradyrhizobia symbiosis. Vinuesa et al.(2008) characterized Bradyrhizobia from
soybean cultivated at two sites in the humid temperate climate zone in Nepal, and
showed that all isolates were members of highly epidemic and well differentiated B.
japonicum of the DNA homology group Ia. In thispaper, we describe the symbiotic
characteristics of native soybean and mungbean nodulating Bradyrhizobium from
different agro-ecological regions in Nepal. We suppose our results will be useful for
the development of effective bio-fertilizers.
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The symbiosis between rhizobia and legume are a cheaper and usually more effective
agronomic practice for ensuring an adequate supply of N for legumebased crop
(Zahran 1999, Risal et al 2010) and thus can play a significant role in improving the
fertility and productivity of soils. Identification and selection of effective rhizobial
strains are important for preserving them for future research. Since, the host–
Rhizobia relationship is more complicated (Lohrke et al 1995) and is affected by
several factors, the variation in the Inoculants performance is often
encountered.Differences
between
Bradyrhizobium strains
regarding
their
effectiveness with different soybean genotypes have been reported by several
workers (Okereke et al. 2001, Tien et al. 2002, Mahna 2006).
Better N2 fixation can be achieved by selecting superior rhizobia. However, selection
of these rhizobia would need to take into consideration not only their N2-fixing
capacity, but also competitive ability against native rhizobia which are frequently
ineffective in N2-fixation. Superior N2-fixing strains have to compete with native
rhizobia and occupy a significant proportion of the nodules. For this to be achieved,
rhizobia have to be selected under natural conditions in competition with the native
rhizobia. The subject of symbiotic effectiveness and competitiveness of rhizobia in
Nepalese context assumes more significance as it has diverse topographic and
climatic conditions in a relatively confined spaces. However, in Nepal, most of the
rhizobial research has been confined to the fast growing rhizobia (Maskey et al.
2001, Neupane 2003) while little attention has been paid to the studies on slow
growing Bradyrhizobia of soybean and mungbean despite being an important
summer legume crop. As a consequence, symbiotic potential of the Bradyrhizobia
autochthonous to different soybean and mungbean growing regions of Nepal is still
unexploited. In the context of these views, in the current investigation, collection of
soil samples from soybean and mungbean cropping fields from different agroecological regions of Nepal was carried out, and Bradyrhizobia were isolated and
authenticated. The main objective of the present study was to evaluate symbiotic
effectiveness of native Bradyrhizobial isolates from Nepal by performing greenhouse
experiment.
Soil samples were collected in 2009 from seven areas in which soybean and mungbean
had been cultivated previously. These seven areas were located in three agro-ecological
regions with contrasting climates (Figure 1). Each soil sample was a composite mixture
prepared by mixing soils obtained from 0–20 cm depth of at least eight places at each
sampling field. No bacterial inoculations have been carried out in these areas, and
therefore the strains were considered to be native to Nepal. The details of the sampling
sites and chemical properties of the soil samples are shown in Table 1. Nepalese local
cultivar Cobb of soybean and Kalyan of mungbean has been used as a trap plant.
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N
CHINA
NEPAL
Sample 6
Sample 5
Sample 4
Sample 3
Sample 2
Sample 0
Sample 1
INDIA
Figure1: Map of Nepal showing the location of soil sample collection sites.
Seeds of Glycine max cv. Cobb and Vigna radiata cv. Kalyan (local Nepalese
varieties) were surface-sterilized by immersion in 70% ethanol for 30 s, and then in
3% sodium hypochlorite solution for 3 min. Seeds were then exhaustively washed
with sterile water. We used five-fold dilutions of soil suspensions as inoculants.
Inoculant (5 ml jar-1) was applied to sterilized vermiculite medium in 300-ml glass
jars prior to sowing two surface-sterilized seeds. After sowing seeds, the jars were
transferred to a growth chamber. Sterilized N-free nutrient solution was added to the
jar up to the 60% moisture level and was maintained at this level throughout the
growth period. Plants were grown for 4 weeks in the growth chamber under a 16 h
lights (28 °C)/8 h dark (18 °C) photoperiod. After 4 weeks, whole plants were
removed from the medium, washed in running tap water to remove vermiculite, and
the root nodules were harvested. Root nodules were surface-sterilized by immersion
in 70% ethanol for 30 s and then in 3% sodium hypochlorite for 3 min, and then were
washed five times with sterile water. Each nodule was crushed in 200 µl glycerol
solution (15% v/v) to obtain a turbid suspension. An aliquot (10 µl) of the suspension
was streaked onto 1.5% Yeast Extract Mannitol (YEM), agar plates and incubated for
1 week at 28 °C. Well separated single colonies were restreaked onto fresh plates to
obtain pure cultures. These isolates were reinoculated onto the host plant to verify
their nodulation ability.
List of Bradyrhizobium strains, from different agro-ecological regions of Nepal, used
in this study has been listed in Table 2. Isolates were grown in 15 ml YEM broth for
1 week with shaking. Bradyrhizobia cells at a density of 1.2 × 1010 CFU were applied
to sterilized vermiculite medium containing respective host seeds. Plants were grown
in axenic conditions in the growth chamber as described above.
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Table 2: List of Bradyrhizobium strains isolated from native legumes and gene
sequencing performed.
Strain name
C1, C2, C3, C4, C5
C6, C7, C8, C9
C10, C11, C12
C13, C14, C15, C16, C17, C18
C19, C20, C21, C22, C23, C24
T1, T2, T3, T4, T5, T6, T7, T8, T9,
T10, T11, T12, T13, T14, T15, T16
H1, H2, H3, H4, H5, H6
H7, H8, H9, H10, H11,H12, H13, H14,
H15,H16
M1, M2, M3, M4, M5, M6, M7, M8,
M9, M10, M11, M12
M13, M14, M15, M16
Host plant
Glycine max cv.
Cobb
''
"
''
"
''
"
''
"
Vigna radiata cv.
Kalyan
''
"
''
"
''
"
''
"
Agro-ecological regions
Sub-tropical Hill (1935 m asl)
Temperate-Mountain (2660 m
asl)
asl)
Tropical-Terai (100 m asl)
asl)
asl)
After harvesting root nodules, nodule number, nodule fresh weight, and shoot weight
were determined. Plant shoots and root nodules were dried at 80 °C for 48 h to
determine dry weight and were powdered for analysis of total N by the indophenol
method.
The ability of a plant to fix N2 was assessed by acetylene reduction activity (ARA)to
determine the presence of an effective nitrogenase enzyme. Plants grown at growth
chamber as described before were uprooted after four weeks. Roots were washed with
running tap water to remove vermiculites in the roots. The root portion separated from
shoot was placed into 300 ml air tight glass jar. Acetylene was injected into each
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jarcontaining root intact nodules to give a final concentration of 10% v/v.Jars were
incubated for one hour at 28°C. After one hour, 1 ml air sample from the glass jar was
sampled and analysed for ethylene (C2H4) content. Ethylene was analysed by standard
flameionisation N-porapak column gas chromatography (Shimadzu GC8A)
standardised with pureethylene and results expressed as μmol of C2H4 produced per
hour per gram of dry nodules. The nodules detached just after ARA measurement were
dried at 80°C for 48 hours to measure the nodule dry weights.
All soybean and mungbean isolates produced root nodules when inoculated onto
seeds of their original host plants to verify nodulation ability. No nodules were found
on the uninoculated plant roots. For accessing the nodulation characteristics of the
isolates, we determined nodule numbers per plant and their dry weights. The results
of nodule number per plant and their dry weights produced by soybean isolates in
their original host plant have been shown in Figure. 5.1 and Figure. 5.2, respectively.
Result shows, different isolates have different ability to form root nodules. The
average nodule number per plant was 22.2 (Figure. 5.1). The highest nodule number,
48 nodules per plant, was obtained from C18 strain inoculated plant. And, the lowest
nodule number, 14 nodules per plant, was obtained from C3 and C12 strain
inoculated plant. Result of nodule dry weight per plant was also different for
different isolates with average of 35.4 mg plant-1 (Figure. 5.2). The highest nodule
dry weight, 65.5 mg plant-1, was obtained from C14 strain inoculated plant. And, the
lowest nodule dry weight, 12.3 mg plant-1, was obtained from C12 strain inoculated
plant.
The results of nodule number per plant and their dry weights produced by mungbean
isolates in their original host plant have been shown in Figure. 5.3 and Figure. 5.4,
respectively. The average nodule number per plant was 60.4 (Figure. 5.3). The
highest nodule number, 110 nodules per plant, was obtained from T16 and M16
strain inoculated plant. And, the lowest nodule number, 17 nodules per plant, was
obtained from H3 strain inoculated plant. Result of nodule dry weight per plant was
different for different isolates with average of 27.3 mg plant-1 (Figure 5.4). The
highest nodule dry weight, 53.0 mg/plant, was obtained from T16 strain inoculated
plant. And, the lowest nodule dry weight, 13.2 mg plant-1, was obtained from H3
strain inoculated plant.
Nitrogen fixation by Nepalese Bradyrhizobia
All soybean and mungbean isolates produced effective root nodules when inoculated
onto seeds of their original host plantsand they showed various levels of atmospheric
nitrogen fixation. No nodules were found on the uninoculated plant roots. For
accessing the nitrogen fixation characteristics of the isolates, we determined
Acetylene Reduction Activity (ARA) of the nodules and shoot Nitrogen content of
the plant. The shoot N content of the soybean plant inoculated with Bradyrhizobium
strains from the same host has been shown in Figure. 5.5. Result shows, different
isolates produced different levels shoot N content. The average was 3.28% N. The
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24-25 March 2015
highest shoot N content (3.79%) was produced by C15, and the lowest N ( 2.05%),
was produced by C21. Isolate C21 showed it’s affiliation with B. yuanmingense, with
well differentiated nifD genes. Symbiotic efficiency of the soybean isolates were
derived as shown in Figure. 5.6. Result shows, different isolates have different levels
of symbiotic efficiency. The highest symbiotic efficiency (43.7 %) was obtained
from C1 strain inoculated plant. And the lowest(14.0 %) was obtained from C12
strain inoculated plant.
The results of shoot N content of mungbean plant and the ARA of root nodules by
mungbean bradyrhizobia in their original host plant have been shown in Figure. 5.7
and Figure. 5.8, respectively. The average ARA of mungbean bradyrhizobia was
51.5μmol hr-1g-1 dry nodule. The highest ARA, 84.8 μmol hr-1g-1 dry nodule, was
obtained from H10 strain inoculated plant. And the lowest ARA was 14.9μmol hr-1g-1
dry nodule, obtained from M3 strain inoculated plant (Figure 5.8).
Symbiotic effeciency of Nepalese Bradyrhizobia
We arranged the symbiotic efficiency of Nepalese soybean bradyrhizobia in the
descending order to describe theie symbiotic effectiveness (Figure. 5.9). The top five
better performers are as follows:
C2, isolated from sub-tropical Hill region.
C16, isolated from temperate Mountain region.
C1, isolated from sub-tropical Hill region.
We also arranged the ARA and total shoot N accumulation in mungbean plant
inoculated with different Nepalese mungbean bradyrhizobia, in the descending order,
to describe theie symbiotic effectiveness (Fig. 5.10). The top five better performers
are as follows:
H10, isolated from sub-tropical Hill region.
T15, isolated from tropical Terai region.
M11, isolated from temperate mountain region.
Host specificity of Nepalese bradyrhizobia
We used mungbean (Vigna radiata), cowpea (Vigna unguiculata), soybean (Glycine
max), alfalfa (Medicago sativa), and wild soybean (Glycine soja) plant to test the
host specificity of mungbean bradyrhizobia. All of them could not nodulate alfalfa
plant. However, we found some strains nodulated G. soja while some could not.
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Conclusion
The results of the plant test suggested that expression of different symbiotic genes in
these isolates resulted in different degrees of symbiotic performance. Our results
suggest that B. japonicum and B. elkaniiare more efficient symbiotic partners than B.
yuanmingense for the local soybean cv. Cobb. Similarly B. yuanmingenseand novel
strains are more efficient symbiotic partners than B. elkanii for the local mungbean cv.
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Kalyan, cultivated at high altitudes of Nepal. However, symbiotic performances in
legume-Rhizobium symbioses have been reported to be cultivar-dependent (Shutsrirung
et al. 2002, Sarr et al. 2009). Therefore, further investigations including different
cultivars and reference strains are required. Such data will be useful for selecting the
best candidate for bio-fertilizer inoculants suitable for soybean and mungbean
cultivation at different agro-ecological regions in Nepal.
References
Jones JB. 2001. Laboratory Guide for Conducting Soil Tests and Plant Analysis. Pp.
191-239.
Jordan DC. 1982. Transfer of Rhizobium japonicum Buchanan 1980 to
Bradyrhizobium gen. nov., a genus of slow growing root nodule bacteria
from leguminous plants. Int. J. Syst. Bacteriol. 32: 136-139.
Lohrke SM, JH Orf, E Martinez-Romero, MJ Sadowsky. 1995.Host-controlled
restriction of nodulation by Bradyrhizobium japonicumstrains in serogroup
110. Appl.Environ. Microbiol.61: 2378–2383.
Mahna SK. 2006. Individual Partner Report. INCO-DEV ResearchProject on Soybean
BNF and Mycorrhization for ImprovedProduction in South Asia.
Department of Botany, MaharshiDayanand Saraswati University, Ajmer,
India.
Maskey S, S Bhattarai, MB Peoples, DF Herridge. 2001. On-farm measurement of
nitrogen fixation by winter and summer legumes in the Hill and Terai
regions of Nepal. Field Crop Res. 70:209–221.
Neupane RK. 2003. Highlights of summer grain legumes research 2000-2002,Pp 1-5.
In: Proc.23rd National Summer Crops Research Workshop (Grain
Legumes),held at NARC, Khumaltar on 2-3 June 2002. National Grain
LegumesResearch Programme, Rampur, Nepal.
Okereke GU,C Onochie, E Onyeagba. 2001. Effectiveness offoreign bradyrhizobia
strains in enhancing nodulation, dry matterand seed yield of soybean
(Glycine max L.) cultivars in Nigeria.Biology and Fertility of Soils. 33: 3–9.
Risal CP, T Yokoyama, N Ohkama-Ohtsu, S Djedidi, H Sekimoto. 2010. Genetic
diversity of native soybean bradyrhizobia from different topographical
regions along the southern slopes of the Himalayan Mountains in Nepal.
Syst. Appl. Microbiol. 33:416-425.
Sarr PS, T Yamakawa,S Fujimoto, Y Saeki, HTB Thao, AK Myint. 2009.
Phylogenetic Diversity and Symbiotic Effectiveness of Root-Nodulating
Bacteria Associated with Cowpea in the South-West area of Japan, Microb.
Environm. 24: 105–112.
Shutsrirung A,P Sutigoolabud, C Santasup, K Senoo , S Tajima, M Hisamatsu, A
Bhromsiri,. 2002. Symbiotic efficiency and compatibility of native rhizobia
in northern Thailand with different soybean cultivars. Soil Sci. Plant Nutri.
48: 491-499.
Tien HH, TM Hien, MTSon, D Herridg.2002. Rhizobialinoculation and N2 fixation of
soybean and mungbean in theEastern region of South Vietnam. In:
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Proc.ofACIAR. Inoculantsand Nitrogen Fixation of Legumes in Vietnam.
Pp. 29–36.
Vinuesa P, K Rojas-Jiménez, B Contreras-Moreira, SK Mahna, BN Prasad, H Moe, SB
Selvaraju, H Thierfelder, D Werner. 2008. Multilocus sequence analysis for
assessment of the biogeography and evolutionary genetics of four
Bradyrhizobium species that nodulate soybeans on the Asiatic continent.
Appl. Environm. Microbiol. 74:6987–6996.
Zahran, HH.1999.Rhizobium–legume symbiosis and nitrogenfixation under severe
conditions and in an arid climate. Microbiologyand Molecular Biology
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SM-4
The Trichoderma spp.: A Biological Control Agents from Nepalese Soil
Ram D Timila, Shrinkhala Manandhar, Chetana Manandhar, and Baidhya N Mahto
Plant Pathology Division (NARC)
, Nepal
Abstract
Soil-borne diseases are the cause of severe losses of economically important crops.
Chemical pesticides have been widely used for several decades to control soil-borne
pathogens. As far as health and environment concerns, application of biological control
agents is one of the eco-friendly alternative approaches to chemical pesticides. In this
context, soil is the reservoir of different biological control organisms. Trichoderma spp.
are the most commonly using biological control agents iN habiting in various types of soil.
Efforts have been made for isolation of Trichoderma spp. from soil samples collected
from the fields cultivated with different crops. Ninty isolates of Trichoderma spp. have
been isolated either by direct soil plating or by serial diluton plate technique on potato
dextrose agar medium. Of them, twenty three isolates were tested for their biological
control efficacy against Rhizoctoniasolani and Sclerotiniasclerotiorum in dual culture.
Four isolates showed bio-control efficacy with zone of inhibition formation with S.
sclerotiorum and two with R.solani. Most of the isolates showed masking effects with both
pathogens.Two local isolates, T. harzianum and T. asperellum found to be effective to
reduce club-root disease in the field. However with other isolates, in vivo/field testing is
required to confirm their degree of efficacy. Exploration of such potential BCAs from soil
of different cropping system should be continued as the strategic plan, in addition to mass
multiplication and field efficacy testing of promising Trichodermaspp. identified to
discourage the use of chemical pesticides.
Keywords: Biological control agent club-root disease, soil-borne diseases,
Trichoderma.
Introduction
Soil microorganisms are the most abundant of all the biota in soil and responsible for
driving nutrient and carobone cycle, soil fertility, soil restoration, plant health and
ecosystem.The microbial communityis an important parameter of soil health.
Microbial community contain both pathogenic as well as beneficial microbes.
Beneficial microorganisms include those that create symbiotic associations with plant
roots (rhizobia, mycorrhizal fungi, actinomycetes, diazotrophic bacteria), promote
nutrient mineralization and availability, produce plant growth hormones, and are
antagonists of plant pests, parasites or diseases (biocontrol agents). Reduction of
chemical pesticide usage, including chemicals for control of soil-borne plant
pathogens, is widely recognized as a desirable goal for agriculture.Many of these
organisms are already naturally present in the soil, although in some situations it may
be beneficial to increase their populations either by inoculation or by applying various
agricultural management techniques that enhance their abundance and
activity.Deteriorated soil health may have high population of soil borne pathogens,
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24-25 March 2015
however it may depend on cropping pattern and tillage practices. Fungal populations
dominate in untilled or no till soilswhile bacteria and actinimycetes in tilled soil
(Hoorman and Islam 2010).
As soil is the reservoir of potential biological control agents (BCAs) which play a key
role as the basic component insuppressiveness of the soil, which is the healthy
soil.Suppressive soil basically contain enough beneficial micro-organisms with enough
organic matter. Soil suppressive phenomenon explains the biological control
mechanism (Mehrotra et al. 1997) which is one of the promising tools for integrated
disease management. It is an ecofriendly alternative approach to the chemical
pesticides. The Biological control mechanism involves:
•
•
•
•
•
Mycoparasitism and hyphal lysis
Antibiosis and inactivation of pathogens’ enzymes
Competition
Enhancement of root development
Induced resistance
The ecological equilibrium between pathogen and BCAs suppress soil-borne diseases.
Certain organisms have received considerable research attention as potential biocontrol
agents. One of the most well studied and documented of these is the fungal
genus Trichoderma.
Some documented BCA candidates for plant pathogens
•








Trichodermaspp.,
T. viride, T. harzianum,T. hamatum, T. koningii
Gliocladiumvirens, G.roseum,
Paecilomycesliiacinus,
Heteroconiumsp.,
Coniothyrumminitans.
Pythiumolygandrum,
Bacillus subtilis, B. polymyxa
Pseudomonas fluorescens
Trichoderma spp. as BCA
Trichoderma spp. have received considerable attention as potential biological control
agents against a wide range of soil-borne plant pathogenic fungi. It is also effective
against seed-borne diseases of various crops. It is a free-living well documented
antagonistic fungus which is common in soil and root ecosystems. It is highly
interactive in root, soil and foliar environments. It reduces growth, survival or
infections caused by the pathogens through different mechanisms like competition,
antibiosis, mycoparasitism, hyphal interactions, and enzyme secretion (Singh 2010). It
is highly ecologically successful fungi and have been used increasingly in commercial
agriculture (Knudsenand Dandurand 2014). For health hazards and adverse effect on
environment concerns, application of biological control agents have been appeared as
295
24-25 March 2015
one of the ecofriendly alternative approaches to chemical pesticides to combat soil and
seed- borne diseases. In this context, testing of Trichoderma for disease management
have been attempted since last many years at Plant Pathology Division. But a regular
work has been started on biological control with the establishment of 'Biological
Control Unit ' at the Division during the fiscal year 2068/69 BS (2011/012). Emphasis
has been given on the exploration of native Trichoderma spp. for biological control of
important soil-borne pathogens
Soil sample collection
Soil samples were collected from the fields with different crops, especially vegetable
crops. Rhizospheric region of the crop plants wastargeted for collecting soil from 0- 10
cm depth. Samples were put in plastic bags and were brought in the laboratory. The
samples were preserved in refrigerator until use.
Isolation of Trichoderma spp.
Each sample was made fine by grinding. Fifty five and fifty two soil samples were
processed during 2012/13 and 2013/14, respectively. Similarly 31 samples were
processed during 2011/12 for the isolation ofTrichoderma spp.
Direct soil plating
Direct soil plating was done by dusting small amount of the fine sample on the surface
of potato dextrose agar (PDA) medium with or without antibiotic (Streptomycin
sulphate, 100 ppm )or modified Trichoderma selective medium (TSM) (Elad et al.
1981). The ingredient namely p-dimethylaminobenzenediazo sodium sulfonate was
excluded in TSM medium. The plates were incubated at 24oC at inverted position for 4
- 6 days.
Serial dilution
Serial dilution methods was adopted for some of the samples. In this method 10 g of
fine soil from the sample was mixed in 90 ml sterile distilled water and shaken in
conical flask for half an hour. An aliquots of 1ml of the suspension was drawn and
mixed with 9 ml sterile distilled water from where 1 ml mixed with another 9 ml sterile
distilled water. In this way a series of dilution was prepared to give the concentration
of 10-1,10-2,10-3 and 10-4 . From each dilution, aliquot of 0.1 ml was dispended on PDA
or TSM medium plates and spread to dry by means of triangular head glass rod. Two
plates per each dilution were used as replicates. The plates were incubated at 24oC26oC at an inverted position for 4 - 6 days.
Isolation and maintaining pure cultures of selected soil-borne pathogens
Plant samples of cauliflower, cabbage and tomato infected by Sclerotiniasclerotiorum,
Rhizoctoniasolani and Fusariumsolani respectively with typical symptoms were
collected. The pathogens were isolated using 2% water agar and pure culture
maintained and preserved in PDA slants at 5oCfor further use.
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24-25 March 2015
Efficacy Testing of Trichoderma against S. sclerotiorum, R. solani, F. Solani
Dual culture method was adopted to study efficacy of Trichodermaspp in PDA. Five
mm disc size of both Trichoderma spp. and respective pathogens from pure culture
were simultaneously inoculated in opposite sides of the PDA plates in about 3 cm
distance and incubated at24oC-26oC for 5 days. A total of 24 Trichoderma isolates
were included in twoconsecutive years (2012/13 and 2013/14). Observation was taken
for biological control mechanisms after 5 days.
Of the 138 soil samples processed, Trichoderma spp. were isolated from 59 samples
during two years (Figure 1). During 2011/12, Trichoderma spp.were isolated from all
the 31 processedsoil samples. Thus a total of 90 isolates of Trichoderma spp. were
isolated and preserved. Trichodermaspp. isolating soil samples were mostly from the
hills with vegetable farming. Ofthe 24 isolates of Trichodermaspp. tested against soilborne pathogens, S. sclerotiorum, R. solani and F. solani, most of the isolates showed
over growth or masking effect with R. solani and F. solaniwhereas with S.
sclerotiorum zone of inhibition reaction was also observed (Table 1 and 2). In overall
observation, 9 isolates found to form clear zone of inhibition exhibiting potential
biocontrol efficacy against S. sclerotiorum and 9 isolates grew fast masking the growth
of the pathogen and 6 were shown competitive growth with the pathogen. Those 6
isolates may not possess enough biocontrol efficacy. In case of R. solani and F. solani,
almost all the Trichoderma spp. isolates showed the masking effectswhich is also one
of the good biocontrol mechanism (Figure 2). Four isolates showed competitive
reaction to F. solaniand one toR.solani.
Besides, 9 isolates were tested in seedling assay against Rhizoctonia root rot, of which
three identified Trichoderma spp. were found effective to reduce root rot thereby
increasing survival percent of the seedlings by 42%, 50% and 75% by the application
of T69 (T. harzianum), TS (T. asperellum), and TS20 (Trichoderma sp.) respectively
compared to 17% in control under screenhouse conditions(PPD, unpublished data).
Similarly, two native Trichodermas, i.e.T. harzianum (T69), T. asperellum (TS) and
one from commercial product of T.harzianum (T22) were effective to
reducedclubrootdisease severity by 35-40 percent in the fieldconditions at Palung
(Timila 2011).
Soil biodiversity plays a key role in the sustainability of agriculture systems and
indicates the level of health of soil, especially when considering the richness of
microorganisms that are involved in biological control of soilborne diseases (Gil et al.
2009).The most of the success stories of biological control are from the studies
conducted under controlled conditions or environment.Their efficacy reduced or not
enough for disease control in the field conditions. The efficacy of biological control
agents may be influenced by other microbial communities present in the soil,
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24-25 March 2015
fluctuating temperature, humidity, air movement, survival and establishment of BCA
itself in the given field conditions.
Table 1: In vitro Biocontrol mechanism of different isolates of Trichoderma spp.
Against Sclerotiniasclerotiorum, Rhizoctoniasolaniand Fusariumsolani
(2012/13).
S.
No.
Trichoder
ma isolates
1.
TS17
2.
TS19
3.
TS 28
4.
5.
TS29
TS 33
6.
7.
8.
9.
10
TS34
TS37
TS18
TS57
TS38
S.
sclerotiorum
Overgrowth
(Masking
effect)
zone of
inhibition
zone of
inhibition
overgrowth
zone of
inhibition
overgrowth
overgrowth
overgrowth
overgrowth
overgrowth
Reaction to
R. solani
F. solani
Crop/location/Agro-eco
Zone
Overgrowth
(Masking effect)
Overgrowth
(Masking effect)
Cauliflower/Marpha/high
hill
overgrowth
overgrowth
Rice, Khudi
competitive
overgrowth
Cauliflower/Naubise/hill
overgrowth
overgrowth
overgrowth
competitive
Cauliflower/Katunje/hill
overgrowth
overgrowth
overgrowth
overgrowth
overgrowth
competitive
overgrowth
overgrowth
competitive
competitive
Cauliflower/Katunje/hill
Carnation/Saanga/hill
Rayo/ Ghalegaoun/hill
Eggplant/Tarahara/terai
Tomato/Kapan/hill
Table 2: In
vitro
Biocontrolmechanism
of
different
isolates
of
Trichodermaspp.againstSclerotiniasclerotiorum,
Rhizoctoniasolaniand
Fusariumsolani(2013/14).
S.
No
Trichoderma
isolates
1.
TS 22
2.
3.
4.
Reaction to
Crop/location/Agro-eco
Zone
Rhizoctoniasolani
Fusariumsolani
TS 12
Sclerotiniascleroti
orum
Overgrowth
(Masking effect)
Zone of inhibition
Overgrowth
(Masking effect)
Overgrowth
Overgrowth(Mas
king effect)
Overgrowth
TS 14
TS 32
competitive
Zone of inhibition
Overgrowth
competitive
Overgrowth
Overgrowth
Cabbage/Dhungkharka/hill
5.
6.
7.
TS 20
TS 21
TS 16
Zone of inhibition
competitive
competitive
Overgrowth
Overgrowth
Overgrowth
Overgrowth
Overgrowth,
Overgrowth
Cabbage/Sidhuwa/hill
Cabbage, Bhajuwa
Asparagus/Bhaktapur/hill
8.
TS 31
competitive
Overgrowth
competitive
9.
TS 9
Overgrowth
Overgrowth
Overgrowth
10
11.
12
TS 6
TS 23.
TS 30
competitive
Overgrowth
Zone of inhibition
Overgrowth
Overgrowth
Overgrowth
Overgrowth
Overgrowth
Overgrowth
Cabbage/Chaughare/hill
Continued…C
Cauliflower/Futung/hill
Dhankuta/hill,
Rice/ Naubise/hill
13
TS1
Zone of inhibition
Overgrowth
Overgrowth
Rayo/ Marpha/high hill
14
TS 15
competitive
Overgrowth
Overgrowth
Rice/ Bhaktapur/hill
298
Cabbage/Sidhuwa/Hill
Pepper/hill
24-25 March 2015
60
50
40
Samples processed
30
Trichoderma isolating
samples
20
10
0
2012/13
2013/14
Figure 1: Number of soil samples processed and Trichoderma isolating samples
25
20
15
Zone of inhibition
Masking effect
10
Competitive
5
0
S. sclerotiorum
R. solani
F. solani
Figure 2: Different antagonistic effects of tested Trichoderma isolates to Sclerotinia
sclerotiorum, Rhizoctonia solani and Fusarium solani.
Conclusions
Biological control could be one of the promising parameter of integrated disease
management of the crops. It has potential role in disease management speciallyin
organic farming.Trichoderma isolates from Nepalese native soil have the high
efficacyof biological control against soilborne pathogens such as S. sclerotiorum, R.
solani,F. solani. However the results from laboratory or from screenhouse conditions
urgently need to be tested in the field conditions for verification.The native isolates, T.
harzianumand T. asperellumcould be utilized for the integrated management of
clubroot disease of brassica vegetables.Those isolates and one more isolate (TS20)
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24-25 March 2015
effective to reduce root rot caused by R. solani. Native Trichoderma spp. should be
emphasized as bio control agents.Exploration of such potential native BCAs from soil
of different cropping system need to be continued as the strategic plan to discourage
the use of chemical pesticides.
Future strategies
Enhancement of exploration of native BCAs from soil of different cropping system
with different agroecological zones will be continued.Laboratory testing, seedling
assay and verification in the field conditions (on station and on farm) will also be
continued.Testing of substrates for mass multiplication of effective Trichoderma spp.
for field delivery will be emphasized.
Acknowledgements
The authors express their thanks to their colleagues of Plant Pathology Division for
their helps and suggestions. They extend their thanks to them who helped in laboratory
and screenhousework as well.
References
Elad Y, I Chet and Y Henis. 1981 . A selective medium for improving quantitative
isolation of Trichodermaspp. from soil . Phytoparasitica. 9(1): 59-67.
GilSV,SPastor and GJMarch. 2009. Quantitative isolation of biocontrol
agents Trichoderma spp.,Gliocladium spp. and actinomycetes from soil with
culture media. Microbiological Research.Vol 164, Issue 2, 2009. Pp. 196–205
Knudsen GR and Louise-Marie C Dandurand. 2014.Ecological Complexity and the
Success of Fungal Biological Control Agents.Advances in Agriculture. Vol.
2014 (2014),Article ID 542703.
Hoorman James J and Ratif Islam. 2010. Understanding soil microbes and nutrient
recycling. Fact Sheet .Agriculture and Natural Resourceshe Ohio State
University.
Mehrotra RS, KR Aneja and A Aggarwal. 1997. Fungal Control Agents. In
Environmentally safe Approaches to crop disease control.Agriculture and
Environment Series.Edt. Nancy A. Reechcgil and Jack E. Rechcigl.
Singh RK. 2010.Trichoderma: A bio-control agent for management soil born diseases.
Agropedia.http://www. Agopedia.iitk.ac.in/
Timila RD. 2011.Evaluation of Some Trichoderma spp. for
Clubroot
Disease
Management. Nepal Agric.Res.J.Vol.11.
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SM-5
Efficacy of JeevatuJho Mal (JJM) to Radish (Raphanussativus
L.)Production in the Central Valley of Kathmandu
Sanu K Bajracharya, Bishnu H Adhikary and Sri K KC
Soil Science Division (NARC),
, Nepal
Abstract
To evaluate the efficacy of Jeevatu Jhol Mal (JJM) in Radish field experiment was conducted
with three replications and six treatments
in a Randomized Complete Block Design
in Hatiban farm of
Potato Research Program, Khumaltar during the year 2070 and
2071. The plot size was 3m x 2m with total plot size of 6 sq. m. The crop was sown in
lines with spacing of 30 cm x 10 cm (RR x PP).The main objective of the experiment was to
study the effect of Jeevatu Jhol Mal supplied by Nepalese Natural Bio-products Pvt. Ltd.The
treatment comprised of control (fertilizer not applied), Jeevatu treated compost (30 t ha-1),
compost (30 t ha-1), Jeevatu treated compost (15 t ha-1) plus half dose of recommended
chemical fertilizer (50:25:25 N: P2O5:K2O kg ha-1), compost (20 t ha-1) plus full dose of
recommended chemical fertilizer (100:50:50 N: P2O5:K2O kg ha-1) and Jeevatu compost
(30 t ha-1) plus JM no. 1 & no. 2. Two years mean result showed an encouraging effect of
Jeevatu treated compost (15 t ha-1) plus half dose of chemical fertilizer (50:25:25 N:
P2O5:K2O kg ha-1) on tuber diameter (10.88 cm), tuber yield (12.58 t ha-1) and leaf yield
(7.24 t ha-1) of radish (Raphanussativus L). However from soil health, economical,
qualitative and quantitative point of view, Jeevatu compost (15 t ha-1) plus half dose of
recommended chemical fertilizer (50:25:25 N: P2O5:K2O kg ha-1) was found significantly
effective for radish production.
Ke words: Chemical fertilizer, jeevatu jholmal, jeevatu treated compost, tuber yield of
radish.
Introduction
Continuous and unbalanced use of chemical fertilizer for long time without adding any
organic fertilizer leads to change in soil chemical and physical characters and soil
becomes acidic (Bajracharya et al. 2007). Acidification of soil is very harmful to
beneficial soil microorganisms and enzyme. Consequently the availability of beneficial
soil microbes and essential macro and micronutrients decrease sharply and soil health
becomes deteriorated in the present context in one hand. According to Gupta and Singh
(2006), indiscriminate and excessive use of chemical fertilizer has not only deteriorated
the soil health but has also impaired the health of human beings and animals. In other
hand, chemical fertilizer is very expensive, not manufactured in our country and not
available in time. Therefore, Ministry of Agriculture Development (MoAD)
Government of Nepal is promoting organic based fertilizers to restore and sustain soil
fertility. In this circumstance, organic liquid fertilizer the Jeevtu Jhol Mal (JJM)
supplied by Nepalese Natural Bioproducts Pvt. Ltd. was tested to study its effect in
radish production in two seasons.
301
24-25 March 2015
Beneficial microorganisms play vital role in Nitrogen fixation, Phosphorus solubilization
and Production of hormone, vitamins, antibodies, organic acids, aminoacids etc. Jeevtu
Jhol Mal is consortium of natural beneficial microorganisms (Adhikari et al.2013). This
organic liquid fertilizer may be one of the appropriate alternative substitutes of chemical
fertilizer to some extent in agriculture sector in our Nepalese context.
Compost was prepared by using of Jeevtu Jhol Mal (JJM) 10% and without using of
JJM but using same amount of water. Duration of compost preparation was one month
and turning was done in every 15 days interval. The two seasons experiment was
carried out in Hatiban farm Potato Research Program during the year 2013 and 2014
following Randomized Complete Block Design RCBD) with six treatments and
replicated three times. Plot size was 3m x 2m with total plot size of 6 sq.m .and total
area was 300 sq. m. Row to row distance was 30 cm. Seed to seed distance was 10 cm.
Two seeds per hole were sown. The Chalisedine (40 days) Mula variety of radish was
used for this experiment. The treatments details are given below:
T1
T2
T3
T4
=
=
=
=
T5
=
T6
=
Control (Fertilizer not applied)
Jeevatu treated compost (30 t ha-1)
Compost (30 t ha-1)
Jeevatu treated compost (15 t ha-1) + half dose of chemical fertilizer
(50:25:25 N: P2O5:K2O kg ha-1)
Compost (20 t ha-1) + full dose of chemical fertilizer (100:50:50 N:
P2O5:K2O kg ha-1)
Jeevatu compost (30 t ha-1) + JM no. 1 & no. 2
Jeevatu Jholmal no. 1(25 kg compost + 25 liter cattle urine + 25 litre water + 1 litre
Jeevatu for drenching in soil as top dressing) & Jholmal no. 2 (37.5 litre cattle urine +
37.5 litre water + 1 litre Jeevatu for spraying) were supplied by Nepalese Natural
Bioproducts Pvt. Ltd. and were used in the experiment. The plants were harvested at
40 days after sowing for agronomic characters and yields from two center lines (1.5
sq.m). All the parameters were recorded as per requirement and the data was analyzed
using MSTAT statistical packages.
Soil and compost analysis
Prior to the establishment of experiments, composite soil sample from 0-15 cm depth
was collected from the field before planting and after harvesting from all the plots. All
collected soil, Jeevatu Jhol Mal, Jeevatu treated compost and normal compost to be
used were analyzed for physiochemical properties. The soil pH was measured by
method using pH meter in 1:1 soil and water ratio. Organic matter was determined by
modified Walkey and Black Method. Phosphorus was analyzed by Olsen’s Bicarbonate
method. Potassium was analyzed by Flame Photometer method. Total nitrogen was
analyzed by Micro Kejeldhl’s method. Texture was analyzed by soil Hydrometer
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24-25 March 2015
method .Compost nitrogen was analyzed by Micro Kejeldhl’s method and Phosphorus
and Potassium by Bicarbonate Fusion method (Table 1).
Physico-chemical properties of composite soil, Jeevatu jhol, Jeevtu treated compost
and ordinary compost before radish planting are presented in Table 1. Physicochemical properties of soil after radish harvesting are presented in Table 2. The soil of
field of experimental site was sandy loam with pH 6.3, organic matter 4.5 %, low in
available nitrogen (0.15%), high in available P2O5 (578 kg ha-1) and high in available
K2O (134.4kg ha-1) ( Table 1). Jeevatu treated compost (JTC) contained high value of
nitrogen (3.25%), Phosphorus (2.73%), potassium (0.71 kg ha-1) (Table 1). These
values were higher over ordinary compost. Soil test results after the harvesting of
radish indicated that soils are found better in nutrients and OM content (Table 2).
Jeevatu Jhol Mal (JJM) response in radish
The mean plant height and plant population, tuber diameter and leaf and tuber yield are
presented in Table 3. The combined statistical analysis of the data revealed that plant
height, tuber diameter and plant population were significant and leaf yield and tuber
yield were highly significant. Plant height was found higher (10.3 cm) in treatment 5
(T5) followed by T4, T3 and T6. These values are higher over the control plot. Plant
population was more or less similar in T3 and T6 treatments. Tuber diameter was found
higher (10.9 cm) in T4 and more or less similar in T5 and T6. Proper supply of plant
nutrients as well as deep and loose soil is essential for proper expansion of radish root.
Similar finding was also reported by Parraga et al (1995).
They reported that application of organic manure with chemical fertilizer increased
root diameter of radish which supports the finding of present study. Highest leaf yield
(8.5 t ha -1) was given by plot treated with Jeevatu treated compost (30 t ha-1) plus Jhol
Mal no. 1 & no. 2. Second highest of leaf yield (7.2 t ha -1) was observed in treatment 4
comprising Jeevatu treated compost (15 t ha-1) plus half dose of chemical fertilizer
(50:25:25 N: P2O5:K2O kg ha-1). Two years mean result revealed that highest tuber
yield (17.7t ha -1) was produced by plot (T5) which was treated with compost (20 ha-1)
+ full dose of chemical fertilizer (100:50:50 N: P2O5:K2O Kg ha-1) followed by T4, T6,
T3 and T2, respectively.
Table 1: Physico-chemical properties of composite soil, Jeevatu Jhol Mal, Jeevtu
treated compost and ordinary compost before radish planting.
Type sample
pH
OM,%
N,%
P2O5
K2O
-1
1. Composite soil (CS)
6.3
4.5
0.15
578 kg ha
395 kg ha-1
2. Jeevatu Jhol Mal (JJM)
1.6
0.15%
0.40
3. Jeevatu treated compost 3.25
2.73%
0.71
(JTC)
4. Ordinary compost (OC) 1.39
2.41%
0.98
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24-25 March 2015
Table 2: Physico-chemical properties of soil after radish harvesting
Treat
ments
Treatment Details
pH
OM,%
N,%
P2O5,
kg ha-1
K2O,
kg ha-1
T1
T2
T3
T4
Control (Fertilizer not applied
Jeevatu compost (30 t ha-1)
Compost (30 t ha-1)
Jeevatu compost (15 t ha-1) +
half dose of chemical
fertilizer(50:25:25 N:P205:K2O
Kg ha-1)
Compost (20 t ha-1) + full dose
of chemical fetilizer
(100:50:50 N:P205:K2O Kg ha1
)
Jeevatu compost (30 t ha-1) +
JM no. 1 & no. 2
6.3
6.2
6.1
6.4
5.0
5.0
4.4
4.9
0.18
0.18
0.18
0.17
582.3
566.3
555.3
535.6
465.0
371.0
393.6
541.0
6.5
5.1
0.16
599.0
483.0
6.1
4.8
0.18
441.6
483.0
T5
T6
Table 3: Treatment effect of Jeevatu Jhol Mal (JJM) on plant height, population, tuber
diameter and yield of Radish.
Treat
ment
Treatment details
T1
Control
(Fertilizer
not
applied
Jeevatu treated compost (30
t ha-1)
Compost (30 t ha-1)
t ha-1) + half dose of
chemical fertilizer (50:25:25
N:P2O5:K2O kg ha-1)
Compost (20 t ha-1) + full
dose of chemical fertilizer
(100:50:50 N:P2O5:K2O kg
ha-1)
t ha-1) + JM no. 1 & JM no.
2
Mean
CV%
F test
Treatment
Year x Treatment
LSD (at 0.05)
T2
T3
T4
T5
T6
Means of two years data (2013 and 2014)
Plant
Plant
tuber
Leaf
height
population, diameter Yield,
pl1,cm
nos.
pl1,cm
t ha-1
B
B
B
6.9
30.6
6.87
2.2D
Tuber
yield,
t ha-1
4.5C
8.9A
34.8A
9.52A
3.9CD
9.5BC
9.9A
9.9A
36.8A
33.0AB
9.72A
10.88A
4.2CD
7.2AB
7.9C
12.5AB
10.3A
34.5AB
10.54A
5.4BC
17.7A
9.6A
36.5A
10.52A
8.5A
12.2AB
9.3
17.8
34.4
9.0
9.67
19.26
5.3
38.2
10.8
46.9
*
*
2.0
*
ns
3.7
*
ns
2.2
**
**
2.4
**
**
6.0
ns = non significant, * = significant, ** = highly significant at 95% confident. Means followed
by the same letter within columns are not significantly different according to Ducan,s Multiple
Range Test at P = 0.05
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24-25 March 2015
Maximum leaf yield increment of 284.8% over the control was noticed with the full
dose of Jeevatu treated compost along with JM no.1 and JM no. 2 (Figure 1). The
increment of 227.5% leaf yield of radish was observed second highest when half dose
of Jeevatu treated compost (15 t ha-1) combined with half dose of chemical fertilizer
(50:25:25 N: P2O5:K2O kg ha-1) was applied (Figure 1). Maximum increment of radish
tuber yield was observed with full dose of chemical fertilizer (100:50:50 N: P2O5:K2O
Kg ha-1) (285.5%) over control (Figure 2). Application of half dose of Jeevatu treated
compost (15 t ha-1) along with half dose of chemical fertilizer (50:25:25 N: P2O5:K2O
kg ha-1) produced second highest percent increment (173.7%) over control (Figure 2).
Correlation of the plant parameters
Correlation matrix among the leaf yield, tuber yield, plant population, tuber diameter
and plant height has been presented in the Table 4. The correlation of leaf yield and
tuber yield (r = 0.52) was observed highly significant but non – significant with rest of
the parameters. Similarly, the correlation of tuber yield with plant population (r =
0.38), tuber diameter (r = 0.84) and plant height(r = 0.74) was significant. Similarly,
the correlation of plant population was significant with tuber diameter (r = 0.45), while
non – significant with rest of the parameters. Correspondingly, tuber diameter was
highly significant with plant height (r = 0.94)
Figure1:Leaf yield increment over control, % .
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Figure 2. Tuber yield increment over control, %.
Table 4: Correlation matrix between different parameters of the radish plant.
Leaf yield Tuber
Plant
Tuber
Plant height
yield
population
diameter
Leaf yield
1
0.52**
0.15
0.35
0.18
Tuber yield
0.52**
1
0.38*
0.84**
0.76**
Plant
0.12
0.38*
1
0.45**
0.52**
population
Tuber
0.35
0.84**
0.45**
1
0.94**
diameter
Plant height
0.18
0.76**
0.52**
0.94**
1
** = Highly significant and * = significant
Conclusion
It was found that Jeevatu treated compost (15 t ha-1) plus half dose of chemical
fertilizer (50:25:25 N, P2O5:K2O kg ha-1) (T4) and Jeevatu compost (30 t ha-1) + Jhol
Mal no. 1 & no. 2) (T6) has good effect on better yield of radish tuber and radish
leaves. From soil health, economical, qualitative and quantitative point of views the
above result was found effective for increased radish yield. It can be concluded that
Jeevatu treated compost compost has positive Jeevatu treated compost effect in radish
production and is found more effective when supplied along with half dose of the
recommend chemical fertilizers.
Acknowledgement
The authors express their cordial thanks to Dr. Buddhi P Sharma, Potato Research
Program providing experimental land for conduction of this research. We would like to
give special acknowledgement to Dines Khadka for analyzing soil, Jeevatu Jhol mal,
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jeevatu treated compost and ordinary compost. We also would like to thank to Laxman
Lakhay and other concern staff of Soil Science Division for their cooperation in
conducting the experiment. Mr. Duryodhan Chaudhari (Technical Officer) from Potato
Research Program is also highly acknowledged for his involvement in works in
supervising the field of this investigation.
References
Adhikari SR, KB Poudel, K Pokhrel and A Poudel. 2013. Effect of microbial (Jeevatu)
treatment on
rice (Oryza sativa L.) production. Int. J. Appl Sci
Biotechnol. 1(4): 184 - 188.
Bajracharya SK, DP Sherchan, S Bhattarai. 2007. Effect of vermicompost in
combination with bacterial and mineral fertilizers on the yield of vegetable
soybean. Korean J.Crop Science . 52(1): 100-103.
Gupta, RD and H Singh (2006). Indiscriminate use of fertilizer poses health hazards.
Farmer's Forum. 9 (6): 20–24.
Parraga MS, AL Pereira, JL Medeiros and PFP Carvalho. 1995. Effect of organic
matter on quantity and quality of roots in carrot (Daucus carrota L.)
harvested at three dates. Semira (Londrina).16: 80-85.
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24-25 March 2015
4. Geographical Information System (
) and
GSS-1
Soil Types and Fertility Status in Western Terai Region of Nepal: A Case
from the BankatawaVDC of the Banke District
Krishna R Tiwari
Institute of Forestry, Pokhara, Nepal.
Abstract
Soil has a crucial role in addressing some of the key issues in the present context such as
food security, and climate change and provide a key natural resources asset underpinning
sustainable development. Land use change, soil degradation are the major problems for
agriculture production and food security in Nepal. To address the issue of these problems
National Land Use Project, Ministry of Land Reform and Management, Government of
Nepal has implemented the project to prepare land use plan at VDC level. Soil survey and
classification as well as soil fertility analysis for land use planning was done to classify the
different soil types and fertility status of the area. The study was chosen Bankatawa VDC
of the Banka District of Nepal. A Semi-detailed soil survey was conducted in February
2014, to delineate and map the existing soil types supported by remote sensing technique
and geographical information system (GIS) analysis. Soil
were collected from
each mapping unit. Soil types were classified based on USDA soil taxonomy system and
soil fertility such as pH, SOM, Total N, Available P
Kwere analyzed using standard
methods. Soil survey and data analyzed showed that soil is formed homogeneous flat area
with young soil (alluvial plain) to old alluvial complex and very gentle slope. Dominant
soil are Inceptisols (74%) followed by Alfisols (24%) in the area. Similarly, fertility status
found low level of nutrient content such as SOM (0.8 to 1.5%), otal N (0.06 to
1%).Whereas, vailable P (42.6 to 116 ppm), and Ex K (40 to 915.5 ppm) were found
medium to high. Soil pH
slightly acidic to alkaline
nature. Field survey and soil
analysis report showed that the land is highly suitable for intensive agriculture production
by improving soil fertility and irrigation facility. However, the recent trend of urbanization
particularly along the East-West highway resulted change in fertile land into settlement
threat for agriculture production and food security in future.
Keywords:Cropping pattern nutrient content, soil classification and soil profile.
Introduction
Information of the soil types and fertility status is useful for land-use planning and land
management, from large agricultural development projects and extensive farming to
precision agriculture and intensive farming, as well as for non-agricultural applications
(Bassols 2009).Interrelation between the environment protection and economic
development can lead to sustainable development. Despite of development efforts in
the past decade in agriculture food insecurity is increasing in various districts of
Nepal.It provides employment opportunities to 66 percent of the total population and
contributes about 34 percent in the GDP (Economic Survey: 069/70) Therefore, the
development of agriculture sector is key for the development of national economy
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(DOA 2014). Furthermore, the interim constitution of Nepal has mentioned "food
sovereignty" as fundamental right in its constitution(Interim Constitution of
Nepal18.3). This statement tries to protect people from the negative consequences of
increasing food insecurity, unequal food distribution and no access to food. All of
these planning processes attract a range of stakeholders that are interested in the
activities that take place in their communities. In this context, soil survey, and land
capability classification is an important task to increase food security and sustainable
land management.
Agriculture is the main source of livelihood for the majority of people in Nepal and is
considered as the primary engine of growth of the economy. Despite the fact that it is
declining, agriculture still contributes nearly 34 percent to Nepal’s total Gross
Domestic Product (GDP) and crop production is the largest component of the
agricultural GDP (MOAD 2013). Maintenance, and indeed eN hancement, of soil
fertility is essential to meet the basic food and resource needs of Nepal's rising
population (Brown et al.1995). As a result of rapid population growth (at a rate of
approximately 2.5 per annum,agricultural stagnation and a range of institutional
failures, the threat of a serious food crisis in Nepal is substantial. Nepal’s most recent
(2010) Global Hunger Index (GHI) score is 20, which places it at 27th out of 84 ranked
countries; moreover, western regions of the country score far lower (Hollema and
Bishokarma 2009).
As the world’s population continues to expand, maintaining and indeed increasing
agricultural productivity is more important than ever, though it is also more difficult
than ever in the face of changing weather patterns that in some cases are leading to
aridity and desertification. The absence of scientific soil inventories, especially in arid
areas, leads to mistaken decisions about soil use that, atthe end, reduce a region’s
capacity to feed its population, or to guarantee a clean water supply. Greater efficiency
in soil use is possible when these resources are properly classified using international
standards.
In recent years, Nepal faces the unmanaged land utilization and urbanization
particularly agriculture production area resulted the decreasing land quality and
threatening food security in future. In this context, Ministry of Land Reform and
Management, National Land Use Project (NLUP), Government of Nepal has
undertaken an initiative to study soil survey, land resource mapping and capability
classification at present land use report and map at VDC level. To address the land use
planning at the VDC level it is essential to understand the soil types and fertility status
in the area and hence this study carried out.
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24-25 March 2015
Study area
Banakatawa Village Development Committee (VDC) lying in Banke district, Mid Western Tarai Region of Nepal, covers a total area of 41.04 square kilometers (4104.42
ha). Banakatawa VDC shares its border with Bageshoweri and Raniyapur VDC to the
south, Titihiriya VDC, Banke and Mankhola of BardiyaDistrictin west, Rajhena and
Samsergunj VDC to the east and Naumasta VDC to the north. The VDC lies in the
north-western part of Banke district. The maximum north-south extent is about 10.7
km whereas east-west extent is about 6.2 km. This VDC is about 18 km far from the
district headquarter, Nepalganj. Economic condition of the people of this VDC largely
depends on agriculture. Land is the main source of income and capital accumulation
and also the major source of employment. VDC area forming the southernmost part of
Nepal is a part of the northern end of the Indo- Gangetic Plain and range in elevation
from 128 to 150 m above msl.The study area is located in the sediments of the
Indo-Gangetic Plain. Most of the study area falls in the Bhabharand Middle
Terai zones.
Soil survey
Soil survey was conducted in the months of January 2014 to delineate and map the
existing soil types as baseline data supported by remote sensing technique and
geographical information system (GIS). The methodology adopted for the present soil
survey was based on integrated use of visual interpretation and computer aided
technology and integrated use of GIS and Remote Sensing techniques. Numbers of 35
profiles were described in detail in the field through the excavation of pits within the
various land use categories to cover the entire VDC.
At each pit location, soil profile was studied in each horizon with surface and
subsurface diagnostic horizons. Soil morphological characteristics and properties such
as texture, structure, consistency, mottles, porosity, compactness, pH, colour, slope,
and drainage minutely analyzed in each pit and recorded at the soil profile description
sheet developed by National Land Use Project. Additionally, soil sample was taken
from the surface horizon, for further laboratory analysis of physical and chemical
properties at the soil lab using standard techniques. Analysis included weretexture
(sand, silt, and clay), pH, Total N, Available P, availableK, and Organic matter.
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24-25 March 2015
Figure 1: Map of the study area.
Soil mapping units were demarcated based on the land units that also identified
capturing the local topography variation. The description of soil mapping unit and the
symbol was formed with the integration of land system, landform, land type and
geological map and land use/land cover (Shahid 2013).
Climatic Condition
Climate is one of the major soil forming factors affecting the soil formation directly
and indirectly. The data showed that Pre-monsoon season (April-May), that
corresponds to the summer naturally has the highest mean maximum temperature (37
0
C) while mean minimum temperature is 70C in the months of January. The total
average temperature analysis showed 24.5 oC in the survey area. Based on the
temperature data, this VDC falls under the Thermictemperature regime.
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24-25 March 2015
Rainfall data showed that (Figure 2.2) VDC receives annually on an average 1542 mm
precipitation on the basis of a decade data (2002-2012) with each of the month
receiving some amount of precipitation. The maximum rainfall recorded in the month
of July (522 mm) and minimum rainfall in the month of November and December
(about 2 mm). Rainfall data showed that more than 80 % rainfall received in three
rainy season months (June, July and August). Precipitation datashowed that study area
can be classified under Ustic moisture regime.
Agricultural Land use
Agricultural land of the Bankatuwa VDC is classified as Terai cultivation based on the
physiographic region. This VDC contains all of its agricultural land use dominantly
under rice based cultivation. The rice field is further divided into lowland khet and
upland. The cropping pattern of the VDC varies according to agricultural land types,
irrigation and precipitation. The upland cultivation comprises of crops such as rice,
wheat, pulses, mustard, and vegetables. Rice is the dominant summer crop whereas
wheat, pulses (lentil), oilseed are cultivated in the winter season. In the upland area
pigeon pea cultivation is also common practice in the VDC.
The total agriculture land of the Banakatawa VDC was found to be 3769.17 hectares in
which rice-wheat cropping pattern was pre-dominated with 75.62 percent share
proportion among all crop combinations. It is followed by rice-pulses crop
combination. The area under other crop combination was less dominant cropping
pattern of agricultural land. Most of the agricultural land in the VDC was categorized
as intense and moderate based on the cropping intensity in which intense has
dominated cropping intensity.
Soil types from order to sub-group level
Soils of Bankatuwa VDC of Banke district are classified based on the information of
soil derived from soil pits and soil mapping unit level. This soil classification is based
on the Great Soil Groups of Soil Taxonomy (USDA 2010) with LRMP (1986) report.
In this system, the soils are grouped according to Soil Orders, Sub-Orders, Great
Groups, Sub-Groups and Soil Family level. Table 1 presents Soil Taxonomy
classification for the soils of Bankatuwa VDC.
Table 1: Soil Taxonomy Classification of Bankatuwa.
Anthrepts
Haplanthrepts
Dystrusepts
3
Ustepts
4
14
Utisols
Hydrography
Total
Ustults
Haplustepts
Humustepts
Haplustults
Source: Soil Survey (2014).
312
TypicHaplanthrepts
TypicDystrustepts
VerticDystrustepts
TypicHaplustepts
VerticHaplustepts
TypicHumustepts
TypicHaplustults
879.12
217.05
62.93
979.39
196.32
97.85
10.85
24.46
3301.42
26.63
6.57
1.91
29.67
5.95
2.96
0.33
0.74
100.00
24-25 March 2015
Bankatuwa VDC formed homogeneous flat area with young soil (alluvial plain) to old
alluvial complex and very gentle slope. Physical properties such as texture found
loamy, clay loam,silty loam and silty clay loam were recorded. Soil pH data showed
that slightly acidic, neutral and slightly alkaline. Soil fertility status found OM, and
total N found low level in all sampled areas. In case of Phosphorus and Potassium
generally reported high, medium and low level availability. Additionally,
Micronutrients such as Zinc in ppm reported low level where as Boron was found
greater than critical level.Soil survey team explored four Order, six Sub-orders, nine
Great soil groups and Sub Great group are explored from the soil survey investigation
in Bankatuwa VDC of Banke district (Table 1). Two orders Inceptisols, , and Ultisols
were reported from the soil survey.
Soil survey and mapping of the Bankatuwa VDC showed that soil is old alluvial
toyoung soil profile development with sufficient depth for cultivation. About 99% soil
order found was Inceptisols, and 1% soil found some mature soil profile (Ultisols) in
the area of this VDC. Soil map of Bankatuwa VDC of Banke District is prepared by
integrated use of Geo-science technology consisting of RS, GIS and GPS and soil
mapping unit identified with landform and land type units.
Most of the land types and soil mapping units are under 1° slopes. Terrain
classification is done to represent micro-relief of the area represented by land type
units and land use/land cover. Furthermore, cropping pattern is also considered to
differentiate the soil mapping unit. These parameters helped to characterize the unique
features of physio-soil relationship. Based on land type, over 90% of total geographical
area of the VDC is found having alluvial fan and depositional plain.
General Fertility Status of Soils
Soil organic matter (SOM) is at low range in most of the area (1.5 to 2.9 %). But in the
some moist area, SOM is found 2.5 %, which could be due to accumulation of plant
litters. The total nitrogen follows the SOM trend (0.05 to 0.14). Both Available P and
AvailableK are at medium range, which indicate poor soil fertility status. Soil pH
values are towards acidic to neutral side ranging from 4.9 to 7.5. However, the
majority of soil pH is at 6.3 to 6.6 (Table 2). Therefore, these nutrients status indicate
that overall soil fertility status of theareas are low level of nutrients status particularly
organic matter and total N.
Continuous crop cultivation with low level of soil organic matter content indicates
decreased soil quality in this area. Previous research articles also support that
decreasing the soil fertility due to intensive farming with low application of organic
matter (Trapathi et al. 2010, Brownet al. 1999). Area found highly suitable for
intensive cultivation if irrigation is available and improve soil fertility.
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24-25 March 2015
Table 2: Soil nutrients parameter.
SNo
1
Soil Properties
pH
Result (range)
5.5 to 7.5
2
OM (%)
1.5 to 2.9
Interpretation
Moderately acidic
to slightly alkaline
Low to medium
3
TN (%)
0.05 to 0.14
Low to medium
4
P2O5 (ppm)
11 to .4211
Low to high
5
K2O (ppm)
55 to 341.8
Low to high
Remarks
Majority of the areas
are slightly acidic soil
More than 75 % areas
having low level
More than 75 % areas
having low level
Majority area having
medium level
Majority area having
medium level
The result showed thatthere should be increased organic matter content and application
of lime to increase soil fertility and improve soil quality in the area.Present study
strongly felt the need of the soil survey and mapping of all the VDCs of Nepal for
optimum land use planning and sustainable development of VDCs in future. Based on
the analysis of nutrient status it can be recommended to supply recommended dose of
fertilizers as well as increased organic matter content in the soil
Conclusion
Soil survey and mapping of the Bankatuwa VDC showed that soil is old alluvial
toyoung soilprofile development with sufficient depth for cultivation. About 99% soil
is covered by soil order found Inceptisols and the rest is by Ultisols. Soil fertility status
showed that low level of nutrients particularly total N and organic matter. It is
recommended that addition of Organic matter with recommended dose of chemical
fertilizer to increase the agriculture production for long term sustainability.
Acknowledgement
I would like to thanks for Rajdevi Consultancy, Kathmandu and their staffs
RagendraTandon,RashilaKhadaka and Raju Rai to provide data and necessary help in
the field work and data management.
References
Bassols B, JA Zinck and Evan Ranst. 2009. Participatory soil survey: experience in
working with a Mesoamerican indigenous community.Soil Use and
Management. 25: 43–56.
Brown S, H Shreier, PB Shah and L Lavkulich. 1995. Modeling of soil nutrient
budgets: an assessment of agricultural sustainability in Nepal. Soil Use
Manage.15:101-108.
DOA 2014. Annual Report, Department of Agriculture, Ministry of Agricultural
Development, Kathmandu, Nepal.
MOAD. 2013. Statistical Information on Nepalese Agriculture, Government of Nepal
Ministry of Agricultural Development Agri-Business Promotion and Statistics
Division Agri statistics Section Singha Durbar, Kathmandu, Nepal.
314
24-25 March 2015
Hollema S and M Bishokarma. 2009.A sub-regional hunger index for Nepal.
Kathmandu:World Food Programme, Nepal food Security Monitoring System
(NeKSAP).
LRMP. 1986.Land Capability Report.Land Resource Mapping Project,Nepal.Kenting
Earth Sciences Limited, Ottawa, Canada.
Tripathi BP and JE Jones. 2010. Biophysical and socio-economic tools for assessing
soil fertility: A case of western hills, Nepal. Agron. J. Nepal. 1:1-9.
USDA. 2010. Soil Taxonomy a Basic System of Soil Classification for Making and
Interpreting Soil Surveys, Soil Survey Staff, Agriculture Handbook No 436,
Soil Conservation Service, U.S.D.A.
315
24-25 March 2015
GSS-2
Soil Fertility Evaluation of Middle Mountain of Nepal: a case of
Shikharpur Municipality, Kathmandu District
Raju Rai, Rajendra P Tandan and Krishna B Karki
Rajdevi Engineering Consultancy Pvt. Ltd., New Baneshwor
Abstract
An attempt is made to evaluate Soil fertility of Shankharapura recently announced
Municipality in the Kathmandu District and map them. LRMP maps of land system,
geology and land use are overlayed on the recent satellite images and polygons are
developed and sampling points are marked with their GPS points to sample. Top soil based
on these land use polygons are collected and analysed in the laboratory following methods
generally adapted by DoA and NARC. They are classified to the soil taxonomy, grouped
into different slopes, land use and land capability classes and prepare different soil fertility
maps using ArcGIS software. This municipality occupies arable and non- arable Land. The
land systems of this Middle Mountain Range fall on 9a, 9b 10a, 10b, 11 and 12 systems.
The lands are south facing with slopes ranging from 1 to 45% (32% gentle terrace, 28%
very high and the rest flat and very gentle terrace). Soils of higher percentage of slopes are
highly erodible aggravated by light sandy texture. The soils are dominated by different subgreat groups of Inceptisols (48%) and Entisols (52%). Top soils are light textured
dominated by sandy loam to loamy sand with well to excessive surface and internal
drainage. Soil organic matter is high (>5% OM) with strongly acidic pH (5.5).These soils
contain low to medium P2O5 and higher K2O. Higher amount of K2O is due to the higher
silt content in the texture. Soil fertility rating ranges from medium to high to high. Fertility
evaluation shows 23% high, 19% medium and low 27% and 31% non-arable Soils on the
higher slopes and with lighter texture and higher infiltration rate are not recommended for
rice cultivation where upland crops with legumes are suggested. In the lower valleys with
abundant water availability all arable crops including vegetables are suggested.
Keywords: GPS points, higher infiltration rate, satellite images and soil fertility maps.
Introduction
Soil productivity depends on adequate nutrient and water supply. Although total
production has increased marginally,the productivity of most existing lands in Nepal
has been declining(Joshi and Karki 1993). Improving soil fertility could trigger rural
and national economic development, achieve long-term food security and improve
farmers’ standards of living, mitigating environmental degradation and minimize rural
migration for these reasons, soil fertility and productivity enhancement have to be
supported by policies with regard to credit facilities, produce and input prices, access
to markets and secure land tenure(Jaisy and Manandhar 2004). In this context, this
paper presents soil-fertility evaluation and mapping of Shankharapur Municipality of
Kathmandu District.
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24-25 March 2015
Methods and Materials
Study Area: Shankharapur Municipality is situated in between 3067204 to 3075752
north latitude and 641030 to 654555 east longitude. Its’maximum east-west length is13
km and north south width is7.5 km. The elevation of Shankharapur Municipality
ranges from 848 to 2353 meter. This Municipality is located in eastern part of the
Kathmandu. Bajrayogini, Lapsiphedi, Nanglebhare, Pukhulachhi, Indrayani and Suntol
VDCs were merged to form this Municipality in 2014. Particularly, the Municipality
bordered withMelamchi Municipality (Sindhupalchowk District) in the east,
KageshwariMunicipality in the west, Bhotechaur VDC (Sindhupalchowk) in the north
and Changunarayan and Mahamanjushree Municipalities (Bhaktpur District) in south
(Figure 1). The Municipality occupy 60.25 km2 area of the District.
Figure 1: Location of the study area, Shankharapur Municipality.
Soil Polygon
Soil polygons were developed by overlaying existing land system, land use and
geological maps developed by LRMP in 1986 over the recent high resolution satellite
image (GeoEye-2). Seventy eight polygons were delineated and on each polygon one
soil profile was located and its GPS points were noted. Soil profiles were opened and
described following FAO soil profile description guidelines. Surface soil samples were
collected for laboratory analysis. Soil samples were air dried and passed through 2 mm
sieve, stored for physical and chemical analysis following DoA/ NARC approved
procedures. Analysis included texture (sand, silt, and clay fraction), pH, N, P, K, Boron
and Zinc, as well as organic matter. The procedure adopted while analyzing soil
samples is presented in Table 1.
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24-25 March 2015
Soil Mapping
Based on shape, size, tonal variation and color variation and relative height, the
landform and land types of the study area were identified on satellite imagery and
Digital Terrain Model. Individual soil unit to the Great Group level were classified
following Soil Taxonomy 2010 (eleventh edition).
Soil FertilityMapping
Soil analytical results were grouped based on high, medium and low categories of soil
nutrients as suggested byDeo and Joshi (1976). MCE and WCS methods were used to
calculate weighted average of the important soil nutrients and final fertility status was
developed and map is presented in Figure 3-5.
Table 1:Methods adopted in soil sample tests in laboratory.
Soil Sample Tests
Texture
pH
Organic Matter content
Phosphorous (P2O5)
Potassium (K2O)
Nitrogen (N)
Zn (ppm)
Boron (ppm)
Analysis Method
Hydrometer & Texture Classification following USDA system
1:2 soil water paste
Modified Walkley and Black wet digestion methods
Modified Olson Sodium Biocarbonateextraction and color
developed with ascorbic acid blue color and detected in
colorimeter in 546 nm.
Flame photo metric method extraction with 1 N, N Ammonium
Acetate
Microjeldahlmethod of using K2Cr2O7 as oxidizing agents with
Conc. H2SO4 digestion and back tritrated with dilute HCl.
DPTA Extraction & AAS detection as explained by (Lindsay
and Norvell, 1978)
Hot water Extraction, colorimetric detection with color
developed using Carmine, as explained in FAO Bulletin No.19
Multi-Criteria Evaluation (MCE)
MCE is a decision support tool aiding a choice to be made between alternatives. The
basis for a decision is known as a criterion. In a Multi-Criteria Evaluation, an attempt
is made to combine a set of criteria to achieve a single composite index for a decision
according to a specific objective. Decision need to be made about what areas are the
most capable for specific land use type development. In this analysis, criteria or factors
affecting capability of crops production include edaphic factors such as soil depth,
drainage condition, permeability and soil fertility factors like pH, Organic matter and
total Nitrogen (N) available Phosphorus (P) and available Potassium (K). Land
capability maps were generated from the MCE process in which parameter weight was
derived from the expert knowledge given below Table 2.
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24-25 March 2015
Table 2: Parameters and given weightage for MCE.
SN
1
Parameters
Soil Depth
Weightage
4
2
3
pH
OM
3
3
4
Drainage
3
5
K2O
2
6
P 2O 5
2
7
Nitrogen
1
8
Permeability
1
Weighted CompositeScore (WCS)
Weighted Composite Score (WCS) is a systematic procedure for developing factor
weights required for preparing capability map. The weights assigned to different
factors were obtained by subjective to expert judgment. The larger the weight, the
more important is the criterion in the overall capability class (Malczewski 1999).
In developing the weights, an individual factor were ranked as low, medium, and high
and very high weight are assigned as 1, 2, 3 and 4 respectively as given below. Factors
or criteria were rated according to the following 4-point scale. Weighted Composite
Score (WCS) was employed based on parameter weight and individual weighted value
as4, 3, 2 and 1 corresponding to very high, high, medium and low rank of concerned
factor respectively. The final value of weighted composite score (WCS) for each soil
mapping unit was calculated by summing all individual factors value obtained by
multiplying individual factor weight rank value with their corresponding weight of
parameters. The equation of calculation of WCS are given below:
Weighted Composite Score (WCS) = Soil depth weightage value*4+pH weightage*3+
Drainage weightage value*3+ OM weightage value*3+ K2O weightage value*2+ P2O5
weightage value*2+ Nitrogen weightage value*1+ Permeability weightage value*1
(Table 3).
Table 3:Rank, Weightage and Different Parameters for Fertility Calculation.
Rank
Weightage
Value
Soil
Depth,
cm
Low
1
<20
Medium
2
21-30
High
3
31-50
Very High
4
>51
pH, units
Highly
Acidic/
Alkaline
Medium
Acidic/
Alkaline
Slightly
Alkaline/
Acidic/
Neutral
‒
OM,
%
Nitrogen
%
K20
kg ha-1
P2O5
kg
ha-1
Drainage
Fertility
<2.5
<0.10
<110
<30
Poor
<35
2.5-5
0.100.20
110280
3055
Imperfect
36-45
>5
>0.20
>280
>55
Well/Moderate
>46
‒
‒
‒
‒
‒
‒
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24-25 March 2015
Soil Great Group
This study foundtwo soil orders, they areInceptisoil and Entisols withtengreat
groups.Ustarentsoccupiedabout 46.91 percent of the study area.Similarly 0.12 percent
soil is covered by Dystochrepts group.Hydrography covered by1 percent of the total
land of the Municipality. Figure 2 presents the soil great group percentage and figure 2
shows position of soil great groupin ShankharapurMunicipality.
Soil Texture
Texturerefers to the size of the particles that makes up the soil. Soil texture is an
important soil characteristic that influences stormwater infiltration into the soil and
aeration. The soilsin this Municipality aredivided intofive textural classes. About one
third (33%)of soil is sandy loam and one fourth (25.80 percent)isloamy sand indicating
light textured soils. Only 4.35 percent is loam (Figure 3). These soils are highin
infiltration and aeration whereas they are poor in moisture and nutrients
retention(Shepherd 1996). To retain the plant nutrients in soil when they are cultivated
with conservation tillage and maintaining higher humus in the soil (Chan et al. 2003).
Organic Matter
Organic matter plays a great role in agriculture. It builds stable aggregates and soil
structure. Higher soil organic carbon is needed for good structure and water stable
aggregates (Bronick and Lal 2005 Six et al. 1999). In the present study, most of the
soil samples are low to medium range.Only a few samples could be classified as high
(7.46%) at higher altitude of the Municipality due to lower temperature where
decomposition of applied organic manure is low (Kirschbaum 1995 Von Luetzow and
Koegel-Knabner 2009). Around one third area has been found as low and nearly 29
percent inmediumsoil organic matter content. The rest 31.78 percent is occupied by
public use like residential area, hydrography etc. (Figure 4).
[CATEGOR
Ustorthen Y NAME]
[VALUE] %
ts
Ustochrep
2%
ts
26%
Ustipsam
ments
2%
Figure 2:
[CATEGOR Haplanthr
Y NAME]
epts Humudept
Humustep
s
[VALUE] %
2%
ts
Hydrograp
4%
12%
hy
Plagganthr
1%
epts
4%
Ustarents
47%
Percentage distribution of Soils Great Group Levelin Shankharapur
Municipality
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24-25 March 2015
Figure 3:Distribution of Soil Great Group and TextureinShankharapur Municipality.
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24-25 March 2015
Figure4: Distribution of Availability of OM and Nitrogen in Shankharapur
Municipality.
Nitrogen
Nitrogen (N) is one of the key nutrients for crop growth and development. It is needed
in larger amount for protein building in plant system. In general there is lower content
of total nitrogen in Nepalese soil but in this case majority of soil content medium level
(33%) but 15.60 % is found high, and 11.72% is low level. Overall Nitrogen level is
goodas farmers in this area use higher amount of Farm Yard Manure and compost
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24-25 March 2015
which has contributed to the increase in total soil N. But in sloppy terraces soil erosion
is high and hence Nitrogen losses through erosion, leaching and runoff(Wang and Alva
1996) though in rainfedcrop land the level of leaching is much lower (Dalal and Chan
2001). The amount of Nitrogen has found medium (33.16%), low (19.46%), and high
(15.60) in the study area (Figure 4).
Phosphorus
Available Phosphorous (P) has great importance for crop production. Phosphorus is
essential for the maturity of crops and for root growth. The soil conditions that made
phosphorus available to plants varied greatly in the area. However, most of the soil
samples were in the medium range 36.64% (Figure5) and availability of P is not a
problem (Hinsinger 2001). Only a few soil samples had a low P levels. High content of
soil organic matter improves general soil condition and suppliesa part of P to the soils.
Because of sandy soils the applied P could have been lost through leaching (Ozanne et
al. 1961)or with soil erosion.
Potassium
Potassium is a primary plant nutrient that plays a major role to achieve higher
productivity. Most potassium (K) in plants is found in the above-ground portion,
mainly in straw. Therefore, if crop residues are returned to the soil, a good proportion
of the potassium is added for crop availability (Rosolem et al. 2005). Soils, potassium
is found as part of the mineral structure of many clay minerals particularly micas and
silt (Mengel et al.and Dou 1998). Soil tests have shown that availableK content in the
soil was generally high (Figure 5). Only 1.35 percent was found low. Soils that have
high clay content can retain high levels of Potassium reserves. Availability of the
Potassium depends on the type of clay and several other factors(Sadusky et al.
1987).However, in sandy soils, soil K is lost through leaching (Jalali and Rowell 2003,
Rosolem et al. 2005).
Soil pH
Soil pH is an important factor for crop production. It measures the degree of acidity or
alkalinity of soil, both of which plays a vital role. The range of soil pH in the study
area has been found between 4.7 to 7.7. Since soil pH is controlled by several factors
such as clay and organic matter content in the soillime requirement, study should be
conducted before adding any lime (Karki 1987). However, well decomposed organic
manure is as good as lime since it buffers soil pH (Bagayoko et al. 2000, Karki 2006)
either lime or higher amount of manure is needed. Table 4 shows distribution of pH in
soil in Shankharapur Municipality.
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24-25 March 2015
Figure 5: Availability of P2O5 and K2O in Shankharapur Municipality.
Table4: pH of Soils in Shankharapur Municipality.
SN
pH Rating
Area (km2)
1
N/A
19.15
2
Highly Acidic
17.72
3
Slightly Acidic
5.34
4
Medium Acidic
7.07
5
Neutral
1.17
6
Very Highly Acidic
9.81
Total
60.25
324
Percent
31.78
29.41
8.86
11.73
1.95
16.28
100.00
24-25 March 2015
Present Land Use
The present land use mapping was carried out from high resolution of satellite images
constellation along with visual interpretation and extensive field verification. In this
study, present land use were grouped into five categories. More than two thirds (68 %)
of land is covered by agriculture. The second largest (28%) area is covered by forest.
Similarly, residential area, public use and commercial area are covered by less than 2
percent each (Figure 6).
Figure6: Spatial Distribution of Present Land Use of Shankharapur Municipality.
Soil Fertility Status
Soil fertility refers to the ability of soil to supply essential plant nutrients and soil water
in adequate amounts and proportions for plant growth and reproduction in the absence
of toxic substances. Evaluation of soil fertility is calculated on the basis of weightage
average of soil nutrient. Soil fertility is grouped into three categories. Present study
shows that 23.79 percent land has high, 25.97 percent medium and 18.45 percent low
fertility level (Figure 7).Of the total land 31.78 percent land in Shankharapur
Municipalitycovered by nonagricultural use.
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24-25 March 2015
Figure7:Spatial distribution of Soil Fertility in Shankharapur Municipality.
Land Capability
The arable soils are grouped according to their potentialities and limitations to sustain
production of the common cultivated crops that do not require specialized amendment.
Non-arable soils are grouped according to their potentialities and limitations for the
production of permanent vegetation as per their risks of soil damage. Land capability
classes comprise of seven classes ranked in order of increasing degree of limitation and
in decreasing order of adaptability for agricultural use. Class I land is identified as the
best suited land and it can produce wider range of crops and pastures at higher levels of
production with lower costs and/or with less management requirements and/or less risk
of damage to land compared to other higher class II, III, IV and V.
Land capability classification of the land type units has done on the basis of WCS and
MCE criteria of soil and other parameters. In this study, land capability classes are
found I to VI. More than one third area (34.42 percent) land is found of class I, 32.85
percent in class III. Similarly, 13.56, 10.40, 5.25, 3.51 percent found of class II, VI, V,
IV respectively (Figure 8).
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24-25 March 2015
Figure 8: Spatial Distribution of Land Capability in Shankharapur Municipality.
Conclusion
On the whole soil fertility of this Municipality can be regarded as good. Ten different
great groups of soil taxonomy of twosoil orders which are Inceptisols and Entisols
arefound in this area. Analyzed surface soils exhibit sandy loam and loamy sand
domination which is highly susceptible to erosion. Soil reaction is dominated by
strongly to slightly acidic, total N and P2O5 is at the medium level and K2O is high.
Soil organic matter content is medium. Nearly seventy percent land is arable which has
26 percent is medium in soil fertility rating and 24 percent land high in this
Municipality. The use of land resources without proper management can result in
accelerated loss of soil nutrients, soil erosion, floods, landslides andultimately land
degradation and desertification. More than one third area (34.42 percent) land is found
of class I, 32.85 percent in class III. Similarly, 13.56, 10.40, 5.25, 3.51 percent found
of class II, VI, V, IV respectively.Proper land use based agriculture on the basis of
land’s capability and application of conservation measures to preserve capability
requires careful planning.
Acknowledgement
The authors gratefully acknowledge theNational Land Use Project (Government of
Nepal) for the use of the data. We also are thankful toProf. Dr. Hriday L. Koirala,
Associate Professor Dr. BhojrajKareriya and Mr. Umesh Kumar Mandal (TU, Central
Department of Geography) for their encouragement and supports. Similarly, the group
thanks Laxmi Basnet (GIS Expert and Geographer) for her help in maps preparation
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24-25 March 2015
and Rajdevi Engineering Consultant P.Ltd., Baneshwor, Kathmandu for the facilitiesin
preparing this article.
Reference
Bagayoko M, S Alvey, G Neumann and A Buerkert. 2000. Root-induced increases in
soil pH and nutrient availability to field-grown cereals and legumes on acid
sandy soils of Sudano-Sahelian West Africa. Plant and Soil. 225:117-127.
Bronick CJ and R Lal. 2005. Soil structure and management: a review. Geoderma.
124:3-22.
Chan KY, DP Heenan and HB So.2003. Sequestration of carbon and changes in soil
quality under conservation tillage on light-textured soils in Australia: a review.
Australian J. Expt. Agric..43:325-334.
Dalal RC, and KY Chan. 2001. Soil organic matter in rainfed cropping systems of the
Australian cereal belt. Soil Research. 39:435-464.
Deo GP and D Joshi. 1976. Fertilizer recommendation to major field crops. Soil
Science Division, Kathmandu. Pp. 76.
Hinsinger P. 2001. Bioavailability of soil inorganic P in the rhizosphere as affected by
root-induced chemical changes: a review. Plant and Soil. 237:173-195.
Jaisy SN, and R Manandhar. 2004. HMG Policy and Programmes towards Sustainable
Soil Fertility Management, HICAST, Bhaktapur. Green Field J.Agric. Sci.
Techn.4:5
Jalali M and DL Rowell. 2003. The Role of Calcite and Gypsum in the leaching of
Potassim in a Sandy Soil. Expt. Agric. 39:379-394.
Joshi D and KB Karki. 1993. Soil fertility and fertilizer use in Nepal. HLS
Tondon(ed.). Soil fertility and fertilizer use in Asia. Development Consulting
Services, New Delhi.
Karki KB. 1987. First Review/Working Group Meeting on Bio-fertiliser Technology,
Kathmandu, Nepal. November 15-16, 1987. Soil Science Division, Khumaltar.
Karki KB. 2006. City waste compost and sustainability of Rice-Wheat cropping
system. Nepal Agriculture Research J.7:49-53.
Kirschbaum MUF. 1995. The temperature dependence of soil organic matter
decomposition, and the effect of global warming on soil organic C storage. Soil
Biol. Biochem. 27:753–760.
Lindsay WL and WA Norvell. 1978. Development of a DTPA Soil Test for Zinc, Iron,
Manganese, and Copper1. Soil Sci. Soc. Amer. J. 42:421-428.
Malczewski J. 1999. GIS and Multi-criteria decision analysis. New York: John Wiley
and Sons Inc.
Mengel K, Rahmatullah and H. Dou. 1998. Release of Potassium from the Silt and
Sand Fraction of Loess-derived Soils. Soil Science.163:805-813.
Ozanne PG, DJ Kirkton and TC Shaw. 1961. The loss of phosphorus from sandy soils.
Australian J. Agric. Res.12:409-423.
Rosolem CA, JC Calonego and JSS Foloni. 2005. Potassium Leaching from Millet
Straw as Affected by Rainfall and Potassium Rates. Comm. Soil Sci. Pl.
Anal.36:1063-1074.
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Sadusky MC, DL Sparks, MR Noll and GJ Hendricks. 1987. Kinetics and Mechanisms
of Potassium Release from Sandy Middle Atlantic Coastal Plain Soils1. Soil
Sci. Soc. Amer. J. 51:1460-1465.
Shepherd MA. 1996. Factors affecting nitrate leaching from sewage sludges applied to
a sandy soil in arable agriculture. Agric. Eco. Environ.58:171-185.
Six J, ET Elliott and K Paustian. 1999. Aggregate and Soil Organic Matter Dynamics
under Conventional and No-Tillage Systems. Soil Sci. Soc. Amer. J. 63:13501358.
Von Luetzow M and I Koegel-Knabner. 2009. Temperature sensitivity of soil organic
matter decomposition-what do we know? Biology and Fertility of Soils. 46:115.
Wang FL and AK Alva. 1996. Leaching of Nitrogen from Slow-Release Urea Sources
in Sandy Soils. SoilSci. Soc. Amer. J. 60:1454-1458.
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GSS-3
Assessment of Soil Fertility Status and Preparation of Their Maps of
National Wheat Research Program (NWRP), Bhairahawa, Nepal
Dinesh Khadka1, Sushil Lamichhane1, Binita Thapa1, Nabin Rawal2, Dev R Chalise2,
Shree P Vista1, and Laxman Lakhe1
1
Soil Science Division (NARC), Khumaltar, Nepal
National Wheat Research Program (NARC), Bhairahawa
2
Abstract
A study to examine soil fertility status and preparation of their maps of the
National Wheat Research Program, Bhairahawa was conducted. The research farm
is situated within latitude 27º31’49”N and longitude 83º27’36”E at altitude 82
masl. Fifty eight samples were collected randomly at depth 0-20 cm. The specific
locations of various soil sampling points were identified using Global Positioning
System (GPS). Soil samples thus collected were analyzed for their texture, pH,
OM, N, P, K, Ca, Mg, S, Zn, Fe, Cu, and Mn status following standard methods in
the laboratory of SSD, Khumaltar. The soil fertility status maps of each nutrient
were prepared on Arc-GIS 10.1 software platform. Evaluation of soil test data
showed that the soil was silt-loam in texture, slightly to moderately alkaline in pH
(7.11- 8.34) and low to high in Organic Matter (0.86-3.6%). acronutrients
low to high total N (0.04 - 0.18%), low to very high available phosphorus (16-195
kg ha-1), very low to high extractable potassium (21- 309 kg ha-1), low to high
extractable calcium (740 - 3580 ppm), low to high extractable magnesium (24 -581
ppm) and very low to high available Sulphur (1- 25.5 ppm) were observed.
Similarly, the status of micronutrients was found to be medium to very high in
DTPA-Zinc (1.1-7 ppm), very high in DTPA-Iron (40-155.8ppm), medium to very
high in DTPA-Copper (1-3ppm), very low to high in DTPA-Manganese (2.414ppm) and very low to very high in hot water Boron (0.01 - 2.5 ppm). The overall
evaluation of the research farm revealed very high variation on the fertility status,
which might be due to the heterogeneity on the management practices for various
research purposes within the farm. Considering this variation in fertility status,
application of the fertilizer dose to each crop based on the soil test rather than on a
blanket approach is highly advisable to make research works more consistent and
the farm more sustainable. Nutrient categories depicted on the prepared soil
fertility maps can serve as an important aid in this regard.
Keywords:
Extractable magnesium, global positioning system (GPS), soil fertility
maps soilfertility status.
Introduction
Soil being the natural medium for plant growth has a direct impact on yield and quality
of crops growing on it. It plays a major role in determining the sustainable productivity
of an agro-ecosystem. Sustainable productivity of soil mainly depends upon its ability
330
24-25 March 2015
to supply essential plant nutrients to the ongoing crops. Soil fertility is defined as the
ability of a soil to supply essential elements for plant growth without a toxic
concentration of any element (Foth 1990). It is determined by the presence or absence
of essential nutrients. The success or failure of agriculture is closely related to the
existing soil conditions. A shortage of nutrients can cause serious restrictions to crop
growth, thereby decreasing soil fertility and crop productivity.
Soil fertility evaluation is a central feature of modern soil management. The
fundamental purpose of soil fertility evaluation has always been to quantify the ability
of soils to supply the nutrients required for optimum plant growth. Knowing this, we
can optimize nutrient management practice needed to achieve economically optimum
plant performance. Soil testing is a key tosoil fertility evaluation. It includes
evaluation,interpretation, fertilization and amendment recommendations based on the
result ofphysio-chemical analyses and other considerations (Peck and Soltanpour
1990).Describing the spatial variability of soil fertility across a field has been difficult
until new technologies and tools such as Introduction of Global Positioning Systems
(GPS) and Geographic Information Systems (GIS). These tools have helped us in
collecting, storing, retrieving, transforming and displaying spatial data (Burrough and
McDonnell 1998).
National Wheat Research Program (NWRP) was established in western region of
Nepal to run the wheat research efficiently. Soil fertility conditions of this research
farm aredeteriorating gradually because of blanket application of macro-nutrients
regularly. Crop performance in the farm is also not satisfactory due to the problems
caused by soil infertility. The assessment of nutrient status ofthe farm as well as
preparation of nutrients status maps are not been done yet and hence this study
conducted.
Description of the study area
National Wheat Research Program (NWRP) lies in Bhairahawa of Rupandehi district.
This research farm is geographically situated within latitude 27º31’49”N and longitude
83º27’36”E at altitude 82 m above sea level (Figure 1). It has a total of 35 hectares of
land area out of which 25 hectares isutilized for wheat research and production
activities.Rest 10 hectares isoccupied by farm roads drainage, office and residence
facilities. The climate at NWRP is sub-tropical. It has total 6 blocks namely, A, B, C,
D, E and F (Figure1).
Soil Samples Collection
Total Fifty eight Soil samples were collected randomly at 0-20 cm depth during October
2013based on the variability of the land on each block. Distribution of soil samples points
from each block are shown on the fig 2. Specific locations of various soil sampling
points were identified using Global Positioning System (GPS) receiver.
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24-25 March 2015
Figure 1: Location of National Wheat Research Program (NWRP) Bhairahawa, Nepal.
Figure 2: Distribution of soil sample points in National Wheat Research Program
(NWRP)
Laboratory analysis of samples
The collected samples were dried at room temperature and ground to pass through
2mm sieve and stored in a plastic container. They are analyzed in the laboratory for the
determination of different physic-chemical properties in SoilScience Division,
332
24-25 March 2015
Khumaltar. The different methods adopted for Physical and chemical properties
determinations are listed under the Table 1.
Descriptive statistics (mean, range, standard deviation, standard error) of soil
parameters were computed from the Microsoft office excel 2007 and employed to
compare the results of each block. Rating is done as low, medium andhigh of
determined value. Geostatistical analyst extension of ArcGIS 10.1 software platform
was used to prepare soil fertility maps. Soil sample points were fitted with different
semivariogram models for different soil parameters in order to achieve optimum
surface prediction using Kriging technique. Alternative semivariogram models were
compared based on various prediction errors, viz. root-mean-square, mean
standardized, root-mean-square standardized and average standard error.
Physical Parameter
Soil Texture
Texture is the relative proportions of sand, silt, and clay in a soil. Texture is an
important property of soils because it determines the surface area of solids per unit
volume or mass of soil. The study area revealed,majority area have silt loam to silty
clay loam textural classin the farm.
Chemical Parameters
Soil pH
Soil pH is very important property as it relate to nutrient availability, microbial activity
and physical condition of the soil. Result of this study area showed, soil was
moderately alkaline in the reaction (Figure 3). The range of soil pH was 7.11-8.34.
Mean value 8.0 was observed on the Block-A while,the lowest meanvalue (7.7) was
recorded on the four blocks namely; C, D, E and F (Table 2).
Table 1: Parameters and methods adopted for the laboratory analysis.
S.N.
1.
2.
2.1
2.2
2.3
2.3.1
2.3.2
2.3.3
2.3.4
2.3.5
2.3.6
2.4
Parameters
Physical
Soil Texture
Chemical
Soil pH
Soil organic matter (SOM)
Macro-nutrients
Total nitrogen
Available P2O5
Extractable K2O
Extractable calcium (Ca)
Extractable calcium (Mg)
Available Sulphur (SO4-S)
Micro-nutrients
Methods
Hydrometer (Bouyoucos 1927) USDA Soil textural
groups
Potentiometric 1:2 (Jackson 1973)
Walkely and Black (Walkely 1947)
Kjeldahl (Bremner and Mulvaney 1982)
Modified Olsen’s (Olsen et al.1954)
Ammonium acetate (Jackson 1967)
EDTA Titration
EDTA Titration
Turbidimetric(Verma 1977)
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24-25 March 2015
2.4.1
2.4.2
2.4.3
2.4.4
2.4.5
Available Boron
Available Iron
Available Zinc
Available Manganese
Available Copper
Hot water (Berger and Truog 1939)
DTPA (Lindsay and Norvell 1978)
Table 2: Soil fertility status of the National Wheat Research Program, Bhairahawa.
Blocks
D
(n=10)
Parameters
A
(n=9)
B
(n=11)
C
(n= 11)
Soil Texture
(Class)
Silt Loam
to Silty
Clay
Loam
Silt Loam
To
Silty
Clay Loam
Silt Loam
to
Silty
Clay Loam
Silt Loam
to
Silty
Clay
Loam
8.0
7.5-8.3
0.20
0.047
7.9
7.2-8.3
0.27
0.06
7.7
7.2-8.0
0.23
0.06
1.7
0.9-2.4
0.32
1.9
1.4-2.2
0.25
0.08
0.05
Soil pH
Mean
Range
StDev.
Standard
Error
SOM %
Mean
Range
StDev.
Standard
Error
E
(n=9)
Silt
Loam to
Silty
Clay
Loam
F
(n=8)
7.7
7.1-8.1
0.30
0.07
7.7
7.2-8.1
0.26
0.06
7.7
7.4-8.0
0.18
0.04
2.5
2.1-3.0
0.28
2.3
1.4-3.6
0.52
2.1
1.4-2.8
0.53
2.2
1.5-2.9
0.42
0.06
0.12
0.08
0.11
Silt Loam
to
Silty
Clay Loam
Soil Organic Matter
It is now widely recognized that SOC plays an important role in soil biological
(provision of substrate and nutrients for microbes), chemical (buffering and pH
changes) and physical (stabilization of soil structure) properties. Study revealed that
soil organic matter of this farm is medium (Figure 3)thoughthe range of soil organic
matter was 0.87-3.6%. The mean of 2.5% was observed on the block-C while, lowest
mean 1.7% was on the Block-A (Table 2).
Total Nitrogen
Nitrogen is the most important plant nutrient for crop production. It is a constituent of
the building blocks of almost all plant structures. In the past 50 years, increased N
fertilizer use and better N management were the major contributors to large increases
in global food production (Smil, 2001). Soil analyzed data revealed, mediumstatus in
the total nitrogen on the majority of the study area (Figure 4). The range of total
nitrogen determined was 0.04-0.18%. The mean of 0.14% was observed on the block-C
while, lowest 0.08% was observed on the block- B (Table 3).
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24-25 March 2015
Figure 3: Soil pH and organic matter status of National Wheat Research Program.
335
24-25 March 2015
Table 3:Macronutrient status of National Wheat Research Program, Bhairahawa.
Parameters
A
(n=9)
B
(n=11)
Blocks
C
(n= 11)
D
(n=10)
E
(n=9)
F
(n=8)
Total Nitrogen %
Mean
Range
0.09
0.06-0.11
0.08
0.04-0.17
0.14
0.10-.18
0.12
0.08-0.17
0.09
0.05-0.17
0.11
0.05-0.16
StDev.
0.017
0.039
0.029
0.027
0.04
0.045
Standard Error
0.006
0.012
0.009
0.009
0.012
0.016
Av. P2O5
kg ha-1
Mean
61.99
73.95
66.71
61.44
99.75
97.61
Range
34-100
16-113
18-96
31-112
42-195
59-157
StDev.
16.37
29.36
18.11
6.49
45.76
24.90
Standard Error
3.86
6.41
3.70
5.13
10.79
6.22
Mean
106
109
107
84
105
184.8
Range
62-186
62-309
21-199
34.9-144.5
62.3-144.5
103.4-281.6
StDev.
32.4
56.1
54
27.6
26.1
47.9
Standard Error
7.64
12.24
10.96
6.17
6.16
11.96
Mean
1911.1
1983.64
2270.9
1070.0
868. 9
1097.5
Range
1580-2260
1280-3580
1920-2620
920-1280
740-1140
760-1440
St.Dev.
230.02
590.78
227.40
124.81
131.19
247.83
Standard Error
76.67
178.128
68.56
39.47
43.73
87.62
Mean
250.6
249.7
209
209.3
135.79
133.1
Range
72.6-484
145.2-387.2
121-399.3
96.8-338.8
24.2-580.8
72.6-229.9
St.Dev.
122.75
70.20
81.37
60.92
168.94
51.74
Standard Error
40.92
21.16
24.53
19.26
56.31
18.29348
Mean
6.57
10.79
10.09
5.77
7.59
9.88
Range
2.5-16.5
1.34-16.5
1-16.67
1-10.83
2.17-12
2-25.5
St.Dev.
4.33
3.88
5.77
3.29
3.71
7.43
Standard Error
1.44
1.17
1.74
1.04
1.24
2.63
Ex. K2O kg ha-1
-1
Ext. Ca mg kg
Ext. Mg mg kg-1
Av. SO4-S mg kg-1
Available Phosphorus
Phosphorus is also one essential nutrientfor plant growth. Its functions
cannotbeperformed by any other nutrient, andanadequate supply of P is required for
optimumgrowth and reproduction.The highamount of the available phosphorus was
observed in the majority of the study area (Figure 4). The range of available
phosphorus recorded was 16.1-195.0 kg ha-1. The mean value99.75 kg ha-1 was highest
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observed on the block-E while, lowest mean value 61.44 kg ha-1 was on the BlockD(Table 3).
Potassium (K) is one of the three major elements that play important roles in plants,
such as maintaining turgor of cells, promoting activation of enzymes, and improving
efficiency of photosynthesis. The lowest amount of extractable potassium was
observed in the majority of the study area (Figure 4).
Extractable Calcium
Calcium acts as a structural component of plant cell walls, which is most abundant in
plant leaves. It is involved in cell growth, both at the plant terminal and at the root tips,
and apparently enhances uptake of nitrate-N. The analyzed data depicted, medium
status of extractable calcium on the majority of the study area (Figure 5). The range of
extractable calcium determined was 740-3580 mg kg-1. Comparing the means among
the soil analysis results the highest mean (2270.9 mg kg-1) was observed in the block-C
while lowest (868. 9 mg kg-1) in the block-E (Table3).
Extractable Magnesium
Magnesium is a primary constituent of chlorophyll, and chlorophyll usually accounts
for 15 to 20% of the total Mg+2content inplants (Havlin et al. 2010). Medium to high
status of extractable magnesium was observed in the majority of the study area (Figure
5). The range of magnesium determined was 24.2-580.8 mg kg-1. Among the Blocks
the highestmean(250.6 mg kg-1) was observed in the block-A whereasthe lowest
(133.1mg kg-1) was in the block-F (Table3).
Available Sulphur
Sulphur is the most abundant element on the earth’s crust (Havlin et al.2010). It is
required for synthesis of S containing amino acids cystine, cysteine and methionine
which are building blocks of proteins and is an important constituent of vitamins and
hormones (Sylvia et al. 2005). The analyzed data showed,low to medium status of
available sulphur on the majority of the study area (Figure 5). The range of available
sulphur was 1-25.5mg kg-1. Among the blocks the highest mean (10.79 mg kg-1) was
observed in the block-B whereas the lowest (5.77 mg kg-1)in the block-D(Table3).
Available Boron
Boron is a non-metal occurs in low concentrations on the earth’s crust. it is neither an
enzyme constituent nor is there convincing evidence that it directly affects enzyme
activities. Very low status of available boron was observed in the majority of the study
area (Figure 6). The range of available boron content was 0.01-2.47 mg kg-1. The
highest blockmean (0.47 mg kg-1) was observed on the block-A while the lowest (0.07
mg kg-1) was in the two blocks namely; E and F (Table4).
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Available Zinc
Zinc is an essentialelement for the normal growth and metabolism ofplants that plays
very important role in enzymeactivation and was also involved in the biosynthesisof
some enzymes and growth hormones (Ranja andDas, 2003).Mediumstatus of available
Zinc was observed on the majority of the study area (Figure 6). The range of available
Zinc was 1.1-7.0 mg kg-1.The highestmean (4.6mg kg-1) was observed in the blockEwhile, lowest mean (1.58mg kg-1) was in the block- C (Table 4).
Figure 4: Primary nutrient status of National Wheat Research Program.
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Figure 5: Secondary nutrient status of National Wheat Research Program.
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Figure 6: Micronutrient status of National Wheat Research Program.
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Figure 7: Micronutrient status of National Wheat Research Program.
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Table 4:Micronutrient status of National Wheat Research Program, Bhairahawa
Parameters
A
(n=9)
B
(n=11)
C
(n= 11)
Mean
0.47
0.21
0.43
Range
0.081.01
0.01-1.02
St.Dev.
0.35
Standard Error
Blocks
D
(n=10)
E
(n=9)
F
(n=8)
0.12
0.07
0.07
0.01-2.47
0.020.54
0.03-0.13
0.03-0.1
0.29
0.72
0.19
0.03
0.03
0.12
0.09
0.21
0.06
0.01
0.01
Mean
49.07
65.16
86.36
76.36
79.39
94.0
Range
40-60.27
51.47-86.6
44.67138.67
52.1120.2
53.33-133.2
59.93-155.8
St.Dev.
6.32
11.96
31.94
25.40
29.90
32.13
2.11
3.61
9.63
8.03
9.97
11.36
Mean
Range
St.Dev.
1.86
1.5-2.67
0.37
1.60
1.2-2.13
0.25
1.85
1.2-2.3
0.412
2.14
1.73-2.8
0.330
1.54
1.0-2.2
0.39
2.23
1.47-3.0
0.60
Standard Error
Av. Zn mg kg-1
0.12
0.075
0.124
0.10
0.13
0.21
Mean
2.2
4.54
1.58
2.22
4.60
2.53
Range
St.Dev.
1.5-2.87
0.47
3.6-5.6
0.66
1.1-2.47
0.437
1.67-2.8
0.42
2.8-7
1.50
1.6-4.8
0.99
Standard Error
0.17
0.20
0.132
0.13
0.50
0.35
Mean
3.9
4.2
7.48
9.79
8.86
7.00
Range
2.5-6.13
2.47-7
2.4-13.4
4.4-14.2
3.47-9.8
St.Dev.
1.158
1.51
3.035
4.3313.2
2.52
3.79
2.67
Standard Error
0.39
0.46
0.92
0.80
1.26
0.94
Av. B mg kg-1
Av. Fe mg kg-1
Standard Error
-1
Av. Cu mg kg
Av. Mn mg kg-1
Available Iron
Iron is probably the most abundant element in the world.Iron is important in the
activation of several enzyme systems in plants including: fumaric hydrogenase,
catalase, oxidase, and cytochrome.Very high status of available Iron was observed on
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the majority of the study area (Figure 6). The range of available iron was 40-155.8 mg
kg-1.The highestmeanamong the blocks(94.0mg kg-1) was observed in the blockFwhile, lowest mean (49.07mg kg-1) was in the block-A (Table 4).
Available Manganese
Manganese in nature is found as oxides, carbonates, and silicates.Manganese is
important in activating many plant enzymes in the metabolism of organicacids,
phosphorus, and nitrogen.Low status of available Manganese was observed in the
majority of the study area (Figure 7). The range of manganese content was 2.4-14.2 mg
kg-1.The highestmean (9.79mg kg-1) was observed in the block-Dwhile, lowest mean
(3.9 mg kg-1) was in the block-A (Table 4).
AvailableCopper
Copper is found in nature in the form of sulfates, sulfides, sulfosalts, carbonates and
othercompounds.Copper plays an important role in plant enzymes and enzymesystems.
Copper deficiencies can affect photosynthesis, respiration, carbohydratedistribution, N
metabolism, cell wall metabolism, water relations, seed production anddisease
resistance. High status of available copper was observed on the majority of the study
area (Figure 7). The range of available Copper content was 1.0-3.0 mg
kg-1.The highestmean(2.23 mg kg-1) was observed in the block-F while, lowest mean
(1.54 mg kg-1) was in the block-E(Table 4).
Conclusion
An attempt is made to study Soil analysis of National Wheat Research Farm analysis
58 soil samples from the surface horizon (0-20 cm). Soil analysis revealed that the soil
texture of the farm is silty clay loam with mildly alkaline in nature. Among the
macronutrientssuch as total N, available P2O5, extractable K2O, extractable Ca,
extractable Mg and available S are observed in varied amount. Obviously
themacronutrients content as residue is observed as medium to high as they are applied
to every crop grown in the farm and the soil pH is high. Among the micronutrients
copper and iron content was found as higher level, zinc content as medium but
manganese and boron low. From this study it can be concluded that due to presence of
varied amount of nutrients in soil regular monitoring of residual soil nutrients is
necessary and apply only the required amount of macro and micronutrients.
Acknowledgement
Authors are very much thankful to National Wheat Research Program, Bhairahawa
forproviding support for the soil samples collection. Similarly, Soil Science Division,
Khumaltar for providing laboratory facilities to analyze the soil samples and
preparation of soil fertility maps.
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References
Berger KC and E Truog. 1939. Boron determination in soils and plants. Ind. Eng. Anal.
Ed. 11: 540 – 545.
Bremner JM and CS Mulvaney. 1982. Nitrogen total. Methods of soil analysis. Agron.
No. 9, Part 2: Chemical and microbiological properties, 2nd ed. AL Page. (ed.),
Am. Soc. Agron., Madison, WI, USA. Pp.595 – 624.
Burrough PA and RA McDonnell. 1998. Principlesof Geographical Information
Systems. OxfordUniversity Press, New York.
Foth HD. 1990. Fundamentals of soil science. New York: John Wiley and Sons.
Havlin JL, JD Beaton, SL Tisdale and WL Nelson. 2010. Soil Fertility and Fertilizers:
An Introduction to Nutrient Management. 7th ed. Pearson Prentice Hall. New
Jersey.
Jackson ML. 1967. Soil chemical analysis. Prentice Hall of India Pvt. Ltd., New Delhi.
Lindsay WL and WA Norvell. 1978. Development of a DTPA soil test for zinc, iron,
manganese, and copper. Soil Sci. Soc. Amer. J. 42: 421 – 428.
Olsen SR and LE Sommers. 1982. Phosphorus. Methods of soil analysis, Agron. No. 9,
Part 2: Chemical and microbiological properties, 2nd ed. (A. L. Page, ed.), Am.
Soc. Agron., Madison, WI, USA. Pp.403 – 430
Olsen SR, CV Cole, FS Watanabe and LA Dean. 1954. Estimation of available
phosphorus in soils by extraction with sodium bicarbonate. U. S. Dep. Agric.
Circ. 9, USA. 39.
Peck TR and PN Soltanpour. 1990. The principles of soil testing.Soil testing and plant
analysis, 3rd ed. (R.L. Westerman, ed.). Soil Sci. Soc. Amer.3:1-9.
Smil V. 1999. Nitrogen in crop production: an account of global flows. Global
Biogeochemical Cycles, 13. Pp.622-647.
Sylvia DM, JJ Furhmann, PG Hartel and DA Zuberer .2005. Principles and
Application of Soil Microbiology. 2nd ed. Pearson Prentice Hall. New Jersey
Verma BC. 1977. An improved turbidimetric procedure for the determination of
sulphate in plants and soils. Talanta. 24: 49 – 50.
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GSS-4
Preparation of VDC Level Land Use, Soil and Land Capability Maps of
Chaumala VDC,Kailali
Chalise1, Abhasha Joshi1, Chet R Bam2, Bikesh Twanabasu3, Nabin Rawal1 and
Saroj Amgai3
D
1
National Wheat Research Programme (NARC), Bhairahawa
Survey Department, Ministry of Land Reform and Management, Minbhavan, Kathamandu
3
Cube Info Company Pvt. Ltd, Lalitpur
4
Lamjung Campus, IAAS (TU), Lamjung
2
Abstract
A research was conducted to characterize soils of different land uses to prepare VDC level
land use map, soil and land capability maps in August, 2014 in Chaumala VDC of Kailali
district. A total of 87 soil pits from different land uses were studied and soil samples from
surface soils (0-20 cm soil depth) were analysed for different physico-chemical
. Altogether seven land uses were found in the project VDC viz. agriculture,
residential, commercial, industrial, forest, public services and others category with forest
pH
covering 66.53% and commercial area covering only 0.12% of total land use area.
range
6.2 (slightly acidic) to 7.8 (moderately alkaline). Total nitrogen ranged from
0.02% (very low) to 0.35% (low), whereas available phosphorus from 36 kg ha-1 (medium)
to 751 kg ha-1 (very high). Available potassium was low (81 kg ha-1) to medium (349 kg
ha-1). A total of thirteen land capability classes were observed in the project area with
IAu/1 covering 26% and IIAu/1R covering only 0.07% of the area.
Keywords: Available potassium, land capability, land use, soil pH and total nitrogen.
Introduction
Land use planning is the systematic assessment of the land and water potential,
alternatives for land use and economic and social conditions in order to select and
adopt the land use options (FAO, 1993). Land is the only natural resource that is at the
centre of all economic activities. An inventory of skilfully classified land, according to
various economic uses, has been an important database for governments, planners and
policy makers. At the country level, these databases are being produced using available
resources and reflecting local needs. Studies have shown that there remain only few
landscapes on the Earth that is still in their natural state. The land use/land cover
pattern of a region is an outcome of natural and socio–economic factors and their
utilization by man in time and space. Land is becoming a scarce resource due to
immense agricultural and demographic pressure. Hence, information on land use / land
cover and possibilities for their optimal use is essential for the selection, planning and
implementation of land use schemes to meet the increasing demands for basic human
needs and welfare. This information also assists in monitoring the dynamics of land use
resulting out of changing demands of increasing population. Land use and land cover
change has become a central component in current strategies for managing natural
resources and monitoring environmental changes. The advancement in the concept of
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24-25 March 2015
vegetation mapping has greatly increased research on land use land cover change thus
providing an accurate evaluation of the spread and health of the world’s forest,
grassland, and agricultural resources has become an important priority. Viewing the
earth from space is now crucial to the understanding of the influence of human
activities on the natural resource base over time. In situations of rapid and often
unrecorded land use change, observations of the earth from space provide objective
information of human utilization of the landscape. Over the past years, data from Earth
sensing satellites has become vital in mapping the Earth’s features and infrastructures,
managing natural resources and studying environmental change. One concept that has
much merit is that land use refers to, "man's activities on land which are directly
related to the land" (Clawson and Stewart 1965). Land cover, on the other hand,
describes, "vegetational and artificial constructions covering the land surface" (Burley
1961).
In almost any classification process, it is rare to find the clearly defined classes that one
would like. In determining land cover, it would seem simple to draw line between land
and water until one considers such problems as seasonally wet areas, tidal flats, or
marshes with various kinds of plant cover. Decisions that may seem arbitrary must be
made at times, but if the descriptions of categories are complete and guidelines are
explained, the inventory process can be repeated. The classification system must allow
for the inclusion of all parts of the area under study and should also provide a unit of
reference for each land use and land cover type (Anderson 1971).
Remote Sensing (RS) and Geographic Information System (GIS) are now providing
new tools for advanced ecosystem management. The collection of remotely sensed data
facilitates the synoptic analyses of Earth - system function, patterning, and change at
local, regional and global scales over time; such data also provide an important link
between intensive, localized ecological research and regional, national and
international conservation and management of biological diversity (Wilkie and Finn
1996).
Therefore, attempt is being made to map out the present status (updated) of land use,
land capability, soil and map theme at the VDC level using Geographic Information
System and Remote Sensing.
The study VDC lies in northern-most part of Kailali district along East-West Highway
covering 143.38 square meters as shown in the Figure 1.
A total of 87 surface soil samples from different land uses were collected. The
collected soil samples were air- dried and sieved through 2 mm and a portion is passed
through 0.2 mm sieves for soil organic matter analysis. The soil samples were labelled
and kept in cool and dry place for physico-chemical analyses. The geographic
coordinates of the pit locations were recorded on the spot using portable GPS receiver.
Soil analyses for different properties were carried out by following standard methods
(Table1).
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24-25 March 2015
Figure 1: Location of study VDC in Kailali district.
General land use pattern
Altogether seven land uses were recorded in the project VDC viz. Agriculture, forest,
residential, commercial, industrial, public service and others category with forest
covering the highest (66.53%) and commercial area covering the lowest (only 0.12%)
of total land use area.
Table 1:Laboratory analysis techniques for different soil physical and chemical
properties.
S.N. Soil parameters
Method
1
Particle size fraction and texture
Hydrometer and Texture
classification/USDA Texture triangle
2
pH
1:2.5 soil water paste
3
Organic matter content (OM %)
Walkley and Black
4
Total Nitrogen content (Total N
Kjeldahldigestion and distillation
%)
5
Available Phosphorus (P2O5
Olsen Sodium bicarbonate extraction for
kg/ha)
alkaline soil & Bray P1 for acidic soils
6
Available Potassium (K2O kg/ha) Flame photometric method
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7
Boron (B)
Hot water extraction method
8
Zinc (Zn)
DTPA extraction method
All soil samples were analysed in the Regional Soil Testing Laboratory, Pokhara.
Figure 2: Present Land Use Map.
Agricultural land use pattern
Terai cultivation is the sole type of agriculture in this VDC covering a total of
2944.68.02 ha of area. 91.45% (2629.94 ha) of agricultural land is under wetland
cultivation whereas 9.17% (270.12 ha) of land is under mixed-land cultivation.
Analysis of cropping pattern shows that Rice-Wheat is the dominant one followed by
Rice-Fallow and Rice- Pulses (Table 2)
Table2: Area Coverage of Different Cropping Patterns.
Cropping Pattern
Area, ha
Rice-Fallow
247.76
Rice-Wheat-Maize
33.49
Rice-Wheat
2313.02
Rice-Wheat/Pulses/vegetables
161.06
Rice-Oilseed
9.50
Rice-Pulses
179.85
348
Percentage, %
8.42
1.14
78.55
5.46
0.32
6.11
24-25 March 2015
Residential area
Residential area (292.38 ha) of this VDC belong to sparsely and moderately populated
class.
Commercial area
This VDC has very small proportion of commercial area, i.e. 16.13 ha only. All of this
area is Market under the Business area.
Forest area
Majority of the area is covered by forest and bushes. There are total 16 community
forests managed by forest user groups and 2 religious forests in this VDC.
Public services area
Hydrographic features cover most of the public service area. Other classes in public
services are: Transportation, Educational and security services.
Soil maps
The soil profile was dug around 80 cm deep or more until two or more natural soil
horizons are clearly detected. However, in the places of fresh channel bank-cuts, where
information of soil horizons at greater depth was available, was also considered as
sample location. The location of the sampling pits is given in following figure.
Figure 3:Location of soil sampling pits.
Soil pH
Majority of soils collected fromthe first horizon ofthe soil profiles in the VDC have pH
value in the range of 6.2 to 7.8, which indicates acidic to alkaline. In general, soils with
near neutral reaction (pH 6.0-7.0) are the most fertile (LRMP 1986)
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Figure 4: Soil pH at Chaumala VDC, Kailali.
Soil organic matter
In the VDC, the organic content is very low to high. The amount of organic matter in a
soil is highly dependent on a range of ecological factors (climate, soil type, vegetative
growth, topography) in which it occurs as well as land use and management and tillage
of the soil.
Figure 5: Soil organic matter, %.
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24-25 March 2015
Nitrogen, Phosphorous, and Potassium:
These soil nutrients play an important role in limited crop production in Nepal. The
level of soil nutrients in the order of rank is summarized in Table 3.
Table3: Organic Matter, Nitrogen, Phosphorus and Potassium rating.
S.N. Nutrients
Soil
Total
Available
rating
Organic
nitrogen,%
phosphorus,
Matter,%
kg ha-1
1
Very low
<1.0
< 0.05
<10
2
Low
1.0-2.5
0.05-0.1
10-30
3
Moderate
2.5-5.0
0.1-0.2
30-55
4
High
5.0-10.0
0.2-0.4
55-110
5
Very high
>10.0
>0.4
> 110
Available
potassium,
kg ha-1
<55
55-110
110-280
280-500
> 500
Source: Soil Science Division, Khumaltar, Lalitpur
It is evident that the soil nitrogen in the VDC varies from 0.02 to 0.41%, indicating that
it is at the concentration of very low to very high.
Figure 6: Soil Nitrogen , %.
Likewise, the phosphorous content in the soil ranges from around 36 to 751 kgha-1
(Figure 7). Dominant part of the VDC has medium to high phosphorous content.
Similarly, the potassium content in the soil of the VDC varies from 81 to 349 kg/ha
(Figure 7). Majority of the sample location shows the concentration between low to
very low values.
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Land Capability of the Study Area
Land Capability Classification Hierarchy
Capability class
Capability classes are groups of capability subclasses or capability units that have the
same relative degree of hazard or limitation. The risks of soil damage or limitation in
use become progressively greater fromclass I to class VIII. The capability classes are
useful as a means of introducing the map user to the more detailed information on the
soil map. The classes show the location, amount, and general suitability of the soils for
agricultural use. Only information concerning general agricultural limitations in soil
use are obtained at the capability class level.Capability classes are the highest order in
the hierarchical structure. Capability classes are directly derived from Land System
Map units. They represent the physical characteristics and reflect the management
options. Following land capability classes have been defined for land capability
mapping:
Class I lands nearly level (slopes 1 degree) and soils are deep. There are few
limitations for arable agriculture or forestry.
Class II lands are gently sloping (1-5 degree slopes) and soils are deep and well
drained. Terracing or contouring is necessary to control erosion when used for arable
agriculture and maintenance of ground cover is required for forestry related use
Class III lands are moderately to strongly sloping (slope 5-30 degree) and soils are 50100 cm deep and well drained. There are few limitations to traditional forest use
provided adequate ground cover is maintained. Terracing is mandatory to control
erosion when used for arable agriculture.
Class IV lands are too steep to be cultivated or (>30 degree slope) or lie above the
altitude limit for arable agriculture. Soils are more than 20 cm deep and well to
imperfectly drain. These lands are suitable for fuel wood, fodder and timber production
provided a good permanent vegetative cover is maintained to minimize erosion.
Class V lands have soils more than 20 cm deep and slopes are less than 30 degree or
lands which are alpine (above tree limit) or are river terraces that are frequently
flooded.
Class VI land includes areas with slopes 40-50 degree or gentle slopes with soils less
than 20 cm deep. These lands are considered fragile because of extreme erosion hazard
and or poor regeneration potential.
Class VII consists of rocks and ice.
Similarly irrigation suitability classification is used following LRMP (1986). Land
Classification is used in part to identify the arable lands in Capability class I and II
according to their suitability for irrigation agriculture.
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Figure7: Soil Phosphorus,kgha-1.
Figure 8: Soil potassium, kgha-1.
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Sub-Class
Subclasses are groups of capability units which have the same major conservation
problem, such as:
E = Erosion and runoff
w = Excess water
s = Root-zone limitations
c = Climatic limitations
The class and subclass together provide the map user information about both the
degree of limitation and kind of problem involved for broad program planning,
conservation need studies, and similar purposes. Land capability subclasses are defined
on the basis of distinct temperature and moisture regime according to LRMP as
described in the previous section. Hence two categories of subclasses are defined
(Table 4 and Table 5).
Table 4: Temperature sub-classes.
S.N.
Sub-classes
1
2
3
4
5
Mapping Symbol
Sub-tropical
Warm temperature
Cool temperate
Alpine
Arctic
A
B
C
D
E
Table 5: Moisture regime sub-classes.
S.N.
Sub-classes
1
Semi-arid
2
Sub-humid
3
Humid
4
Per-humid
Mapping Symbol
a
u
h
p
Similarly, irrigation suitability subclasses are used to indicate deficiencies in soils,
topography and drainage. Table 41 briefly describes the irrigation suitability and map
symbols.
Table 6: Irrigation suitability classes and map symbols.
Land characteristics
Irrigation suitability
Diversified crops-arable
Highly irrigable
Moderately irrigable
Wetland rice-arable
Highly suitable for rice cultivation
Moderately to fairly suitable for
cultivation
Non-arable
Subject to seasonal flooding and
inundation
354
Map Symbol
1
2
1R
2R
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Shallow or impervious soil with 6
coarse texture and low water
holding capacity
There is high level of contrast in capability classes of this VDC. Land capability class
IVAu/ 1 (17.39%) and IAu/2 covers maximum area (16.93%) of the VDC. Next
significant capability class is of IAu/1 (16.39%).
IAu/1
16.39%
VIAu River
Channel
1.20%
IVAu
7.59%
17.39%
IAu/1R
6.97%
IIIAu
1.07%
IAu/2
16.93%
IIAu/5
10.27%
IIAu/2
15.16%
IIAu/1R IIAu/1 IAu/5 IAu/2R
0.07% 1.69% 3.41% 1.85%
Figure 9:Area under various land capability classes.
Figure 10:Land capability map of the study area.
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Conclusion
Present land use map reveals that a large part of the study area is under cultivated area
and forest and shrubs/bush. Human pressure on the forest is high particularly in
proximity to settlement and highway as evidenced by the shrubs and grazing land
developed at the fringe of the forest in piedmont area. Residential areas although
located at the upper terrace and on the elevated areas made by human for residential
purpose, their encroachment on the flood prone areas or on highly arable areas cannot
be encouraged in the future.Analysis of soils characteristics shows that most of land in
the VDC is suitable for production cereals and vegetables crops throughout the year
under irrigation conditions and appropriate land/soil management practice. Results of
soils tests clearly show that most of the cultivated areas are poor in organic matter
contents and available nitrogen, phosphorus, and potash is also below desired level.
Due to continuous tillage and absence of organic matter without compensating nutrient
supply from natural and artificial sources has led to low level of soil nutrient content.
Majority soils sample have pH value within the acidic range.The land capability map
of the studied VDC has been prepared considering various factors and it is observed
that this VDC has high contrast in land capability classes as compared to other nearby
VDCs. Land capability class IAu/ 1covers maximum area of the VDC.Prepared land
use map should be made in access to the concerned stakeholders that can be used for
various purpose, especially in resource management. It is necessary to update the land
use map within certain interval of time so that it will be useful and relevant for
planning various sectors like agriculture, forestry, urban and physical infrastructure
development, watershed management and so on.
There is need to raise public awareness towards sustainable utilization of land
resources. It can be achieved through displaying the land use maps of various time
interval and explaining the changes (positive and/or negative) so that the local people
visualize the scenario, accept the causes and effects thereby easing for implementation
of the plans. It is necessary to review the land capability mapping approach and
currently prepared capability maps in order to develop the viable maps.
Acknowledgement
Our sincere thanks go to all the government officials of National Land Use
Project/Ministry of Land Reform and Management providing opportunity for working
in the project.
References
Anderson JR. 1971. Land use classification schemes used in selected recent geographic
applications of remote sensing: Photogramm. Eng. 37(40):379-387
Burley TM.1961. Land use or land utilization? Professional Geographer. 14(5): 18-20
Clawson M and CL Stewart. 1965. Land use information. A critical survey of U.S.
statistics including possibilities for greater uniformity: Baltimore Md, The
Johns Hopkins Press for Resources for the Future Inc. 402 p.
356
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FAO.1993. Guidelines for LandUse Planning. Food and Agriculture Organization of
the United Nations (FAO). Italy.
LRMP. 1986. Land Utilization Report. Land Resources Mapping Project. Government
of Nepal/Government of Canda – Kenting Earth Sciences Limited.
Kathmandu.
Wilkie DS and JT Finn. 1996. Remote Sensing Imagery for Natural Resources
Monitoring. Columbia University Press, New York. 295 p.
357
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GSS-5
Soil Nutrition Distribution in Eastern Tarai of Nepal:A Case Study of
Jhorahat VDC of Morang District
Rajendra P Tandan, Raju Rai, Laxmi Basnet and Krishna B Karki
Rajdevi Engineering Consultancy Pvt. Ltd., New Baneshwor
Abstract
Food deficit, declining productivity of land and environmental degradation are directly
related with the soil nutrition and its properties. In this context, the role of soil properties
is considered as basis for sustainable land resource management and planning. The
National Land Use Project (NLUP) is preparing land resource map at VDC level and The
UN HABITAT is lunched Participatory Land Use Project (PLUP) as pilot resource
mapping to prepare quality of land resource mapping with cost effective and effective
implementation of resource mapping result. Jhorahat VDC lies in the eastern part of
Morang District and occupies 982 ha area. They are classified based on their
morphological, physical and biological properties. In this VDC single soil order
Inceptisols is found with three sub orders, four great groups and five subgroups. The
majority of area is covered by AridicUstochrepts which is 57 percent followed by
TypicDystrustepts with 22%. Soil pH ranged from 5.3to 6.9, total N is found in the range
of 0.05 to 0.12%. Similarly available P2O5 ranged from 5 to 94 kg ha-1andK2O 18 to 154
kg ha-1.Amount of soil organic matter (OM) is low range from 0.7 to 2.33% and loam is
soil texture.
Keywords: GIS, Jhorahat VDC, land use, soil classification, soil fertility.
Introduction
Study of soils and classifying them into Soil Taxonomy and mapping is the process of
grouping soil, based on their physical, chemical, biological and morphological
properties.Geo-encoding of such information is employed in soil classification which
draws heavily from geomorphology, theories of soil formation, physical geography and
analysis of vegetation and land use patterns. Primary data for the soil survey are
acquired from the field survey and sampling design using remote sensing techniques
(Chang et al. 2001, Johnson et al. 2005). Now-a-days, remote sensing using high
spatial resolution in soil survey and digital techniques is gaining popularity. Previously
soil surveyor used hard copy of aerial photographs, topo-sheets, and mapping keys into
the field with them. Today, a growing number of soil scientists use computer aided
program and GPS in field and map the soils. The computers are loaded with digital
satellite image, topography, soil geo-databases, mapping keys, and more
(Dijkshoornand Huting 2009, Zhu et al. 2001). Practically it helps in providing
information needed for developing optimum land use plans. It brings new areas under
various uses like irrigation water supply, drainagedevelopment, evaluating soils
suitability for irrigation for agricultural crops, demarcating the problematic soils and
waste lands. Areas subject to erosion, soil fertility maintenance and in suggesting soil
and water conservation measures to overcome these problems can be easily delineated
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Figure 1: Study Area of Jhorahat VDC Morang District.
(Thompson et al. 2001). And hence a soil survey of Jhorhat VDC of Morang District
was undertaken and soils fertility evaluated.
JhorahatVillage Development Committee (VDC) is situated in the Morang District of
eastern Tarai, Nepal between 2936804 to 2931744 north latitude and 531502 to 534880
east longitudes. It has extended northsouth length5.08 km and eastwest width 3.22 km
(Figure 1). This VDC is located in eastern part (near about 11 km) from the district
headquarter of Biratnagar, Morang district. The area of thisVDC is 928.40 hectares.
This VDC is iN habited by different castes and ethnic groups. Economic condition of
the people of this VDC largely depends on agriculture, government service, NGOs and
private industries.
Before going to the actual field work a preliminary reconnaissance survey was carried
out to get insight of ground situation of project area regarding the association of
landform and soil. In addition the LRMP (Land Resource Mapping Project) data of the
areas and other relevant publications from DoA and SSD of NARC were studied.
Polygons were demarcated by overlaying land system, land use and geology maps of
that areas and compared with recent high resolution Geo-Eye Satellite image. Field
work was carried out to study the physiography, landform and their associated soils
based on the soil profiles on each polygon. In all 25 soil profiles were opened and
surface soil sample were collected from each soil profiles. Soil of each horizon in the
profile was described following FAO soil description guidelines. Soil sample from
surface horizon thus collected is analyzed for primary soil nutrients and analyzed for
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24-25 March 2015
fertility status. Morphological and on site information of the soil profiles opened on the
field was recorded in profile description sheet. Soil pH in the field was checked with
pH indicator; texture was checked with hand feeling and consistency was also noted.
Other profile morphology such, structure, porosity, mottles, cutans, roots, crotovinas
were observed through visual symptoms using expert knowledge. Based on
morphological and chemical analysis soils are classified according to Soil Taxonomy
(USDA 2010).
Laboratory Soil Analysis
The soil samples collected from the field were sent to Soil Testing Laboratory to
examine the chemical properties of soil including soil texture following procedures as
presented in Table 1. Soil properties provided by the soil surveyors were verified with
the laboratory analysis data and the classified to Great Group levels.
Table 1:Methods adopted in soil sample tests in laboratory.
Soil Sample Tests Analysis Method
Hydrometer and Texture Classification using USDA soil textural
Texture
sizes groups
1:2.5 water suspension(soil water paste) using combined
pH
electrodes
Organic Matter
Walkley and Black methods using H2SO4 wet digestion and
Content
K2Cr2O7 as oxidizing agents
Available
Olson sodium bicarbonate extraction and blue color developed
Phosphorous(P2O
with ascorbic acids and detected in spectrophotometer in 560 nm
5)
1 N neutral ammonium acetate 5 min shaking and filtered
Available
through Watman No 42 filter paper and detected through flame
Potassium(K2O)
ignition
Total
Microjeldahl digestion and distillation
Nitrogen(N)
Based on their physical, chemical and morphological including biological properties
they were grouped into different categories and classified as per Soil Taxonomy. The
fivesubgroups thus classified were AericEpiaquepts, Lithic Haplustepts,
AridicHaplustepts, TypicDystrustepts and AridicUstochrepts. Dominant Subgroup
being AridicUstochreptsoccupying57% of the study area followed by
TypicDystrustepts with 22.7 %of the land of this VDC (Table 2). The spatial
distribution of these classified soils and the map is presented in figure 2. Other
Subgroups coveredcomparatively smaller area. Water body covered 3% (28.9 ha) of
the total land of the VDC.
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Table 2:Distribution of Soils in Jhorhat VDC.
SN
Order
Inceptisols
Sub Order
Aquepts
Subgroup
AericEpiaquepts
Area (ha)
45.03
Percent
4.58
Haplustepts
Lithic Haplustepts
97.70
9.95
AridicHaplustepts
27.05
2.75
Dystrustepts
TypicDystrustepts
223.66
22.77
Ustochrepts
AridicUstochrepts
560.04
57.01
28.92
2.94
982.40
100
Ustepts
1
Ochrepts
2
Great Group
Epiaquepts
Water body
Total
Soils from this study area are of light groups with only 8.3 % clay particles which is
rather low from the points of nutrients and water holding capacity(Burke et al. 1989).
Percentage of silt is high and limited sand particles. These soils are good for rice
cultivations (Kang et al. 1985, Stewart and Letey 1985). To improve water holding
capacity as well as retaining nutrients from leaching higher amount of organic manure
is needed to apply. It is known that manure application improves soil physical,
chemical and biological properties of soil and increase crop production (Kang et al.
1985, Mylavarapua and Zinati 2009).
Nitrogen
Nitrogen (N) is one of the most important nutrients for crop growth.Spatial distribution
of Nitrogen is presented in map and table 3 (Figure 3), about 75 % (734.9 ha) of area
has low distribution of N. Similarly 22.2 % (218.5 ha) land has medium Ndistribution
in this Jhorahat VDC. Rest of soil falls under lownitrogen level.
Table 3:Distribution of Nitrogen and Phosphorous.
SN
Rating
P2O5 (Area ha)
P2O5, %
1
High
283.26
28.83
N (Area ha)
0.0
2
Medium
274.01
27.89
218.53
22.24
3
Low
396.21
40.33
734.95
74.81
4
Water Body
Total
28.92
982.40
2.94
100.00
28.92
982.40
N, %
0.0
2.94
100.00
Phosphorous
Distribution of Phosphorous (P2O5) is displayed in the map(Figure 5), about 40.3 %
(396.7 ha) percent area has low distribution of P2O5, 27.8% (274 ha) percent land
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medium and 28.8% (283.2 ha) percent land has high P2O5 distribution in this Jhorahat
VDC. Since the soils in this VDC is of recent alluvial origin, soil P2O5 in most of the
Nepalese soils contained high level(Karki 2003, Karki 2006).
Potassium and Organic Matter
Potassium (K) is an essential nutrient that affects most of the biochemical and
physiological processes including plant growth and metabolism. It also contributes to
the survival of plants exposed to various biotic and abiotic stresses.The distribution of
Potassium (K2O) and Organic matter(OM) is shown in map(Figure 5 and 6), about
90.4% (888.7 ha) of area has low distribution of K2O and 6.6 % (64.7 ha) has medium
K2O distribution in this VDC. For the soil potassium some authors have indicated that
potassium reserve if Nepalese cultivated soils is decreasing (Adhikary and Karki 2006,
Karki 2003). Organic matter serves as a reservoir of nutrients and water in the soil, aids
in reducing soil compaction and surface crusting. It also increases water infiltration
into the soil. The distribution of Organic Matter (OM) is low all over the VDC ranging
from 0.74 % to 2.33 %. Organic matter in the Terai Region is low because of low level
of organic manure application by the farmers. In general farmers in the Terai apply less
than a ton of FYM ha-1(Joshi and Karki 1993) which decreases over time because of
oxidation and reduction due to higher temperature in this region(Hart and Brookes
1996).
Soil pH
The distribution of salt and Alkaline,about 65% (643 ha) area has medium acidic land
and 21 percent land has low acidic and 11 percent land has neutral pH distribution in
this Jhorahat VDC. Soil pH fluctuates due to cultivation. Generally in upland
cultivation soil pH decreases (Snyder 2002). This decrease may be due to the loss of
Ca and Mg from leaching and plant uptake. But in rice soils soil pH increases because
of formation of OH- (Morales et al. 2010). When soils are flooded, acidic soils tend to
change to neutrality. Similarly alkaline soils come to acidity and hence buffer the soils.
Therefore care should be taken to apply lime to the flooded soils (Karki 1987).
Soil Texture
The distribution of soil textureis shown in the table 4, the large area 42.8% land of this
VDC has Silty Loam (SIL) which is followed by sandy Loam 31.9% and 22.6% with
420.8, 313.9 and 218.7 ha respectively. Most of the soils contain has more than 60 %
sand. Likewise the clay content in soils is around 10% high. More than 55.7% soils
have higherSilt content. Since this area is under the command of Morang –Sunsary
Irrigation Project and the irrigation is highly loaded with silt which ultimately land on
cultivated field.
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Figure 2: Soil distribution of Jhorahat VDC.
Table 4:Distribution of Soil Texture.
SN
Soil Texture
1
Loam (L)
Area Ha
218.72
Percent
22.26
2
Silt Loam (SIL)
420.80
42.83
3
Sandy Loam (SL)
313.96
31.96
4
Water Body
28.92
2.94
Total
982.40
100.00
Soil Fertility
The evaluation of soil fertility of the Jhorahat VDC is calculate on the basis of above
mention soil nutrients followed up of Multi-criteria Evaluation and weighted
Composite Score analysis.In this study, about 55 percent land has medium fertility.
Likewise 29% area has low fertility capacity and 13 percent land belongs to non-arable
land(Table 5).
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Figure 3:Distribution of N2.
Figure 5:Distribution of K2O.
Figure 4:Distribution of P2O5.
Figure 6:Distribution ofOrganic Matter.
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Table 5:Distribution of Soil Fertility of Jhorahat VDC.
SN
Fertility Rating
Area Ha
1
Medium
540.52
Percent
55.02
2
Low
289.99
29.52
3
High
18.64
1.90
4
Non Arable
133.25
13.56
982.40
100.00
Total
Present Land Use
The general land use pattern of Jhorahat VDC at the broad hierarchical classification
has been provided in figure 7.Agriculture land has been found as dominated land use
categories and its coverage area is 894.15 hectares with 84.447% of the total spatial
extent. Similarly, residential area is observed as second important land use type
representing 58.64 hectares (5.97 %) which is followed by public use 5.89 percent
areathe remaining land use types are commercialand Industrial areaconsisting of1.7 %
geographical area. The existing agricultural land in this VDC was found in the category
of Tarai cultivation which is situated in Tarai plain as physiographic unit. Representing
cropping pattern rice-wheat and fallow with medium cropping intensity. Such cropping
pattern was also replaced rice by pulse seed. Intense cultivation was observed only in
the areas of vegetable farming.
Industrial
1%
Public Use
6%
Residential Area
6%
Commercial
1%
Agriculture
86%
Figure7: Distribution of Present Land Usein Jhorahat VDC.
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Conclusion
In this study one soil order Inceptisols is found with three sub order, four Great Group
and five Sub Great Group AericEpiaquepts, Lithic Haplustepts, AridicHaplustepts,
TypicDystrustepts and AridicUstochrepts. The soil AridicUstochreptsoccupiedabout
57% land which is followed by TypicDystrustepts with 22.7 Percent and the water
body is in 3% (28.9 ha) of the total land of the VDC.
About 75 percent land has low Nitrogen (N) distribution.The distribution of
Phosphorous (P2O5) is high, medium and low 28.8 % 27.8% and 40.3% respectively.
But the distribution of Potassium (K2O) is found low which is about 90.4 of the total
land. Almost whole VDC has Organic Matter deficiency range from 0.74percent to
2.33 percent. Silt Sand, Sandy Loam and Loam soil is found in this study area as soil
texture.The distribution Information on soil classification of Jhorahat VDC of Morang
District has been completed. The morphological, some physical and chemical soil
properties are presented but sufficient soil properties for classification were not
available especially some subsoil samples analysis for pH and texture including
Cations Exchange Capacity (CEC). Therefore, the taxonomical classification is
tentative. Since soil map at the district level is not yet available, availability of these
soils are inter-relatively existed. And hence their associations have been mapped. For
the use of general readers the soil association makes little difference but the use of
these soils with regards to agricultural and other uses are more important which this
report provides only an idea for planning.
Acknowledgement
The authors would like acknowledge the support received from Jhorahat VDC
(Morang) without which this articles would not have written. Similarly, supports and
suggestions provided by Dr. S.P. Vista (Soil Scientist, NARC), Dr. Bhagwat Rimal
(Geographer), Soil sample collectors, GIS Experts ofRajdevi Engineering Consultant is
highly appreciated.
References
Adhikary BH and KB Karki. 2006 Effect of Potassium on Potato Tuber Production in
Acid Soils of Malepatan, Pokhara. Nepal Agriculture Research J.7: 41-48.
Burke IC, CM Yonker, WJ Parton, CV Cole, DS Schimel and K Flach. 1989.
Texture, Climate, and Cultivation Effects on Soil Organic Matter Content in
U.S. Grassland Soils. Soil Sci. Soc. Amer. J.53: 800-805.
Chang CW, DA Laird, MJ Mausbach and CR Hurburgh. 2001. Near-Infrared
Reflectance Spectroscopy: Principal Components Regression Analyses of Soil
Properties Journal Paper no. J-18766 of the Iowa Agric. and Home Econ. Exp.
Stn., Ames. Soil Sci. Soc. Amer.J.65: 480-490.
Dijkshoorn JA and JRM Huting. 2009. Soil and terrain database for Nepal.ISRIC
Report Wageningen. 2009/01. 30 p.
366
24-25 March 2015
Hart MR andPC Brookes. 1996. Soil microbial biomass and mineralisation of soil
organic matter after 19 years of cumulative field applications of pesticides. Soil
Biol. Biochem.28: 1641-1649.
Johnson CC, N Breward, EL Ander and L Ault. 2005. G-BASE: baseline geochemical
mapping of Great Britain and Northern Ireland. Geochemistry: Exploration,
Environment, Analysis. 5: 347-357.
Joshi D and KB Karki. 1993. Soil fertility and fertilizer use in Nepal. Soil fertility and
fertilizer use in Asia. HL S Tondon (ed.). New Delhi.: Development
Consulting Services.
Kang BT, H Grimme and TL Lawson. 1985. Alleu cropping sequentially cropped
maize and cowpea with Leucaena on a sandy soil in Southern Nigeria. Plant
and Soil.85: 267-277.
Karki KB. 1987. Use of Lime and Organic Manure in Increasing Productivity of Some
Acid Soils of Nepal. First Review/Working Group Meeting on Bio-fertiliser
Technology. Soil Science Division, Khumaltar. Pp. 87-97.
Karki KB. 2003. Status of potassium in intensively cultivated soils from Kathmandu
Valley. Nepal J. Sc. and Tech.5: 83-89.
Karki KB. 2006. Impact of cropping intensification on nutritional balance in Nepalese
soils.In International Seminar on Environmental and Social Impacts of
Agricultural Intensification in Himalayan Watersheds. RM Bajracharya and
BK Shitaula (eds.). Kathmandu, Kathmandu University, Nepal. Pp. 27-33.
Morales LA, Paz-Ferreiro, J Vieira, SR and VÃ¡zquez EV. 2010. Spatial and temporal
variability of Eh and pH over a rice field as related to lime addition. Bragantia.
69: 67-76.
Mylavarapua RS and GM Zinati. 2009. Improvement of soil properties using compost
for optimum parsley production in sandy soils. Scientia Horticulturae.120:
426-430.
Snyder CS. 2002. Effects of Soil Flooding and Drying on Phosphorus Reactions. A
regional newsletter published by the Potash & Phosphate Institute (PPI) and
the Potash & Phosphate Institute of Canada (PPIC). Pp. 3.
Thompson, JA, JC Bell and CA Butler. 2001. Digital elevation model resolution:
effects on terrain attribute calculation and quantitative soil-landscape
modeling. Geoderma.100: 67-89.
USDA.2010. Keys to Soil taxonomy (ed. USDA/NCRS).Washington: USDA. USA.Pp.
34.
Zhu AX, B Hudson, J Burt, K Lubich and D Simonson. 2001. Soil Mapping Using
GIS, Expert Knowledge, and Fuzzy Logic. Soil Sci. Soc. Am. J.65: 1463-1472.
367
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GSS-6
Soil Organic Carbon Stocks Estimation and Mapping by Using Geographic
Information Systems in Rautahat District
Kamal Sah,Shushil Lamichhaneand Binod Silwal
Soil Science Division, Khumaltar, NARC
Abstract
Agriculture is the backbone of Nepal and more than 60% people are involved in
agriculture for their livelihood. Soil organic carbon (SOC) is depleting day by day from
the agricultural lands due to human activities and soil erosion. SOC is the prime
component of soil which governs the soil fertility, soil health, crop productivity and
climate change. Conventional methods of determining SOC by farmers interviews and eye
estimation is time consuming and less authentic. The application of geographic
information systems (GIS) and field survey for SOC estimation and mapping is more
soil samples
collected from Rautahat
accurate and less time consuming.
district from 0-20 cm and 20-40 cm soil depth for determining the soil organic carbon and
bulk density in 2013 year. The aim of this study was to estimate and map SOC stocks
within the different farming systems and other land use types and recommend suitable
options to raise SOC stocks in that area. The majority of the soil samples were under class
ha-1.
15-30 kg
Keywords: Crop productivity, field survey, GIS, mapping
organic carbon, soil
fertility.
Introduction
Agriculture is the backbone of the Nepal and more than 60% people are involved in
agriculture for their livelihood. Past 10 to 20 years have brought disturbing evidence
that human activities contributes to high atmospheric carbon dioxide (CO2)
concentrations causing significant changes in future global climatic conditions (IPCC
2007, Wallington et al. 2004). These anticipated changes in climatic conditions have
potential social, economic and environmental consequences worldwide (Robert 2001).
However, through the establishment of the Kyoto Protocol, global efforts are being
directed towards biological systems (forests and soils biomass) for carbon
sequestration (Dersch and Bohm 2001, Freibauer et al. 2004). Furthermore, because
soils hold more carbon than the atmosphere and vegetation combined,and can hold it
longer, the focus has increasingly shifted to soil carbon as an opportunity to both
mitigate and adapt to climate change, as well as the provision of ecosystem functions.
Carbonsequestrationsrefer to the removal of carbon dioxide from the atmosphere into a
long-lived stable form that does not affect atmospheric chemistry (Miller et al. 2004).
Agriculture is associated with the provision of food but at a cost to many ecosystem
services including carbon sequestration (Tilman et al. 2002). In addition, degraded
368
24-25 March 2015
ecosystem services also affect agricultural productivity (Albrecht and Kandji 2003,
Dale and Polasky 2007). Agricultural activities such as forest harvesting, livestock
related nitrogen and methane emissions, paddy rice related methane emissions, and
poor land management practices have become a major contributor to CO2 emissions in
the atmosphere (Lal and Bruce 1999, Miller et al. 2004). Consequently, agriculture
contributes immensely to carbon induced climatic changes as well as inducing changes
in soil properties (Yao et al. 2010).
Changes in agricultural land use management can increase or decrease soil organic
carbon (West and Post 2002). Promotion of tree based systems, agroforestry, cover
crops, residue retention, manure application, irrigation, conservation, zero/minimum
tillageand other agrarian practices are options that may greatly reduce carbon loss and
eN hance soil organic carbon levels (Batjes and Dijkshoorn 1999, Marland et al. 2004).
EN hanced SOC has favourable effects on physical, chemical and biological activities
of the soil for better crop yields. SOC provides options for improving soil fertility and
ensuring food security (Marks et al. 2009). The land use/land cover change pattern
introduces spatial variability in the SOC content and an understanding of such
variability is important for developing management practices for a particular land use
(Wang et al. 2010).
In Rautahat district, prevailing cropping pattern was rice-wheat, rice-lentil, rice-maize,
rice-sugarcane, rice-mustardandrice-vegetables. Soil organic carbon (SOC) content in
these cropping patterns was low due to low application of organic matter and intensive
cultivation. Therefore, this study aims to determine the SOC content and map the
spatial variability of SOC in the soil of the district.
The study was conducted in Rautahat district and in different copping pattern land use
in 2013 year.Topo map was used for the location of soil sample point in the district.
Therewere 40 soil sample points taken for the soil sample collection from two depths
0-20 cm and 20-40 cm(Figure 1). Each soil sample point was marked with GPS(Global
Positioning System) to record the latitude and longitude. The sample points were
located randomly at 3 by 3 Kilo meter grid. Two soil samples were taken from each
depth, one sample for routine analysis and one for soil bulk density analysis. After
taking the soil samples from the field, the samples were analyzed in the laboratory of
Soil Science Division, Khumaltar. The soil organic carbon was analyzed in laboratory
by using wet combustion method (Walkely-Black Method).Soil bulk density was
determined on an oven dry (105o C) for 48 hours and calculated by using the formula
BD=(oven dry weight of soil/Volume of core) g/cm3.The soil texture was analyzed by
hydrometer method. Soil pH was measured by a pH meter by using 1:2.5 soil water
ratio method. The soil organic carbon stock was calculated by using the
formulaSOC=Organic carbon% X Bulk Density X Depth X10 (t ha-1). In ArcGIS V10,
the Krigging approach was used to develop the spatial distribution map of the soil
organic carbon content (Wang et al. 2010). Each sampling point was assigned the
actual SOC value during the interpolation process.
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24-25 March 2015
Figure 1:Distribution of soil sample points.
Soil Organic Carbon
The distribution of soil organic carbon content for the top and sub-surfacelayers is
shown in the Figure 2 and Table 1. The majority of the soil organic carbon content area
comes under the SOC class 200- 300 t ha-1. In the top layer, the area covered is
16075.04 ha and in sub-surfacelayer 20527.04 ha. The lowest area covered in SOC
class 60 – 100 t ha-1 in both depth,208.4 ha in top layer and 0 ha in bottom layer. The
second highest area covered in SOC class 300 – 400 t ha-1 in both depth, top layer is
10221.84 ha and bottom layer is 13522.36 ha.
Table 1:SOC content distribution in top & bottom layer.
SOC Classes (t ha-1)
60 - 100
100 - 200
200 - 300
300 - 400
400 -500
500 - 600
600 - 700
Total
Area ha (0-20 cm depth)
208.4
9359.93
16075.04
10221.84
6934.92
7102.05
3496.6
53398.82
370
Area ha (20-40 cm depth)
0
8139.28
20527.04
13522.36
10770.12
440.01
8139.28
53398.82
24-25 March 2015
Figure 2:
Soil Organic Carbon (SOC) distribution at different depths of Rautahat
district.
The total mean value of soil organic carbon content of top layer is 262.52 t ha-1 and
211.54 t ha-1 of sub-surface layer, so it indicate that the top layer has higher SOC
content than the sub-surface layer (Figure.3.and Table 2, 3).
600.000
500.000
400.000
300.000
200.000
SOC(t/ha) (0_20cm)
100.000
SOC(t/ha) (20-40 cm)
0.000
1 3 5 7 9 11 13 15 17 19 21 23 25 27
Figure 3:SOC content in top and sub-surface layer.
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Relation between soil texture with SOC and BD
Table 2:Relation of soil texture with SOC and BD (0-20 cm).
Texture
Mean SOC(t ha-1)
No. of sample
Mean BD (gcc)
Clay loam
3
258.79
1.46
Loam
4
225.39
1.48
Silty clay loam
8
245.57
1.36
25
320.34
1.45
40
262.52
1.43
Silt loam
Total
Table 3. Relation of soil texture with SOC & BD (20-40 cm)
Texture
Mean SOC(t ha-1)
No. of Sample
Clay loam
Mean BD (g cc)
10
181.5
1.52
Loam
2
212.72
1.42
Loamy sand
1
157.14
1.44
Silty Clay loam
11
145.6
1.56
Silt Loam
16
360.74
1.55
40
211.54
1.49
Total
From the above table, it shows that the silt loam texture has the highest SOC content
than other soil texture in both the soil depth. The total mean bulk density of top layer is
1.43 g cc-1and 1.49 g cc-1 for bottom layer, so it indicates that the soil bulk density of
top layer is lower than the bottom layer.
Conclusions
For increasing the SOC in the soil, following appropriate crop management practices
should be adopted by the farmers.Incorporate sufficient amount of FYM in the
agricultural fields, incorporate crop residues in the fields, follow agro-forestry practices
where it is possible, use bio-char to increase the SOC in soil, follow minimum tillage
in the fields, follow soil mulching practices for conserving nutrients and moisture loss.
The level of SOC content in top layer is higher than bottom layer and the soil bulk
density of top layer is lower than the bottom layer.Soil texture Silty Loam has the
higher SOC. With the application of GIS the SOC stocks can be estimated and mapped.
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671-677.
Wallington TJ, S Jayaraman, JN Ole and JH Ellie. 2004. Greenhouse Gases and
Global Warming.Encyclopedia of Life Support Systems (EOLSS).
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Organic Carbon Under Maize monoculture in the Song-Nen Plain,
Northeast China. Pedosphere. 20(1): 80-89.
West TO and WM Post. 2002. Soil Organic Carbon Sequestration Rates by Tillage and
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GSS-7
Geographical Information System and Remote Sensing (GIS and RS)
Supported Soil Fertility Mapping
Ragindra M Rajbhandari and K
B Karki
NEST Pvt. Ltd., Shankhamul, Kathmandu, Nepal
Abstract
Deteriorating soil fertility and low crop productivity are some of the reasons behind food
insecurity in Nepal. The only possible way out to meet this challenge is to increase food
production. Soil fertility, fertilizer application and soil moisture play major roles in
improving crop production.Hence, study of soil fertility status is in itself a major domain
in this regards.
The application of a geographical information system (GIS) and Remote sensing (RS)
technology offers an efficient and cost effective tool inanalyzing soil fertility status of an
area. The flexibility nature of these tools offers scalable spatial representationof status of
soil fertility from parcel level to regional –national to global level. This paper presents
methods and analysis performed in GIS and RS supported soil fertility mapping project
conducted by Irrigation and water Resources Management Project (IWRMP) in the four
food vulnerable districts of Eastern and Mid-Western Development Regions of Nepal
(Taplejung and Tehrathum in the east and Rolpa and Salyan in mid-west). Various maps
and report published by Land Resources Mapping Project (LRMP), such as Land system
and Land use maps; Topographic maps published by Department of Survey are compared
with the recent Satellite Imaginary. These maps were analyzed and overlaid developing
polygons of cultivable area which were the basis for soil sampling. The stratified random
sampling using simple rejection algorithm based on a bivariate uniform random
distribution method is used to locate the sampling pit per dominant soil type per
VDC.Field Enumerators were trained in identifying sampling pit in the field. In all 1400
soil samples (350 sample each districts ) were collected and analyzed for organic matter
(OM), soil pH, texture (particle sizes), total nitrogen (N), available phosphorus (P2O5) and
potash (K2O), Plant available zinc (Zn) and boron (B) following standard analytical
procedure. The existing cultivation areas in these districts were extracted using object
based recent satellite image classification using its spectral and contextual property. The
spatial location of soil sample pits were then overlaid over these cultivation area and its
to produce soil fertility status/map of individual
individual lab observations were
district in Geo-statisticmodeling environment. The lab observation of all soil sampling pit
per district were also presented using descriptive statistic of R Software. The fertilizer
nutrients requirements for all the four project districts were calculated based on the
recommendations made by Pandey and Joshi, 2000.
Keywords: GIS, kriging object based image classification, soil fertility, stratified
random sampling.
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Introduction
Nepal is a land of extremes with high variability of climatic condition. In such
landscapes, topography is an overruling soil forming factor and responsible for a large
variability in soil characteristics, distribution and soil depth. Due to extreme soil depth
variability traditional soil survey is considered less meaningful.
Soil fertility in Nepal is declining despite tremendous efforts made by the Soil
Management Directorate (SMD) of Department of Agriculture (DOA) in development
aspect and Soil Science Division (SSD) of NARC in research. Farmers in remote areas
have been fertilizing their crops by using traditional manure that is sustainable (Karki
1986). However heavy soil erosion and unscientific cultivation practice has
deteriorated soil fertility especially in the mid-hills of Nepal (Maskey and Joshi 1991,
Shrestha 1997). Site specific fertilizer has been recommended to increase crop
production. Similarly, mineral fertilizer has been recommended in the mid-hills but
limited availability of mineral fertilizer has been the stumbling block and hence crop
production in Nepal has remained stagnant or declined (Joshi 1997). Furthermore,
fertilizer is not easily accessible in the remote areas of Nepal and even in region where
fertilizer is easily available, farmers deviate from the advisory dose and apply their
own rates of fertilizer creating imbalance in soil fertility (Joshi and Karki 1993, Karki
2008).
Fertilizers are the most essential plant nutrients that increase the bio-mass and improve
the quantity, market quality, value and nutritional quality of plant. So fertilizers are
indispensable elements for plant growth, development and reproduction. Intensive crop
production in agriculture over the years has resulted in soil mining. It can be seen in
many areas but particularly in old settlement of Terai and some valleys in the MidHills with the intensive agricultural practices (Karki 2008). These areas are already
facing the negative balance in the soil nutrient (Ghani and Brown 1997) which is
alarming. Chemical fertilizers play a significant role in maintaining the soil fertility at
lower cost. These are increasingly used by Nepalese farmers because of intensified
cropping system, adoption of high fertility technologies for higher yield per hectare.
Any compromise on increasing use of chemical fertilizers will inevitably result in steep
decline in food grain production and affects the food security in the country. The
results of 10,000 soil samples (soil testing and service division of DOA) indicate that
70 % of soils in Nepal are low in organic matter (especially in old settlement areas),
nitrogen and phosphorus. The application of one kilogram use of nutrients produces
seven kilogram of extra grain (SMD 2064).
Under the provision of supporting essential inputs, additional financing is made by
World Bank under the name of Irrigation and Water Resources Management Project
(IWRMP) to scale up community managed seed program and soil management. The
objective of the program is to give a stereoscopic status of nutrient deficiency,
sufficiency and toxicity and indicate their status in the map namely soil fertility
mapping for Terathum, Taplejung, Salyan and Rolpa districts. This enables farmers to
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know their soil and help to achieve sustainable production. These maps support the
policy maker in the soil management and crop production policy, identify amount of
seeds and fertilizer needed for the optimum crop production and hence make the
district food secured.
Methodology
Selecting and locating sampling pits
Initial selection of each sampling pit was based on different secondary spatial data
sources that provide information about likely variation in soil properties across the
study area. Cultivation area was extracted from three independent data sources as per
nature of the project: land cover data from Department of Survey, GoN; land use data
and potential land use data from National Land Use Project (NLUP). The common
cultivation area from these data sources was then used to extract corresponding
dominant soil type of the individual project district (land system data base of NLUP).
Land system data was further spatially merged with the corresponding VDC boundary
to ascertain soil sampling pit in every VDC of the district. This database was then
aggregated and analyzed to distribute soil sampling pit per district. The stratified
random sampling method was used to locate the sampling pit per dominant soil type
per VDC. The stratified random sampling points were generated using a simple
rejection algorithm: potential points are generated within the polygon (i.e. Dominant
Soil type per VDC) boundary based on a bivariate uniform random distribution
principle. 350 soil sample pits location were generated for individual districts. These
soil sampling pit locations were verified in topographical maps of Department of
Survey and in Google image.
The identified soil sampling pit was located in the ground with the aid of printed
Google image and GPS. The composite soil sample was taken from different soil pits
dug at 15cm to 20cm depth (As adopted in Soil fertility maps of various district,
published by Soil Management Directorate, Hariharbhawan, Lalitpur in the year
2063/64 BS along with the soil data adopting guidelines for Soil Profile (FAO 1977)
and/or Soil Survey Manual (USDA National Soil Survey Handbook, Revised 2005).
The collected soil samples were then labeled in the filed with pit number, date of
sampling, name of sampler, GPS coordinates, elevation, landform, vegetation, climate
and tentative soil classification. These samples were preserved in airtight plastic bags
while transporting from the field.
Laboratory analysis
These samples were dried in shade and powdered to be used in reagent for chemical
analysis. The laboratory testing was done for various physical and chemical properties.
The lab results were carefully analyzed for its quality assurance. 5-10 randomly
selected samples were re-analyzed and its results were compared with its original
result. The doubt sample results were re-analyzed for its verification. The following
routine analysis of soils was done in the laboratory:
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Table 1: Analysismethodapplied for variousphysical and chemicalproperties.
Soil Sample Tests
Analysis method
Texture
Hydrometer & Texture classification (USDA)
pH
1:2.5 soil water paste using combined electrode
Organic Matter
Walkley and Black Method
(OM)
Available P2O5
Bray and Kurtz method (0.03M NH4 F/0.1M HCL Extraction)
Available K2O
1N Neutral Ammonium Acetate extraction and K detected by
Flame Ignition
Total Nitrogen (N) Micro Kjeldahl method
Available Zn
Extracted by DTPA extracting solution following procedure
outlined by Lindsay and Norvel (1978) and detected in AAS
Available Boron
Hot water extraction and detection in AAS
Extracting cultivation area
Ortho-rectified medium resolution (5m) Rapid Eye multispectral (5 bands: Red, Green,
Blue, Near Infrared and Rededge) were acquired and classified to extract cultivated
area using object based image classification technique in e-Cognition software. Multi
resolution image segmentation was done at appropriate levels with different scale,
compactness and smoothness parameters. Spectral information together with Shape and
morphometric characteristics was used in different level to separate land cover/ land
use class. Normalized Difference Vegetation Index (NDVI) value close to statistical
mode of the image was used to discriminate dense forest, Sparse Vegetation, Nonvegetation and River feature. From all these class all false positives were sequentially
extracted using different criteria. NIR band have zero or very low spectral reflectance.
Thus sand area and water body was separated using NIR band ratio threshold from
river feature Class. Moderate to gentle slopes terrain are often converted to terraces for
agricultural activity. These terraces are parallel to contours, and width of such terraces
is largely uniform. This feature of the terrace offers a unique texture in the image and
can thus serve as diagnostic feature. The frequency of combination of grey levels, i.e.
texture in an image, was calculated using grey level co-occurrence matrix (GLCM).
Mean GLCM of the red band discriminates the terrace pattern clearly and was thus
used in combination with slope and NDVI to classify agricultural land. A built-up area
was extracted from Non-vegetation class based on the Haralick texture measure GLCM
Contrast. However, texture values were not calculated on the basis of original spectral
bands, but using specially transformed image, namely Red Band filtered with the use
of Laplacian Edge Detector (Type 1). The applied transformation enhanced edges of
objects representing built-up land. In addition, in order to increase accuracy of class
recognition the Standard deviation of Red band together with GLCM Homogeneity of
Red band and slope of terrain were used. The detail rule set used for extraction of
different class parameter are given in Figure 1.
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Image Pixel Level
Multi Resolution Segmentation
River
(NDVI<-0.02)
Water Body
Ratio NIR<=0.16
Non-Vegetated
Area
-0.02<=NDVI<0.05
Bare Land
MEAN Slope >
30°
Sparse Vegetation
0.05<=NDVI<0.35
Dense Vegetation
NDVI<=0.2
Bare Cultivation Area
118<=GLCM MEAN RED<=135
NDVI<=0.18
Mean Slope <=30
Brightness>=4600
Green Cultivation
Area
Brightness>=4600
Sand Area
Ratio NIR>0.16
Grass Land/Shrub
Area
Cultivation
Forest
Built up
GLCM Contrast of Laplecian Edge of Red Band >=2000
0.02<=GLCM Homogeneity RED<=0.035
MEAN Slope <=12
Standard Deviation RED>=300
Figure 1: Rule set used for extraction of different class parameter.
The cultivated area extracted using object based image classification method was then
used to prepare fertility map of corresponding district. The analyzed chemical
properties of the spatially correlated sample soil pit were stored in database in GIS
environment. Various literature and scientific publication recommend Kriging in place
of Inverse Weighted Distance, (IDW) for fertility mapping of soil chemical element
(Kravchenko et al, 1999; Hengl et al, 2007; Yasrebi et al 2009; Zandi et al 2011;
Omran, E, 2012; Chen et al). Thus Kriging interpolation method was implemented to
produce the soil fertility map of the cultivation area in the district in Geo-statistical
environment of ArcGIS software application.
Soil Fertility Rating
Soil fertility rating developed by Soil Science Division of NARC and Soil Science
Directorate, Department of Agriculture was adopted in the analysis of lab result and
Soil Fertility Mapping of the district.
Soil Chemical Results and Discussion
Soil pH
The Scatter plot of pH plotted against the number of samples along horizontal axis and
corresponding pH value shows that the maximum cluster of samples for Taplejung lies
between pH value of 5.0 and 6.0, 5.5 and 6.5 for Terathum; 6.0 and 7.0 for Salyan; 6.0
and 7.5 for Rolpa. The Bar Chart of pH of soil samples categorized according to the
rating specified above shows that around 200 soil samples are moderately acidic and
100 soil samples are slightly acidic in Taplejung; 120 soil samples are moderately
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acidic and around 115 soil samples are slightly acidic in Terathum; more than 120 soil
samples are nearly Neutral and around 120 soil samples are slightly acidic in Salyan
and above 100 soil samples are Slightly Acidic and around 70 soil samples are Nearly
Neutral in Rolpa. The histogram plot shows that mean and median of the pH for all
districts are quite similar. The distribution is similar to the typical normal distribution
curve except for Rolpa which is negatively skewed. Further, In Normal Q-Q plot also
called as normal probability plot, which is the plot of ordered data against what would
be expected if the data were drawn from a normal distribution, the majority of the
points lie approximately on the theoretical line in case of Taplejung suggesting
normally distributed whereas for the case Terathum, Salyan and Rolpa, most points
depart from the theoretical line; this suggests that they are not normally distributed.
The box plot of the pH also shows that the mean and median of the data are quite close
to each other for Taplejung, whereas the mean is slightly higher than median in case of
Terathum, Salyan and Rolpa.
Taplejung
Terathum
Salyan
Rolpa
Figure 2: Scatterplot, Bar chart, Histogram, Normal Q-Q plot, Box Plot for four
districts.
The soil’ pH analysis for these districts shows that pH below 5.5 is very limited and
organic matter content is only 3.58% for Taplejung and 2.55% for Salyan. Also only
68 and 29 soils samples out of total samples (19% and 8.3%) in Terathum and Rolpa
respectively are acidic hence lime requirement study is not done in these districts.
However, the soil pH below 5.5 could be recommended a blanket recommendation of
2-3 t ha-1. Moreover, lime application in the paddy cultivated soils should be done very
cautiously since the application decreased nutrient uptake and yield of paddy (Singh
and Singh 1980 Whalen et al. 2000) . Therefore to buffer the soil pH, well decomposed
organic manure (FYM / compost) would be the best (Wong et al. 1998). Some soil
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samples of Rolpa show slightly alkaline pH which could be due to low precipitation
and high evaporation in those area. Also there could be limestone deposit in vicinity. In
such pH micronutrient deficiency is common and need amelioration. Amelioration of
high pH soil could easily be done through increasing application of well decomposed
organic manure. The pH status in Taplejung, Terathum, Salyan and Rolpa is presented
in figure below.
a.
b.
d.
c.
Figure 3: Maps of PH Status in four districts a. Taplejung, b. Terathum, c. Salyan, d.
Rolpa.
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Organic Matter percentage (OM)
The Scatter plot of OM shows that the maximum cluster of samples lies between 3.0%
and 5.0% in Taplejung, 2.0% and 4.0% in Terathum; 2.0% and 3.0% in Salyan; 2.0%
and 4.0%. inRolpa. The Bar Chart of OM of soil samples categorized according to the
rating specified above shows that more than 200 soil samples have medium range of
Organic Matter content in Taplejung and Terathum; more than 150 soil samples have
Low range of Organic Matter content in Salyan; more than 250 soil samples have
Medium range of Organic Matter content in Rolpa. The histogram plot, box plot and
normal Q-Q plots show normal sample distribution for Taplejung whereas skewed
distribution for rest of the district.
The low amount of organic matter in soil could be due to the problem of livestock
maintenance in the hill districts as a result of manpower shortage (Bhandari and Grant,
2007) and also loss of organic matter through erosion (Dregne 1987, Gardner and
Gerrard 2003). In addition, green manuring in the remote areas of Nepal is rarely
practiced. Moreover, there is a concept among Nepalese farmer that green manure is
only applicable in submerged soil. Soil organic matter could be increased by the
addition of crop residues and also green manure plant incorporation even in upland
condition (Azmal et al. 1996). Other sources of biological N fixation and incorporation
of these materials in soil could significantly contribute to soil organic matter (John et
al. 1992). Various efforts has been extend towards improved compost making by
several government and non-governmental organization but only very limited farmers
has implemented these in real practice. Legumes are cultivated but in practice while
harvesting these are uprooted, even the root biomass is removed thereby reducing root
decomposition. These are the some of the reasons for low organic matter content in
soils in these districts.
Figure 4:Map of Organicmatter distribution in Terathum district.
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Total Nitrogen percentage (TN)
The Scatter plot of Total Nitrogen shows that the maximum cluster of samples lies
between 0.05% and 0.125% in Taplejung, 0.05% and 0.1% for Terathum; below 0.05%
in Salyan and below 0.03% in Rolpa. The Bar Chart of Total Nitrogen of soil samples
categorized according to the rating specified above shows that more than 200 soil
samples have low range of Total Nitrogen content in Taplejung and Terathum; more
than 150 soil samples have Very low range of Total Nitrogen content in Salyan
whereas more than 150 soil samples have high range of Total Nitrogen content in
Rolpa. The histogram plot, normal Q-Q plot and box plot suggests that sample data are
not normally distributed in all district.
Joshi and Karki1993, Ladha et al.(2003) and Karki(2006a) has also shown low rating
of Total Nitrogen for the hills area of Nepal. Nitrogen does not remain in soil for long
time after it is mineralized from the organic sources. Nitrogen enters via atmospheric
deposition and by application of fertilizer or organic manures, and is lost through denitrification, leaching, volatilization and removal in the crop at harvest. In Nepalese
mid-hills only 25% of the applied nitrogen is utilized as grain, straw and roots and 65%
of it is unaccounted i.e. it does not remain in soil (Ghani and Brown 1997, Pilbeam et
al. 2002). It could have been lost in leasing, soil erosion and evaporation; and even
consumed by microorganisms. Monsoon enters into Nepal through eastern sector and
precipitates in that region more than the west (Dahal and Hasegawa 2008) resulting in
high loss of Total Nitrogen due to leaching in these part of the country. Hence, there is
a low Total Nitrogen content in the soil of cultivation field in these areas. The cropping
pattern shows that 15% of the crops are grown following maize/cowpeas/peas. These
legume crops could fix little amount of nitrogen but does not remain for long time. In
addition, there is a practice that legume crops are uprooted at the time of harvest and
even the root biomass is taken out from the soil. Thus, very little organic matter and N
is added into the soil.
Available phosphorus in kg per ha (P2O5)
The Scatter plot of available phosphorus (P2O5) shows that the maximum cluster of
samples lies between 0 kg ha-1 and 100 kg ha-1for Taplejung, 0 kg ha-1and 50 kg ha-1for
Terathum, above 100 kg ha-1for Salyan and below 50 kg ha-1for Rolpa. The bar chart of
available phosphorus (P2O5) of soil samples categorized according to the rating
specified above shows that 120 soil samples have very high range of Available
Phosphorus (P2O5) and 80 soil samples are in high as well as in Low rating for
Taplejung; more than 120 soil samples have Medium range of Available Phosphorus
(P2O5) and around 115 soil samples are in high rating for Terathum; more than 250 soil
samples have very high range of available phosphorus (P2O5) and around 50 soil
samples are in medium rating for Salyan and more than 150 soil samples have Medium
range of available phosphorus (P2O5) and around 150 soil samples are in high rating for
Rolpa. The histogram plot shows, Normal Q-Q and box plot shows the distribution to
be positively skewed for all district.
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Figure 5:Map of Nitrogen distribution in Terathum district.
Available P2O5 in Tapljung District is found to have high rating. Only 29% of the
samples analyzed shows lower rating. In the soil sample of Terathum 41 (11%) soil
samples are low to very low groups. Available Phosphorus (P2O5) in Salyan District is
found in very high rating. The mean value is 278.50 kg per ha. Only 11% of the
samples analyzed show lower rating 71% are in very high rating. In the soils of Rolpa
only 6.3% of soil samples are in low to very low rating. 48% fall under medium level
and 42% on higher category. It shows that the P in soil samples is not related to any of
other soil properties. If we say it is related to organic matter which contains also
phosphorus, the number of high phosphorus containing soil samples are not that much
high in number. Similarly low organic matter and low P2O5 could not be correlated.
Likewise relation with total nitrogen content is also not well related. But there could be
some relation with available K2O which cannot be supported by any literature. In the
plant system there is synergisms in the uptake of P and K by plant (Jungk and Claassen
1986). The higher amount of P2O5 is also observed in their soil analysis by Soil
Science Division, Khumaltar(SSD 2003) .
Available Potash in kg per ha (K2O)
The Scatter plot of available potash (K2O) shows that the maximum cluster of samples
lies between 200 kg ha-1and 300 kg ha-1for Taplejung; 200 kg ha-1and 300 kg ha-1for
Terathum, below 200 kg ha-1 for Salyan and Rolpa. The bar chart of available potash
(K2O) of soil samples categorized according to the rating specified above shows that
250 soil samples have Medium range of available potash (K2O) and 70 soil samples are
in high rating for Taplejung; around 150 soil samples have high range of available
potash (K2O) and around 130 soil samples are in medium rating for Terathum; around
140 soil samples have Medium range and around 80 soil samples are in high rating for
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Salyan; more than 150 soil samples have Medium range and around 90 soil samples are
in high rating for Rolpa. The histogram plot, Normal Q-Q and Box plot shows samples
are normally distributed in Taplejung and Terathum whereas mean is higher than
median for Salyan and Rolpa.
Figure 6:Map of Phosphorus distribution in Salyan district.
In all district, the soil K shows higher level. This could be due to the reasons that the
textures of soil in Taplejung are generally light that contain silt and sand more than
clay contents. Sand and silt are the source of potassium in soil. Abundance of K2O in
the clay fractions were from the breakdown of the structural units of the expansible
minerals, micas and feldspars (Igwe et al. 2005)
Soil Texture
The Scatter 3D plot shows that majority of the sample has dominant proportion of Sand
in all districts. The comparative box plot of the Sand Clay and Silt also shows that
Sand occupy higher composition and Clay occupy lower composition in these district.
The composition of Sand, Clay and Silt form the basis of Texture nomenclature. The
Bar Chart of the texture classification of soil sample of Taplejung shows to have Sandy
loam texture in more than 150 samples and Sandy Clay loam texture in very minimum
(around 10) samples; Sandy loam texture in more than 150 samples and loam texture in
more than 100 samples for Terathum, Loam texture in more than 150 samples and
Sandy loam texture in around 150 samples for Salyan; Loam texture in more than 150
samples and Clay loam texture in around 100 samples for Rolpa.
Soil texture and soil structure are both unique properties of the soil that will have a
profound effect on the behavior of soils, such as water holding capacity, nutrient
retention and supply, drainage, and nutrient leaching. In soil fertility, coarser soils
generally have a lesser ability to hold and retain nutrients than finer soils. However,
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this ability is reduced as finely-textured soils undergo intense leaching in moist
environments. Sandy loams are productive soil but their capacity to hold nutrients and
moisture is limited (Silver et al. 2000). These soils have good aeration and water
movement. Infiltration will be higher, increasing higher drainage class (Bronick and
Lal 2005). These soils dry up fast and for good crop production frequency of irrigation
should be high and water should be supplied via control irrigation system (Phene and
Sanders 1976). Heavy amount of organic manure is needed for nutrient maintenance
(Schjnning et al. 2002).
Figure 7:Map of Potash distribution in Rolpa district.
Figure 8:Map of Soil Texture in Taplejung district.
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Available zinc in mg per kg (Zn)
The Scatter plot of available zinc (Zn) shows that the maximum cluster of samples lies
between 0.5 to 1 mg per kg and between 2.5 to 3.5 mg per kg for Taplejung, less than
1mg per kg for Terathum, lies between 0.5 to 1 mg per kg for Salyan and scattered
between 0.3 to 4.48 mg per kg for Rolpa. The bar chart of available zinc (Zn) of soil
samples categorized according to the rating specified above shows that more than 250
soil samples have zinc deficiency and more than 50 soil samples are in sufficiency
rating for Taplejung; all soil samples have zinc deficiency for Terathum and Salyan,
around 250 soil samples have zinc deficiency and remaining 100 samples have
sufficient zinc composition for Rolpa. The histogram plot, Normal Q-Q and box plot
shows normally distributed sample for Salyan whereas skewed distribution in case of
Taplejung, Terathum and Rolpa.
Figure 9:Map of Zinc distribution in Taplejung district.
Boron in mg per kg (B)
The Scatter plot of Boron (B) shows that the maximum cluster of samples lies below 1
mg per kg for Taplejung; between 0.5 to 1.5 mg per kg for Terathum, well scattered
between 0.5 to 1.5 mg per kg for Salyan and well distributed between 0.25 mg per kg
and 1.0 mg per kg for Rolpa. The bar chart of Boron (B) of soil samples categorized
according to the rating specified above shows that more than 150 soil samples have
sufficient Boron rating and 150 samples have deficiency rating for Taplejung, around
250 soil samples have sufficient rating and around 60 samples have deficiency rating
for Terathum, around 250 soil samples have sufficient Boron content and more than 60
Samples have Deficiency rating for Salyan; around 200 soil samples have sufficient
Boron content and more than 125 samples have deficiency rating for Rolpa. The
histogram plot, Normal Q-Q and box plot shows positive skewed distribution for
Taplejung, Terathum and Rolpa whereas normal distribution for Salyan.
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Fertilizer (mt)
Figure 20:Map of Boron distribution in Rolpa district.
400
350
300
250
200
150
100
50
0
375.08
307.84
268.86
115.90
89.43
Taplejung
87.0471.65
Terathum
Total Nitrogen (TN)
131.81
78.8779.14
Rolpa
112.13
70.21
salyan
Available Phosphorus (P2O5)
Available Potassium (K2O)
Figure 11: Comparative barchart for fertilizerrequirement.
The comparative bar chart for the fertilizer requirement shows that Total Nitrogen
requirement is high in all four districts with highest in Salyan and Taplejung district.
However, available phosphors and potassium requirement is within the similar range in
all four districts. Among all four districts, deficiency of all kind of fertilizer is high in
Taplejung whereas it is least in Rolpa.
387
24-25 March 2015
Conclusion
Soil fertility of Taplejung, Terhathum, Salyan and Rolpa districts are evaluated by
collecting soil samples and analyzing them in the laboratory. The maps were prepared
based on the lab results of the sampling pit applying Kigring interpolation method in
GIS environment. On the whole for all four districts, majority of soils are loamy in
texture, slightly acidic to near neutral in soil reaction, low in total nitrogen, available
zinc and boron. Soil organic matter falls under medium to low categories. Available
phosphorus and potassium varies and fall under all the categories.
Total nitrogen which is mainly associated with the organic matter is also low. Since
nitrogen is a mobile element; even if found in higher amount in soil, farmers are
advised to apply full rate of nitrogen to their crops. Available P2O5 and K2O vary and
the calculation of fertilizer requirement is done mainly based on the P2O5 and K2O.
Plant available Zn and B are mostly deficient. Where these elements are found in
higher amount care should be taken to apply these elements to the soil. The range of
toxicity, sufficiency and deficiency is so narrow, if Zn and B is applied in its higher
containing soil, it could prove to be toxic and amelioration would be very difficult.
The soil fertility of these four districts could be rated as medium to low categories.
Farming is based on organic manure produced in their yard. Although farmers use
heavy amount of FYM massive soil loss by water erosion washes away the applied
manure and soil fertility is deteriorated. Farmers are found using mineral fertilizer
only in the accessible area that too is not proportionally balances. Timely and adequate
amount of fertilizer availability is being a major constraint in the remote districts and
technical advice by qualified manpower is also very limited. In the hills soil moisture is
always deficit and gravity irrigation is only feasible in the valleys, and hence
application of soil moisture conservation and adapting water harvesting technology to
improve crop production is very much needed for these hill districts.
The fertility maps produced in the study are based on Kigring interpolation method.
These methods have a tendency to overestimate and underestimate the extreme value.
This is in fact not a problem for the district level fertility status. However, for field
level application, it is advised to test the field soil chemical property before application
of the fertilizer. Further, the GIS database prepared is extendable for future monitoring
of soil fertility of the district. This will help to prepare different time series fertility
data of the district which can be used to analyze the fertility tendency of soil in the
district. Thus will help is long term agriculture planning of the district.
Acknowledgement
We acknowledge our sincere gratitude to Government of Nepal/Ministry of Agriculture
Development, Department of Agriculture, Irrigation and Water Resource Management
Project (IWRMP), for entrusting us with the project assignment’; IWRMP Project
Manager Mr. Satya Narayan Mandal and senior Agriculture Engineer of IWRMP Mr.
388
24-25 March 2015
Chaittya Narayan Dongol for their cooperation, support and valuable suggestions;
NGC lab and WETC for their hard work and continuous dedication in chemical
analysis of the soil which is the core part of the study. Last but not the least, we thank
experts, engineers, technicians and supporting staffs from Joint Venture of Soyan
Mega Soft–NEST-GRID for their hard work and concerted effort for the completion
of this study.
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392
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GSS-8
Preparation of ata ase and Soil Map of Nepal using WRB 2010
Classification System
Subhasha N Vaidya
(
)
Kamal Sah
, Nepal
Abstract
A cooperation agreement was signed between the Institute of Soil Science, Chinese
Academy of Sciences (ISSCAS) and the Nepal Agriculture Research Council (NARC)
.The main objective was to prepare a Soil Map of Nepal using the World Reference
Base (WRB) 2010 soil classification system at 1:1000,000 scale in ESRI Shapefile
format and also to prepare national soil data base containing soil profile information
.Working on behalf of the NARC the Soil Science Division has prepared a Soil Map of
Nepal using WRB 2010 classification system at a scale of 1: 1000,000 scale and also
prepared soil profile data base exactly in the standard format that fits into the
Harmonized World Soil Data Base (HWSD). For this purpose Soil profile information
from Land Systems Reports of the LRMP (Land Resources Mapping Project) were
extensively used along with some other soil information available with the Soil
Science Division.As per the HWSD, the physico-chemical properties have been
converted into two layers in each profile viz 0 -30 and 30 -100. For this purpose the
Batjes formula has been used. Land systems comprise the soil mapping unit within
each of which occurrence of major soils have been shown with minor association.
Calcaric Fluvisols (FLca), Eutric Gleysols (GLeu), Calcaric Phaeozems (PHca), Gleyic
Cambisols (CMgl), Hapli cPhaeozems (PHha), Eutric Gleysols (GLeu), Chromic
Cambisols (CMcr), Dystric Regosols (RGdy), Chromic Luvisols (LUcr), Chromic
Cambisols (CMcr), Eutric Cambisols (CMeu), Humic Umbrisols (UMhu), Leptic
Umbrisols (UMle), Leptic Regosols (RGle) along with some minor soils as well. The
data base also contains a complete set of physic-chemical properties of each layer (030) and (30-100) viz, Soil texture, WHC, BD, pH H20, pH CaCl2, OM, total N, C/N
ratio, otal CaCO3, Ca,Mg, Na, K, P, CEC, BS and EC.
Keywords: HWSD, physico-chemical
World Reference Base (WRB).
Introduction
Located between 26o 22’ to 30o 27’ north latitude and 80o 4’ to 88o 12’ east
longitude, and having an area of 147181 sq. km with rectangular shape , Nepal is a
country of extremes. Climate ranges from sub-tropical to arctic. Physiography includes
vast alluvial plains to permanent snow covered rugged peaks. Vegetation includes
tropical Sal forests to arctic like tundra Nival zones. So diverse is the country that one
easily encounters banana and apple ripening in the same season within a few kilometer
distances from south to north. With more than a dozen spoken languages and as many
dialects, people of Nepal are also diverse as land.Since Climate, Physiography, Parent
materials, Vegetation are some of the characteristic features closely associated with
Soils, they are briefly discussed below.
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24-25 March 2015
Though small in size, the country has extreme diverse climates, subtropical to arctic
temperature regimes and arid to per-humid moisture regimes. High relative relief and
pronounced wet and dry monsoon seasons are the characteristic features of this country
that can be considered responsible for the present state of diversity in terms of ecosystem, flora and fauna.
Physiography and Geology
Five physiographic regions have been recognized based primarily on the bedrock and
surficial geology. They are briefly discussed below:
Tarai
Considered as the bread basket, this southern flank of the country is mostly flat to
gently sloping and has the elevation range between 60 to 330 m above mean sea level.
The geology consists of recent and post-Pleistocenealluvium predominantly loamy
textured and stone free. Drainage, texture, natural vegetation and present land-use vary
with change in relief. (Sherchan and Vaidya 1983).
Siwaliks
Located at the northern end of the Tarai, the Siwaliks consist predominantly north
dipping, semi consolidated inter bedded tertiary to quaternary sandstones, mudstones,
siltstones and conglomerates. The landscapes is quite rugged and steep slopes with
weakly consolidated bedrock and are very vulnerable to severe surface erosion. The
region also includes some structurally controlled valleys whose outlets in the past were
blocked by rapid tectonic uplift of the Siwalik hills. Agriculture and settlements in the
Siwaliks region are centered around these inner valleys.(SSD 1998).
Middle Mountain
Considered as the homeland of most native people, the region consists of Cambrian to
pre cambrianphyllites, schistss, and quartzites and also granites and limestones of
different ages. Diverse climate and landscapes support year round diverse agricultural
production on the river valleys, sloping terraces and level terraces.
High Mountains
The region has more highly metamorphosed phyllites, schists, gneisses and
quartzites.All valleys in the region have been glaciated. The relief is very
high(>3000m). The climate is very cool and hence less suited to chemical weathering.
Consequently soils are shallower.
High Himal
The elevation range from around 3000mto 8848m (Mt.Everest).and hence most snow
peaks are located in this region. The region has gneisses, limestones and shales of
different ages. Over 86 percent of the region has bedrock at or near the surface.
However there are few small pockets where agriculture is done.
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24-25 March 2015
Land Resources Mapping Project (LRMP) maps and reports published in 1986 have
remained to date the most comprehensive data base with regards to Land and Soils
resources of the country, though sporadic soil surveys have been conducted by
different national institutions. And moreover they contain comprehensive physicochemical laboratory analysis data and have geo-referenced information as well.
Hence,the present soil map and data base preparation were heavily based on them.
Along with whatever sporadic information we have with regards to soils and lands
have also been for the present work as references. (KESL 1986).The Land sat
interpretation based on Nelson’s(FAO 1980) recognition of Physiographic regions
with minor alterations formed a sound base and it was guided by intensive aerial
photographic interpretation and extensive field surveys based on which further
recognition and delineation of different land systems and land types within each of the
physiographic regions were accomplished . Though LRMP had made about 6000
profile inspections, 158 geo-referenced representative soil profiles were analyzed for
physic-chemical properties and they have been used for the present purpose.T he
LRMP has followed USDA soil classification system. (USDA 1999).The original
profile physico-chemical laboratory data were converted to suit to the requirement of
the HWSD using the standard formula and were expressed in terms of the Surface soil
(0-30 cm) and Subsoil (30-10 cm). An example of an original profile depth. Similar
conversion exercises were done to calculate all the parameters right from % sand to
electric conductivity.
Depth, cms
0-15
15-40
40-80
80-120
Ph, units
8.5
7.2
7.5
6.0
For the surface soil 0-30 cm
8.5 x ( 15/30) + 7.2 x(15/30) = 7.85
For the subsoil 30-100 cm
7.5x(10/70) + 7.5 x (40/70) + 6.0 x(20/70) = 7.03
Soils have been mapped with reference to the recognized land systems units. In what
follows is a brief description of the mapping units and occurrence of dominant soils as
per the WRBS in each of the mapping units.
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24-25 March 2015
Calcaric Fluvisols (FLca)
Depth,cm
Sand%
Silt%
Clay%
USDA_tex
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
CEC_soilcmol
kg-1
BS,%
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds m1
ece
0-30
26
66
8
Silt loam
1.51
0.52
8.00
14.20
100.00
20.30
6.70
0.00
0.20
77
20
3
Loamy
sand
1.60
0.17
8.00
9.90
100.00
17.40
7.00
0.00
0.17
30-100
Eutric Gleysols (GLeu)
Depth,cm
Sand%
Silt%
Clay%
19
21
50
50
31
29
0-30
30-100
USDA_tex
Silty clay
loam
Clay loam
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
1.30
1.32
0.76
0.37
7.22
8.03
CEC_soilcmol
kg-1
11.11
9.55
BS,
%
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds m1
ece
79.90
85.94
6.50
6.54
1.28
1.40
1.25
1.03
0.06
0.06
Calcaric Phaeozems (PHca)
Depth,cm
0-30
30-100
Sand%
24
48
Silt%
62
45
Clay%
14
8
USDA_tex
Silt loam
Loam
Ref bulk
density
g cc-1
1.43
1.56
Oc
%
1.00
0.15
396
Ph_h2o
7.70
8.07
TEB
CEC_soilcmol BS,
cmol
kg-1
%
,kg-1
15.30
95.80 17.96
11.40
100.00 20.41
CACO3,
%
3.22
5.69
ESP,
%
0.00
0.00
Ds
m1
ece
0.28
0.24
24-25 March 2015
Gleyic Cambisols (CMgl)
Depth,c
m
0-30
30-100
Sand%
24
Silt%
48
Clay%
28
83
14
3
USDA_tex
Clay loam
Loamy
sand
Ref bulk
density
g cc-1
1.33
Oc
%
1.44
Ph_h2o
7.81
1.65
0.18
8.07
Ref bulk
density
g cc-1
Oc
%
CEC_soilcmol
kg-1
21.13
12.44
TEB
BS,
cmol
%
,kg-1
100.00 27.57
CACO3,
%
3.71
ESP,
%
0.00
Ds
m1
ece
0.26
100.00 18.97
5.44
0.00
0.13
Haplic Phaeozems (PHha)
Depth,c
m
Sand%
Silt%
Clay%
38
42
20
58
39
3
USDA_te
x
Ph_h2o
CEC_soilcmol
kg-1
BS,
%
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds
m1
ece
0-30
30-100
Loam
Sandy
loam
1.40
2.18
5.90
15.10
55.00
8.25
1.15
0.00
0.11
1.57
0.70
5.99
10.64
64.14
6.81
0.30
0.00
0.09
Chromic Cambisols(CMcr)
Depth,cm
Sand%
Silt%
Clay%
0-30
17
52
31
10
51
39
30-100
USDA_tex
Silty clay
loam
Silty clay
loam
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
CEC_soilcmol
kg-1
BS,
%
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds
m1
ece
1.30
1.33
5.24
8.08
53.53
4.34
0.43
3.26
0.06
1.25
0.75
5.20
8.30
55.00
4.60
0.50
3.61
0.04
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24-25 March 2015
Dystric Regosols (RGdy)
Depth,cm
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
1.57
0.65
6.23
0.76
6.85
Sand%
Silt%
Clay%
66
25
9
USDA_tex
Sandy
loam
65
26
10
Sandy
loam
1.56
USDA_tex
Loam
Ref bulk
density
Oc
g cc-1
%
1.38
0.72
0-30
30-100
BS, %
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
7.03
100.00
10.22
1.53
5.69
0.21
9.24
100.00
23.19
1.72
3.48
0.29
Ph_h2o
4.57
CEC_soilcmol
kg-1
5.89
BS,
%
28.67
TEB
cmol
,kg-1
1.73
CACO3,
%
0.10
ESP,
%
0.17
Ds m1
ece
0.02
6.09
10.18
43.71
3.47
0.40
2.83
0.21
CEC_soilcmol
kg-1
Ds
m1
ece
Chromic Luvisols (LUcr)
Depth,cm
0-30
30-100
Sand%
31
Silt%
47
20
36
Clay%
22
45
Clay
1.25
0.40
USDA_tex
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
CEC_soilcmol
kg-1
Chromic Cambisols (CMcr)
Depth,cm
Clay%
BS,
%
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds
m1
ece
Sand%
Silt%
44
40
16
Loam
1.45
0.73
5.93
10.67
39.33
4.17
0.13
0.00
0.06
38
43
18
Loam
1.42
0.53
5.83
9.51
46.57
4.46
0.07
0.00
0.06
0-30
30-100
398
24-25 March 2015
Eutric Cambisols (CMeu)
Depth,cm
0-30
Sand%
34
Silt%
49
30-100
34
47
Clay%
17
19
USDA_tex
Loam
Loam
Ref bulk
density
Oc
g cc-1
%
1.42
0.28
1.40
Ph_h2o
5.48
0.23
5.40
CEC_soilcmol
kg-1
4.76
4.60
BS,
%
53.60
TEB
cmol
,kg-1
2.48
CACO3,
%
0.78
ESP,
%
4.20
Ds
m1
ece
0.04
58.00
2.60
0.70
4.35
0.04
BS,
%
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds
m1
ece
Humic Umbrisols (UMhu)
Depth,cm
Sand%
Silt%
Clay%
USDA_tex
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
CEC_soilcmol
kg-1
0-30
25
49
26
Loam
1.34
4.94
5.28
13.96
27.63
3.81
0.31
1.91
0.09
51
38
11
Loam
1.52
0.04
6.01
4.51
53.94
2.41
0.37
4.43
0.10
30-100
Leptic Umbrisols (UMle)
Depth,c
m
Sand%
Silt%
Clay%
83
12
5
USDA_tex
Loamy
Sand
75
20
5
Sandy loam
0-30
Ref bulk
density
g cc-1
Oc
%
Ph_h2o
CEC_soilcmo
l kg-1
1.69
1.80
5.60
7.30
1.68
0.75
5.70
3.50
30-100
399
BS, %
88.00
100.0
0
TEB
cmol
,kg-1
CACO3,
%
ESP,
%
Ds
m1
ece
6.40
0.80
2.74
0.08
3.70
0.50
5.71
0.07
24-25 March 2015
1. The active alluvial plains of the Tarai Physiographic region which are subject
to variable seasonal flooding. Calcaric Fluvisol (FLca) is the major soils in
the active alluvial plains followed by some Gleyic Fluvisols (FLgl)
andEutric Cambisols (CMeu) . This unit comprises of significant area under
river and sand bars
2. Recent alluvial plains with dominant slope ranging from less than ½ to 1
degree slope with dominantly poor to imperfect drainage class with some area
have moderately well drained drainage class. Eutric Gleysols (GLeu) is the
major soils in the recent alluvial plains followed by some
GleyicFluvisols(FLgl)
,Eutric
Cambisols
(CMeu)
and
some
minorHaplicPhaezomes(PHha),HaplicArenosols (ARha) and Chromic
Cambisols (CMcr).
3. The upper piedmonts with considerable relief variations (at some places about
20 degree slopes) have Calcaric Phaeozems (PHca) and Haplic Phaezomes
(PHha). Other soils in this mapping unit are Haplic Umbrisols (UMha),
Luvic Phaeozems (PHlu), EutricCambisols (CMeu), Dystric Cambisols
(CMdy) and Calcaric Cambisols (CMca).
4. The active and recent alluvial plains of the Siwalik Physiographic region:
Gleyic Cambisols (CMgl) is the major soils with some
EutricCambisols(CMeu) . Minor inclusions are Calcaric Fluvisols (FLca)
and Eutric Gleysols (GLeu) This mapping unit comprises significant area
under river and sand bars.
5. Ancient river terraces with varying relief conditions have dominantly Haplic
Phaeozems (Phha) with some Luvic Phaeozems (PHlu), Eutric Cambisols
(CMeu) Rhodic Alisols (ALrh) and some minor inclusions of Dystric
Cambisol sand Chromic Lixisols (LXcr).
6. The depositional basins with varying relief conditions range from depressional
, gently rolling to highly dissected terrain. Eutric Gleysols (GLeu) is the
dominant soils in association with Humic Acrisols (AChu), Chromic Alisols
(ALcr) and Humic Umbrisols (UMhu).
7. The moderately to steeply sloping hilly terrain of the siwaliks. Chromic
Cambisols (CMcr) is the major soils in association with Chromic Luvisols
(LUcr).
8. Steep to very steeply sloping mountainous terrain of the siwaliks. Dystric
Regosols RGdy) is the major soils in association with minor Haplic Luvisols
(LUha)
9. Depositional alluvial plains and fans of the middle mountain Physiographic
region. GleyicCambisols (CMgl) is the major soils with minor inclusions of
Chromic Luvisols (LUcr), Calcaric Cambisols (CMca), Eutric Fluvisols
(FLeu), Eutric Gleysols (GLeu), Dystric Gleysols (GLdy) and Sodic
Gleysols(GLso) The unit comprises of significant areas under rivers and
sandbars.
10. Ancient lake and river terraces with varying degree of dissections. Chromic
Luvisols (LUCr) is the major soils in association with Gleyic Cambisols
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24-25 March 2015
(CMgl) with minor inclusions of Chromic Alisols (ALcr)and Chromic
Acrisols (ACcr)
11. Moderately to steeply sloping mountainous terrain of the middle mountains.
Chromic Cambisols (CMcr) is the major soils in association with Dystric
Cambisols (CMdy) with minor inclusions of Chromic Luvisols (LUcr),
Humic Umbrisols (UMhu), Gleyic Cambisols (CMgl), Leptic Umbrisols
(UMle), Haplic Regosols (RGha), Gleyic Regosols (RGgl), Haplic Acrisols
(ACha), Leptic Regosols (RGle).
12. Steeply to very steeply sloping mountainous terrain of the middle mountains.
Eutric Cambisols (CMeu) is the major soils in association with Leptic
Regosols (RGle) with minor inclusions of Haplic Arenosols (ARha), Humic
Umbrisols (UMhu), Leptic Cambisols (CMle), Chromic Alisols.
13. The alluvial plains and fans of the high mountain physiographic region. Gleyic
Cambisols (CMgl) is the major soils in association with Leptic Cambisols
(CMle) with minor inclusions of Eutric Cambisols (CMeu) and Haplic
Fluvisols (FLha) This unit comprises some area under rivers and boulders .
14. The post glaciated mountainous terrains with varying degree of steepness lying
below altitudinal limit for arable agriculture. Eutric Cambisols (CMeu) is the
major soils in association with Leptic Cambisols (CMle) and Leptic
Regosols (RGle) with minor inclusions of Humic Umbrisols (UMhu),
Dystric Cambisols (CMdy), Calcaric Luvisols (Luca) Calcaric Phaeozems
(PHca) Chromic Cambisols (CMcr) This unit comprises of some bare rocks
as well.
15. The post glaciated mountainous terrains with varying degree of steepness lying
above altitudinal limit for arable agriculture. Humic Umbrisols (UMhu) and
Leptic Umbrisols (UMle) are the major soils with minor inclusion of Entic
Podzols (PDen)
16. The alluvial, colluvial and morainal depositional surfaces with high relief
conditions.Leptic Umbrisols (UMle) is the major soils with minor inclusions
of Leptic Cambisols (CMle), Leptic Regosols(RGle), Leptic Podzols(Pdle),
Entic Podzols (PDen), Histic Gleysols (GLhi)
17. Steeply to very steeply sloping mountainous terrain of the high Himalayas.
This unit comprises mostly rockland with minor Leptic Regosols (RGle)
18. Lake
19. Glaciers
20. Gravel Beds
Mapping units 4, 9 and 13 have been combined as they have GleyicCambisols
(CMgl) as the dominant soils, though they have different proportions of minor
soils.
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24-25 March 2015
Figure 1: Physico-Chemical Characteristics of the major soils of Nepal.
A comprehensive soil database of Nepal has been prepared that fits into HWSD. This
database is available in the Soil Science Division Khumaltar.
References
Kenting Earth Sciences Limited .1986. Land Resource Mapping Project,Land Systems
Report, The Soil Landscapes of Nepal.
SSD. 1998. Soils of Okhaldhunga district. Soil Science Division, Nepal Agricultural
Research Council, Khumaltar. Nepal
Sherchan DP and SN Vaidya. 1983. General Soil Survey Report of Dailekh District,
Bheri Zone. Division of Soil Science and Agricultural Chemistry.Department
of Agriculture Khumaltar Nepal.
USDA. 1999. Soil Taxonomy: A basic system of soil classification for making and
interpreting soil surveys. Natural Resources Conservation Service.http:/
/soils.usda.gov/ United States Department of Agriculture, Washington, USA.
402
24-25 March 2015
GSS-9
Modeling of Soil Organic Matter Content from
World View-2 Sensor in Nayavelhani VDC of Nawalparasi District, Nepal
Umesh K Mandal
Central Department of Geography, Tribhuvan University, Nepal
Abstract
Soil organic matter (SOM) is one of the fundamental soil properties affecting productivity
of crops by controlling nutrient budgets in agricultural production systems. Visual and
qualitative interpretation of air-photos is still the base of mapping of SOM as most
common method. Quantitative estimation of soil organic matter content (SOM) is
essential when there is scanty of soil test laboratories, its strong spatial dependence and
its measurement is a time and labor-consuming procedure and emerging geographical
science information technology. In the present attempt, soil organic matter content is
modeled by using airborne world view-2 reflective remote sensing methodology and it
was tested in Nayavelhani (62.31 sq.km) VDC of Nawalparasi district of Nepal. SOM was
found to be measured ranging from 0.14 % to 4.96 %, with a mean of 1.57 %. Multiple
correlation analysis was performed between the SOM content of 38 soil samples and the
corresponding digital number (DN) of seven multispectral bands (bands 2-8) of World
View-2 Star trackers imagery.
Based on correlation analysis, multiple regression model was built to estimate the soil
organic matter content based on MS bands as explanatory variables andPrincipal
component analysis has thus facilitated the selection of a more effective set of bands for
the prediction of mean SOM content it was found significant explaining 31 percent
spatial variability of SOM. Visible bands (V) have shown higher significance in
estimating the SOM than the Near-Infrared bands (NIR). Among the visible bands, Blue
and and Infrared NIR-2 were found having the greater strength to determine the SOM in
decreasing order of magnitude. Remotely sensed data such as World View-2 Star trackers
imagery have the potential as useful auxiliary variables for estimating SOM content.
Key words: Digital number, World View-2, coefficient of the estimator, correlation, soil
organic matter content.
Introduction
Soil organic matter is vital to precise agriculture and soil evaluation and essential
macronutrient for increase soil fertility, plants growth and development that is
extremely influential on soil physical, chemical, and biological processes. Not only
this, water and nutrient holding capacity are enhanced and soil structure is improved
with increasing SOM but it is one of the most deficient soil nutrients in terrestrial
ecosystems. Proper and efficient management soil organic matter can enhance
productivity and environmental quality along with reduction of the severity and costs
of natural disasters, such as drought, flood, and disease (Chen and Aviad 1990 and
Stevenson and He 1990). Apart from this, increasing SOM can reduce atmospheric
CO2 levels contributing to prevention of global warming (Yadav and Malanson 2007).
403
24-25 March 2015
Remote sensing application has become a subject of wider interest for soil scientists.
Remote sensing has been playing a significant role in both soil survey and mapping of
soil nutrient applications after the development of methods using optical remote
sensing in combination with field measurements studies during the last decade
(Ben-Dor 2002, Dehaan and Taylor 2002).
Continuous cropping and its rotations can produce more biomass and cover and
ultimately, it results greater amounts of soil organic matter (Gerritse and Robert 1988).
Many remote sensing methods were studied to map soil organic matter in the past
decades. Soil moisture, soil organic material and soil nitrogen in Australia were
predicted using NIR spectral method.
Organic matter has a strong influence on soil
reflectance. Spectral reflectance generally
decreases over the entire short wave region
as organic matter content increases (Stoner
and Baumgardner 1980).
This study was designed to evaluate the
potential of spectral analysis of World View2 Star trackers reflective data as an approach
for mapping soil organic matter content in
sub-tropical regions. This shows how
principal components analysis as a
multivariate statistical technique can be
readily adapted to soil nutrient mapping in
reconstructing a multiple regression model
for estimating the magnitude of soil organic
content in Nayabhelhani VDC of
Nawalparasi District of Nepal.
Figure 1: location map of study
area.
Study area
The study area is Nayabelhani VDC lying in central part of Nawalparasi district, Nepal
(Figure1), covering total area of 62.31 sq.km. The study area is ranging from 100 meter
elevation from mean see level to 500 m with an average of 265 m and from less
than 1° to greater than 30° slope predominated by 1-5°. Geologically the study area is
originated in two different geological period as Pleistocene to middle Miocene and
recent and Pleistocene. Arun Khola is the major river draining 1096 sq km of the total
geographical area.The average maximum and minimum temperature of 5 years period
(2006-2010) is found to be 30.78 °C and 18.99°C, respectively with the average annual
mean temperature of 24.89 °C. The average annual rainfall is 2851.44 mm out of
which seventy percent of annual total rainfall (2015.70mm) is received during the
months of rainy season.
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24-25 March 2015
World View-2 image acquisition and processing
In order to model/predict soil organic matter content(SOM) in the study area using
remotely sensed data as auxiliary variables, World View-2 image was acquired on 4
April, 201123 .8-channel World View-2 imagery of Star trackers was obtained
covering the study area from National
Land Use Project (NLUP), Nepal.
Normalized difference vegetation index
(NDVI), as widely used as vegetation
spectral index in Remote Sensing was used
for showing abundance of vegetation cover
(Chen and Brutsaert 1998). Negative NDVI
values were dominant in the study area
indicating that the study area was
comprised mostly of bare soil when the
image was acquired.
Soil Survey and Analysis
Table 1: Technical specification of World
View-2
Band
No
8
Spectral
range (nm)
400-1040
Spatial
Resolution
mss (m)
1.85
Image
Swath
(km)
16.4
A total of 65 soil samples from epipedon Figure 2: Distribution of soil samples
were collected from
different land use
collection pits.
mainly from agriculture fields in January 6,
2013. Walkley-Black is one of three methods used for organic matter content
determination. The calculation of organic matter assumes that 77% of the organic
carbon is oxidized by the method and that soil organic matter contains 58% C. Since
both of these factors are averages from a range of values, it would be preferable to omit
them and simply report the results as "easily oxidizable organic C." (Schulte and
Bruce 2009).
Multivariate Statistical Analysis
Multivariate statistical analysis used in the present investigation includes correlation,
regression and principal component analysis (PCA). Multivariate correlation and
regression analysis was performed to calculate the nature, direction and strength of
association between soil organic matter content and selected spectral band digital
number (DN) as variables respectively. Relationship between spectral bands as
independent or predictor variables and SOM as a dependent or criterion variable was
characterized. Multiple regression model was built establishing the correlation between
SOM and World View-2 satellite data. Multiple linear regression was conducted for
SOM of the 60 soil samples with DN of Bands 2–8 of the World View-2 Star trackers
(raw and natural log-transformed) as the independent variables. Principal component
405
24-25 March 2015
analysis (PCA) was performed using same bands to compute underlying set of
independent orthogonal component eliminating all redundant bands arising the
problem of multi-collinearities while operating multiple regressions. PCA was applied
to isolate visible and Near-Infrared (NIR) dimensions, because initial multiple
regression was seen unsatisfactory by presence of multi-colinearities among spectral
bands. The component extracted from PCA was then used as basis for reformulating
the previous multiple regressions to provide a means of predicting or modeling the
magnitude of soil organic matter content in Nayabelhai VDC of Nawalparasi district.
Spectral behavior of soil organic matter content
The paper is embedded by theoretical consideration of Remote Sensing application in
soil nutrient estimation by specifying the spectral behavior of soil organic matter.
Organic matter has a
strong influence on soil
reflectance.
Spectral
reflectance
of
soil
generally decreases over
the entire short wave
region as organic matter
content increases (Stoner
and Baumgardner 1980).
The spectra of soils with
organic-matter contents
greater than 5 % often Figure3: Spectral characteristics of soil derived from
have a concave shape
Stoner and Baumgardner (1981).
between 0.5 and 1.3 μm.
Organic-matter content greater than 20% depend on the decomposition of the organic
material. Spectra of fully decomposed (sapric) materials resemble curve A of Figure. 3,
whereas spectra of partially decomposed (hemic) materials resemble curve D of Figure.
3 (Stoner and Baumgardner 1981). The spectral reflectance of minimally decomposed
(fibric) organic matter is high in the near infrared and is similar to the spectral
reflectance of senescent leaves (Stoner and Baumgardner 1981). Curve E in Fig 3
represents the spectra of soils with high iron-oxide content (greater than 4 %) such as
the tropical soils (oxisols) observed by Stoner and Baumgardner (1980). Iron
absorption in the middle infrared by these soils can be strong enough to obliterate the
water-absorption band at 1.4 μm (Stoner and Baumgardner 1981). As soil moisture
increases, reflectance of soil decreases at all wavelengths. Texture of soil will cause
increased reflectance with decreased particle size as the bigger particles like rocks,
sand, and soils basically cast a larger shadow and a large number of soil properties
such as, soil moisture, organic matter, particle size distribution, iron content and
surface conditions, influence the soil reflectance (Stoner et al. 1980, Stoner and
Baumgardner 1981).Bare rock and soil reflect strongly in the mid-infrared region – a
406
24-25 March 2015
region corresponding to Landsat’s band 7, while green vegetation reflects strongly in
the region corresponding to Landsat’s band 4.
Relationship between world view-2 Sensor’s DN value and soil organic matter
content
Karl Pearson’s correlation coefficient analysis was performed between the seven
independent bands from 2–8 and the soil organic matter content(SOM) as dependent
variable The correlation coefficient was revealed positive low correlation except for
the DN of NIR-1, which may have been influenced by the presence of moisture in
some regions of the study area (Table 2). Soil organic matter (SOM) content was
found significantly correlated only with the DN of Blue Band (r = 0.305) and NIR-2(r
= 0.328) at 0.05 significant level and with Yellow Band at 0.01 significant level(Table
2). Such significant correlation coefficient was investigated after removal of outliers
found in two observations and data transformation did not enhance the correlation
coefficient rather decrease . Thus it is not required because of already having
symmetric distribution of variate as usually being done in skewed distribution.
Table 2: Pearson’s correlation coefficient between soil organic matter (SOM) and
DN value of World View-2 spectral bands
Blue
Green
Yellow
Red
Edge red NIR-1
NIR-2
0.305
0.293
0.461
0.064
0.302
-0.031
0.328
SOM
Multiple regression analysis was performed to test the spatial dependency of soil
organic matter content on DN value of World View-2 sensor. A t-test showed that
regression coefficient of seven bands were found insignificant even though an
ANOVA reported that the model is significant at the 2 percent level indicating that
using the model is better than guessing the mean. As a whole, the regression does a
good job of modeling soil organic matter content (SOM). Nearly forty-five percent the
variation in SOM is explained by the model (R2. = 0.449) .Although multiple
correlation coefficient was found moderate (R=0.67), individual bands as predictors
are suffering from multi-collinearties problem indicated by low value of percentage of
Tolerance and high value of Variance Inflation Factor (VIF) in the regression analysis
(Norusis 1993).Thus, the small tolerances show that more than 70% of the variance in
a DN value of bands can be explained by the other factors as soil moisture, particle size
and iron-oxide. Geometric technique, stepwise multiple regression, orthogonalization
process and principle component analysis (PCA) are various ways of tackling the
problem of multicollinearity (Frisch 1934). Among them, PCA is the most suitable
eliminating all redundant factors and produces an underlying set of orthogonal
variables/dimensions. Principal component analysis is then applied to isolate visible
and NIR dimension of Nayabelhani VDC, because of initial multiple regression
analysis did not produce so satisfactory result. The components extracted by PCA are
then used as a basis of reformulating the previous/initial regression equation to provide
means of predicting magnitude of SOM in Nayabelhani VDC of Nawalparasi district
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24-25 March 2015
Interpretation of Components
Two important components were extracted considering Bartlett's test of Sphericity and
Kaiser-Meyer-Olkin (KMO) to measure of sampling adequacy. Both statistical
measure of sampling adequacy were required in order to assess the factorability of the
data and their respective values: p< 0.05 and 0.86 shows farther than the minimum
level for a factor analysis to be considered appropriate. Table 3 summarizes the
percentage of total variance extracted by the two components. Component I and II
together account for more 90 percent of the total variance and covariance of original
seven bands implying that the variance between the seven bands can be attributed to
two major components. The degree of association between a band and a component is
indicated by the factor loadings as the same meaning of correlation coefficient outlined
in Table3. Principal Component –I, which accounts for 67.77 percent of the total
variance, obviously is the most significant factor. The bands which are significantly
correlated with this component are: Red, Blue, Red Edge and Green (Table 4). These
relationships agree with the high associations found in the correlation analysis. Among
the Visible Bands, it can be observed that Red, Blue, Red Edge and Green are
collinear. Simple correlation coefficients between Band Blue and the three Bands- Red,
Red Edge, Green –respectively are 0.914, 0.986 and 0.973 while that between NIR-1
and the same bands are 0.963, 0.793, and 0.827. It is obvious that Blue and NIR1 are
are collinear. They suggest that component I represents size dimension. The correlation
coefficients between SOM and visible bands (blue, green, red, red edge and yellow)
were higher than that between SOM and NIR bands except NIR-2 of World View-2
imagery in study area. This is consistent with the results of Wu et al. (2009) in case of
relationship between SOM and ETM sensor.
NIR dimension except NIR I is clearly revealed in component II, which accounts for
26.97 per cent of the total variance. The variables that are highly associated with this
component are: NIR2 and Yellow (Table 4). The remaining component has hardly
any significant factor loadings. This component accounts for 5.26 per cent. Perhaps
this might best be designated as a term comprising random covariations. The
significant inverse relationship was found between both of the components and Near
Infrared (NIR) dimension. Similarly insignificant inverse relationship was observed
between SOM and NIR-I. This is not consistent with the other results who reported
there was no absorption apex caused by organic matter in the NIR region (800–2400
nm), and SOM content was better measured with visible bands than NIR bands. It
might be the cause of slight difference of NIR I towards visible wave length (770895nm).
Reformulated Multiple-Regression Analysis for Predicting SOM content
Principal Component Analysis (PCA) indicates that two bands that are orthogonal and
at the same time related to mean SOM content are: Blue and Near infrared II (NIR II).
The former is a member of dimension 1(Visible band) and the latter of dimension
2(NIR). These two bands are now used as surrogates for the two basic dimensions to
reconstruct the initial multiple regression equation.
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24-25 March 2015
Where SOMi is the mean content of Soil Organic Matter (SOM). V is the Blue visible
band; N is NIR 2 the Near infrared band and a, b and c are numerical constant of the
regression equation. In this equation, soil organic matter (SOM) content is said to be a
function of two orthogonal dimensions: Visible and NIR spectral band reflectance. The
resulting least square fit has the form:
A t-test shows that both the regression coefficients for Blue(X1) band and NIR 2(X2)
band are highly significant at the 96 percent and 95 percent confidence level
respectively. The multiple correlation coefficient was found of 0.556 while the
coefficient of determination, R2 was investigated of 0.31 , implying that 31 percent
of the variation in the mean soil organic matter content of Nayabelhani Village
Development Committee of Nawalparasi District, Nepal can be accounted for by the
combination of two bands alone, namely blue visible and NIR 2 near infrared or more
generally, by the two spectral basic dimension- visible and near infrared band.
Table-3: Percentage of total explained variance
Components
Eigen value
% of total explained variance
1
4.74
2
1.88
total
6.62
67.77
26.97
94.74
Table-4: Varimax Rotation of Components
Components
1
Blue
Red
Red_Edge
Green
.980
.964
.955
.940
.004
.193
.125
.314
NIR1
.928
-.081
NIR2
-.134
.965
.422
.893
2
Yellow
Table 5: Analysis of variance for the multiple regression
Source of variation
Sum of Squares df
Mean Square F
Sig.
Due to regression
2.635
2
1.317 4.034
.022
Deviation about
10.776
58
.327
regression
Total
13.411
60
F-ratio of multiple regression coefficients is highly significant and ANOVA, doubtless,
verifies the power of the model which is significant at 0.02 % significant level. A
summary of the analysis of the variance for the multiple regressions is given in
Table 5.
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24-25 March 2015
The magnitude of soil organic matter content can be determined with the just two
explanatory bands: Blue and NIR II even though it was moderate degree of estimation.
The R2 of the reconstructed regression model (R2. = 0.31) is found less as compared to
the original initial R2 (R2. = 0.45) in which seven independent bands were used. The
reformulated multiple regression equation is found more precise in comparison to
previous one. It is because of the multi-colinearity problem that initial regression
equation suffered, has now eliminated, and much simpler, for few bands are used in the
reformulated regression analysis. The highly significant values of regression
coefficients in the new regression equation clearly reflect the estimating power of the
model. This is consistent with the results of several studies made by different scholars
during different time-periods. Wu et al. (2009) reported that the reflectance of visible
wavelengths (0.425–0.695 mm) had a strong correlation with SOM content.
Conclusions
Principal component analysis has thus facilitated the selection of a more effective set
of bands for the prediction of mean SOM content in Nayabelhani VDC of Nawalparasi
District, Nepal. With the elimination of redundancies of a battery of independent bands
among visible and near Infrared two independent components of Blue and NIR 2, it
has provided a sound rationale for reformulation of initial multiple regression equation.
It also noted that there exits inverse relation between both of components with the NIR
bands-NIR-1 and NIR-2. However, the correlation coefficients were only moderate in
this study. This may be attributable to the differences in soil parent material, moisture,
and land use/land cover conditions at the time the World View-2 imagery was
acquired.
Improving soil quality and agricultural production, soil management options should be
developed to enhance SOM content in this area. Predicting and mapping SOM content
based on Remote Sensing Technology used in this study can provide useful
information for improving soil quality and managing nutrient budgets for agricultural
production in the region.
References
Ben-Dor E. 2002. Quantitative remote sensing of soil properties. Advances in
Agronomy. Israel.
Chen Y and T Aviad. 1990. Eff ect of humic substances on plant growth P 161–186.
P. Maccarthy et al. (ed.) Humic substances in soil and cropsciences: Selected
readings. ASA, Madison, WI.
Chen D and W Brutsaert. 1998. Satellite-sensed distribution and spatialpatterns of
vegetation parameters over a tallgrass prairie. J. Atmos. Sci. , 55:1225–1238.
Dehaan RL and GR Taylor. 2002. Field-derived spectra of salinized soils and
vegetation as indicators of irrigation-induced soil salinization. Remote Sensing
of Environment, 80, p 406-417.
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24-25 March 2015
Frisch R. 1934. Statistical Confluence Analysis by means of Complete Regression
Systems. Oslo University, Institute of Economics, Publication No-5.
Gerritse and G Robert. 1988. Role of soil organic matter in the Geochemical cycling of
chloride and bromide. Journal of Hydrology, CSIRO, Wembley, Australia , p 8395.
Norusis and MJ J. 1993. SPSS for Windows TM : Professional StatisticsTM, Release
6+.SPSS Inc. 444 N Michigan Avenue. Chicago, Illinois 60611.
Schulte EE and B Hoskins. 2009. Recommended Soil Testing Procedures for the
Northeastern United States:Cooperative Bulletin No. 493.
Stevenson FJ and X He. 1990. Nitrogen in humic substances as related to soil fertility.
P Maccarthy et al. (eds.) Humic substances in soil and crop sciences: Selected
readings. ASA, Madison, WI. Pp. 91–109.
Stoner ER and MF Baumgardner.1980. Physicochemical, Site, alld Bidirectiollal
Reflectance Factor,Characteristics of Uniformly Moist Soils. LARS Tech. Rep.
111679. Purdue University, West Lafayette, .
Stoner ER and MF Baumgardner.1981. Characteristic variations in reflectance of
surface soils. Soil Sci. Soc. Am. J. 4S: 1161_1165.
Wu Chunfa, J Wu,YLuo, L Zhang, D Stephen and De Gloria. 2009. Spatial Prediction
of Soil Organic Matter ContentUsing Cokriging with Remotely Sensed Data.
Soil Sci. Soc. Am. J. (SSSAJ): 73(4): 1206.
Yadav V and G Malanson. 2007. Progress in soil organic matter research: Litter
decomposition, modeling, monitoring and sequestration. Prog. Phys.Geogr.
31:131–154. Prog. Phys.Geogr , 31:131–154.
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5.
SE-1
Carbon Dioxide Emission from Soil Grown to Wheat Crop at Khumaltar,
Lalitpur
Saraswoti Kandel , Shree C Shah Ananda K Gautam
.
Institute of Agriculture and Animal Sciences, Tribhuvan University, Rampur, Chitwan, Nepal
Abstract
Changes in farming practices could be an effective way to reduce carbon (CO2-C)
emissions from agricultural lands thereby sequestering more carbon in the soil. A field
experiment was conducted on an acidic silt loam upland soil of Khumaltar, Nepal during
the dry season of 2011/2012. The study evaluated soil CO2 - C emission from a wheat
field as influenced by tillage, mulch, and nitrogen (N) application. The factorial
experiment laid-out on a split-split plot design consisted of three replications of 12
treatment combinations, i.e., two types of tillage (zero and conventional) on a main-plot,
two levels of mulch (zero and 4 t ha-1 of rice straw) on a sub-plot and three levels of N
application (zero, 100 and 150 kg ha-1) on a sub-sub plot. The crop growing season in this
region is relatively longer primarily due to the effects of low temperature and high
elevation (1300 masl); therefore, wheat (var. WK-1204) planted on December 6 of 2011
matured in six months (harvest date June 2 of 2012). Wheat was planted @120 kg ha-1 on
plots of 4m x 3m size. Major nutrients, viz., phosphorus and potassium were applied @50
kg ha-1each, and nitrogen was applied as a treatment. The test crop received irrigation at
the crown root initiation stage, maximum tillering stage; and heading stage. A closedchamber (25cm high and 20cm radius) technique was employed to collect CO2 gas
samples inserting the iron channels 3 cm below the soil surface, and used CO2 monitor to
estimate its concentrations (conc.) in the sample. Gas samples were collected from the
chamber for initial 6 minutes at 10 different dates, keeping a constant time interval of 16
days until crop harvest. This interval is generally accepted for a single growing season
measurement where rainfall and other factors, such as residue and soil disturbances, are
minimal. The CO2-C conc. values obtained for each date were converted into the flux of C
emission. Trend lines were then constructed for each factor’s C fluxes separately within
the growing season. The most efficient treatment in terms of C emission reduction was
evaluated by separating C flux values for each date using least square difference (LSD)
significant at 0.05 probability level.
Results showed that within the season variability in the CO2-C emission (mg sq.m. hr-1)
was high in all treatments, as indicated by mean values ranging between 123 and 264 on
tillage plots, 89 and 306 on mulch plots, and 58 and 389 on N plots. ero tillage, no mulch,
and lower rates of N application treatments were in variably superior in terms of reducing
C emission relative to conventional tillage, mulched, and higher rates of N application
treatments. Lower C emission may also imply that part of the applied carbon is
sequestered in the soil and immobilized as microbial tissues. A closer observation of the
trend lines revealed CO2-C emission spikes during the early growing stage and towards the
maturation stage under tillage and mulch treatments. This was likely associated with the
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24-25 March 2015
increased soil wetness due to irrigation and, or rainfall events preceding the CO2 gas
sampling. The rates of N application from zero to 150 kg ha-1 in this study consistently
maintained higher C emissions (p = 0.01) through all data collection dates until crop
harvest, differing from the highest CO2-C emission seen in the early stage of treatment
application observed by several incubation and field studies. In this short-term study,
results were encouraging in terms of keeping the C emission lower, such as zero tillage, no
mulch and lower N rate treatments; but some results still appeared inconsistent and
complex. Therefore, extensive field experimentation of carbon decomposition is warranted
to develop a better understanding of carbon dynamics in soil and in the environment.
Keywords: Carbon dynamics,CO2 emission, mulching, zero tillage.
Introduction
Global warming has led to a significant interest in sequestration of atmospheric carbondioxide (CO2) in terrestrial ecosystems (Spargo et al. 2008). Land use and land cover
changes and agricultural practices contribute about 20% of the global annual emission
of CO2 (IPCC 2001).There is a strong synergism between crop residue management
and no-till farming. Another route by which elevated CO2 may impact on soil
biological processes is by intensifying competition between soil microbes and plants
for N (Bardgett, 2005). Resource Conservation Technologies such as zero tillage,
residue management and appropriate use of nutrients have shown potential to improve
productivity of wheat as well.The resources conservation technologies help in
improving soil properties, nutrient use efficiency and reduce environmental pollution
(Halvorson et al. 2002, Lal 2008). Because of the high rate of CO2-C emission from
the land surface we need to develop agricultural technologies that minimizes the CO2C emission. Tillage practices, residue management and application of fertilizer
nutrients to a minimum and properly can play a vital role to minimize the CO2-C
emission in our condition. The objective of this study was to evaluate the effects of
cultivation practices, residue management and higher use efficiency of plant nutrients
appliedin a minimal level to the crop plants so that CO2-C emission can be minimized.
The factorial experiment laid-out on a split-split plot design consisted of three
replications of 12 treatment combinations, i.e., two types of tillage (zero and
conventional) on a mainplot, two levels of mulch (zero and 4 t ha-1 of rice straw) on a
sub-plot and three levels of N application (zero, 100 and 150 kg ha-1 ) on a sub-sub
plot. The experiment was conducted in the farmland of NARC, Khumaltar.Wheat was
planted @120 kg ha-1 on plots of 4m x 3m size. Major nutrients, viz., phosphorus and
potassium were applied @50 kg ha-1each, and nitrogen was applied as a treatment.
Crop received irrigation at the crown root initiation stage, maximum tillering stage;
and heading stage. Collection of gas samples was carried out by closed chamber
techniques. The iron rings were inserted 3 cm inside the soil. A 3- way stop cork and
air tight toddler bags were fixed in the cover of chamber to collect gas sample. The
chamber was thoroughly flushed several times with a 50 ml syringe. Gas samples were
drawn with the help of syringe. Head space volume inside the chamber was recorded,
which was used to calculate CO2 flux. Gas samples at 0 and 6 minute time were
413
24-25 March 2015
collected from the chamber at 10 different dates from all the twelve treatments of three
replications at 16 days intervals. Carbon dioxide concentration in the gas samples
collected from the field was estimated or analyzed by carbon dioxide (CO2) monitor
(AEU 2010).
Result and Discussion
Influence of tillage management on soil CO2-C emission
Tillage is among the most important primary sources of CO2 emission. The zero-tillage
practice had lower soil CO2-C emissions than conventional tillage (Figure 4). The
effect of tillage on soil CO2-C emissions from wheat field is presented in Table 3. A
comparison between zero and conventional tillage at different dates showed that, the
lowest CO2-C emission from zero-tillage was 45.27 mg/m2/hr at 64 DAS. The lowest
CO2-C emission might be due to the reduced exposure of soil in no tillage. The highest
CO2-Cemission from conventional tillage was 300.16 mg/m2/hr at 144 DAS. Lal
(2008) reported that excessive tillage practices disturbed soil and caused rapid
oxidation of soil organic matter, thereby increased flux of C to the atmosphere.
Influence of mulch management on soil CO2-C emissions
There was a significant effect of mulch on soil CO2-C emissions at 48 DAS, 64 DAS
and 144 DAS but its effect was nonsignificant for rest of the periods.
350
Tilled
Untilled
300
CO2 (mgCm-2hr-1)
250
200
150
100
50
0
16
32
48
64
80
96
112
128
144 at harvest
Days after seeding
Figure 1: Effects of tillage management on soil CO2-C emissions from wheat field at
Khumaltar, Lalitpur, Nepal, 2011/2012.
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24-25 March 2015
Table 3: Effects of tillage on soil CO2-C emissions from wheat field at Khumaltar,
Lalitpur, Nepal, 2011/2012.
CO2-C (mg/m2/hr)
Days After Seeding
16
32
48
64
80
96
112
128
144
At
harve
st
CT
136.61
207.05
129.94
156.16a
185.55
147.50
129.83
168.11
300.16a
206.3
3
ZT
132.94
154.72
125.83
45.27b
157.83
127.22
122.61
166.66
264.05b
173.8
3
SEm
6.6105
31.8229
12.7857
1.7378
10.9359
17.6389
12.7476
19.3523
1.0460
28.90
81
LSD
ns
ns
ns
5.21
ns
ns
ns
ns
6.365*
ns
CV,%
12.31
19.97
13.75
9.51
24.65
13.32
15.20
24.14
8.56
11.42
TN
Tillage
Means followed by the same letter(s) in a column are not significantly different at 5% level of
significance as determined by DMRT.
Without mulch
350
CO2 (mgCm-2hr-1)
300
250
200
150
100
50
0
16
32
48
64
80
96
112
128
144
at
harvest
Days after seeding
Figure 5: Effects of mulch management on soil CO2-C emissions from wheat field at
Khumaltar, Lalitpur, Nepal, 2011/2012.
A higher soil CO2-C emission was noted from the treatment in which rice straw was
applied @ 4 t ha-1 than from the field without rice straw mulch. This might be due to
decomposition of rice straw mulch that caused higher CO2 emission. As organic matter
decays, CO2 is among the immediate breakdown products. The mulched soils had
significantly higher amount of CO2-C emissions (112.16 mg/m2/hr) than no mulch soil
(89.27 mg/m2/hr) at 48 DAS. Similar result was also found at 44 DAS and 144 DAS.
The significant higher soil CO2-C emissions at 48 DAS, 64 DAS and 144 DAS from
mulched soil might be due to higher oxidation of mulch derived carbon from tillage
soils. As the tillage intensity increases, soil contact of crop residue is increased and
incorporated residues are placed into more moist condition than those left on the soil
surface (Halvorson et al. 2002).
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24-25 March 2015
Influence of nitrogen management on soil CO2-C emissions
Nitrogen fertilizer has major influence on soil CO2-C emissions. The amount of the
nitrogen fertilizer applied to the field determines the soil CO2-C emissions from the
soil.
450
N0
N100
64
80
N150
CO2(mgCm-2hr-1)
400
350
300
250
200
150
100
50
0
16
32
48
96
112
Days after seeding
128
144
at
harvest
Figure 3: Effects of nitrogen management on soil CO2-C emissions from wheat field at
Khumaltar, Lalitpur, Nepal (2011/2012).
Higher the amount of nitrogen fertilizer applied in the field more soil CO2-C emissions
was found during the experiment. This might be due to the application of higher
amount of nitrogen enhanced more soil carbon mineralization caused more CO2-C
emission from soil. Korschens (1998) reported that mineral fertilization increased
carbon by only 0.1% but mineralizable carbon was 21 to 49% of total carbon.
significance as determined by DMRT
N0= No nitrogen, N100= 100 kgNha-1, N150= 150 kgNha-1
Tillage and mulch interaction effects on soil CO2-C emissions
There were no significant effects of tillage and mulch interactions at all dates but
significant variations in soil CO2-C emissions were found at 16 DAS, 64 DAS, 96 DAS
and 144 DAS.
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24-25 March 2015
Table 4: Effects of mulch on soil CO2-C emissions from wheat field at Khumaltar,
Lalitpur, Nepal, 2011/2012.
TN
Mul
ch
M0
Mw
SEm
LSD
CV,
%,
16
32
48
64
134.89
134.67
7.8589
ns
12.31
179.33
182.44
9.8179
ns
19.97
106.27b
149.50a
7.4314
39.15*
13.75
89.27b
112.16a
1.9618
5.882*
9.51
CO2-C (mg/m2/hr)
Days After Seeding
80
96
157.33
186.05
9.0029
ns
24.65
129.16
145.55
4.2852
ns
13.32
112
128
144
At harvest
116.22
136.22
5.2760
ns
15.20
149.55
185.22
26.4159
ns
24.14
258.38b
305.83a
1.8663
7.328*
8.56
187.05
193.11
13.4839
ns
11.42
Table 5: Effects of nitrogen on soil CO2-C emissions from wheat field at Khumaltar,
Lalitpur, Nepal (2011/2012).
CO2-C (mg/m2/hr)
Days After Seeding
Treatm
ents
Nitrog
en
N0
16
32
48
64
80
96
112
128
144
At harvest
101.25c
128.58c
91.083c
57.91c
121.91c
103.16c
96.00c
120.50c
194.33c
145.91c
N100
138.00b
176.33b
121.16b
92.91b
171.50b
138.16b
129.41b
166.08b
262.58b
184.83b
N150
a
a
a
a
a
a
a
a
239.50a
SEm
165.08
237.75
171.41
a
151.33
221.66
170.75
153.25
215.58
389.41
4.7898
10.4285
5.0744
2.7649
12.2153
5.2835
5.5403
11.6634
2.7263
6.2670
LSD
14.36**
31.26**
15.21**
36.62**
15.84**
16.61**
34.97**
20.90**
18.79**
CV,%
12.31
19.97
13.75
8.289*
*
9.51
24.65
13.32
15.20
24.14
8.56
11.42
Tillage and nitrogen interaction effects on soil CO2-C emissions
The effects of tillage and nitrogen interaction are given in Table 7. The interaction
effects of tillage and nitrogen management were significant at 64 DAS, 144 DAS and
at harvest.
Mulch and nitrogen interaction effects on soil CO2-C emissions
The interaction effect of mulch and nitrogen management was significant at 64 DAS,
144 DAS and at harvest.
Tillage, mulch and nitrogen interaction effects on soil CO2-C emissions
Variation in the soil CO2 flux can result from the interaction of many factors. There
were significant effects of tillage, mulch and nitrogen interactions on soil CO2-C
emissions at 64 DAS, 144 DAS and at harvest but at rest of seven different dates it was
not significant.
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24-25 March 2015
Table 6: Interaction effects of tillage and mulch on soil CO2-C emissions from wheat
field at Khumaltar, Lalitpur, Nepal (2011/2012).
CO2-C (mg/m2/hr)
Days After Seeding
16
CT
ZT
SEm
LSD
CV,
%
M0
153.88a
115.89b
64
Mw
119.33b
150.00a
96
M0
138.44b
40.11d
5.531
16.58*
12.31
Mw
173.88a
50.44c
2.774
8.318*
9.51
144
M0
152.33a
106.00b
Mw
142.66a
148.44a
6.060
23.80*
13.32
M0
311.88a
204.88c
Mw
288.44b
323.22a
5.049
19.83**
8.56
CT= Conventional tillage, ZT= Zero tillage
M0= Without mulch, Mw= With mulch
Table 7: Interaction effects of tillage and nitrogen on soil CO2-C emissions from
wheat field at Khumaltar, Lalitpur, Nepal(2011/2012).
CO2-C (mg sq.mhr-1)
Days After Seeding
64
CT
ZT
SEm
LSD
144
At harvest
N0
N100
N150
N0
N100
N150
N0
N100
N150
93.83c
22.00f
3.910
11.72**
9.51
139.83b
46.00e
234.83a
67.83d
173.83e
214.83d
9.861
29.56**
8.56
266.50c
258.66c
460.16a
318.66b
175.50c
116.33d
8.863
26.57*
11.42
203.00b
166.66c
240.50a
238.50a
CV
(%)
CT= Conventional tillage, ZT= Zero tillage
N0= No nitrogen, N100= 100 kg N ha-1, N150= 150 kg N ha-1
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24-25 March 2015
Table 8:Interaction effects of mulch and nitrogen on soil CO2-C emissions from wheat
field at Khumaltar, Lalitpur, Nepal (2011/2012).
CO2-C (mg sq.mhr-1)
M0
Days After Seeding
64
N0
N100
52.50e
86.33d
Mw
63.33e
SEm
3.91
11.72**
9.51
LSD
99.50c
N150
129.00b
144
N0
149.00d
N100
223.50c
N150
402.66a
At harvest
N0
163.00c
173.66a
239.66c
301.66b
376.16a
128.83d
9.86
29.56**
8.56
N100
182.8
3c
186.8
3c
N150
215.33b
263.66a
8.86
26.57**
11.42
CV %
M0= Without mulch, Mw= With mulch
N0= No nitrogen, N100= 100 kg N ha-1, N150= 150 kg Nha-1
Table 9:Interaction effects of tillage, mulch and nitrogen on soil CO2-C emissions of
wheat field at Khumaltar, Lalitpur, Nepal (2011/2012).
CO2 – C (mg sq.mhr-1)
Nitrogen management
Days After Seeding
64
Tillage
Mulch
144
N0
N100
88.00de
99.66d
17.00j
27.00ij
133.33c
146.33c
39.33hi
52.66gh
N150
N0
At harvest
N100
N150
N0
194.00b 148.00f 249.33d 538.33a 192.00cd
275.66a 199.66e 283.66cd 382.00b 159.00de
ZT
64.00fg 150.00f 197.66e 267.00d 134.00ef
71.66ef 279.66cd 319.66c 370.33b 98.66f
SEM
5.53
13.95
LSD
16.58**
41.81**
CV, %
9.51
8.56
Means followed by the same letter(s) in a column are not significantly different at 5%
CT
M0
Mw
M0
Mw
N100
N150
221.00bc
185.00cd
144.66e
188.66cd
238.00b
243.00b
192.66cd
284.33a
12.53
37.58**
11.42
level of significance as determined by DMRT.
Conclusion
The results were encouraging in terms of keeping the C emission lower at zero tillage,
no mulch and lower N rate treatments. The rates of N application from zero to 150 kg
ha -1 in this study significantly maintained higher C emissions (p = 0.01) through all
data collection dates until crop harvest. The ability of soils to sequester C in a high
CO2 world is likely to be increased substantially by reducing decomposition of soil
organic matter and the activities of invasive species. Thus, proper agricultural
technologies provide a window of opportunity for reduction of CO2 emission from our
soils.
419
24-25 March 2015
References
AEU. 2010. Annual Report. Agricultural Environmental Unit (NARC), Khumaltar,
Lalitpur, Nepal. Pp. 1-24.
Bardgett R. 2005. The biology of soil. Oxford University Press, New York. 242 p.
Halvorson AD, B J Wienhold and AL Black. 2002. Tillage, nitrogen and cropping
system effects on soil carbon sequestration. Soil Sci. Soc. Amer.J.66: 906-912.
IPCC.2001.Climate Change.The Scientific Basis. Intergovernmental Panel on Climate
Change Cambridge University Press, NY.
Korschens M. 1998. Effect of different management systems on carbon and nitrogen
dynamics of various soils. R Lal, JM Kimble, RF Follett and BA Stewart
(eds.). Management of carbon sequestration in soil.CRC Press.US. Pp. 297304.
Lal R. 2008. Carbon management in agricultural soils.Mitigation Adop.Strategies
global change. 12: 303-322.
Spargo JT, M M Alley, R F Follett and J V Wallace. 2008. Soil carbon sequestration
with continuous no-till management of grain cropping systems in the Virginia
coastal plain. Soil Till. Res. 100: 133-140.
420
24-25 March 2015
6.
RCT-1
Enhancing Soil Fertility and Crop Production Through Promoting
Conservation Agriculture Production Systems (CAPS) in the Mid Hills of
Western Nepal
Bir B Tamang1, Keshab Thapa1, Roshan Pudasaini1, Bikash Paudel2, Susan Crow2,
Jacklene Halbrendt2,Ted Radovich2 and Catherine Chan2
1
2
Local Initiative for Biodiversity, Research and Development (LI-BIRD), Nepal
Department of Natural Resources and Environmental Management, University of Hawaii, USA
Abstract
Conservation tillage improves the soil physical, chemical and biological properties to
make the soil nutrients easily available to the crops. Therefore, it is a viable solution for
challenges faced by farmers in arid and semi-arid zones and who are dependent in sloping
land agriculture. Chepang tribal communities in the Dhading, Gorkha and Tanahun
districts of Nepal face excessive soil and nutrient loss, structural degradation, and
consequent production loss in the maize based farming system. Research was conducted to
test three conservation agriculture production systems in three villages viz. Hyakrang of
Dhading district, Thumka of Gorkha district, and Kholagaun of Tanahun district to
understand the implications of the production systems on soil quality as well as crop
production on the sloping agricultural land. A set of experiments included two seasons i.e.
maize grown under conventional tillage(CT) and strip tillage(ST) in the first season,
followed by legume and finger millet in the form of Conservation Agriculture Production
System (CAPS) in second season. The composition of the three CAPS were: i) legume in
CT (CAPS1) ii) legume mixed with finger millet in CT(CAPS2),and iii) legume and millet
in strip tillage (CAPS3). The control was conventional tillage (CT) with maize millet
rotation. The three years experiment in CAPS showed that the leguminous crop CAPS1
and CAPS3 improved soil pH, organic matter, nitrogen content, bulk density, and water
stable aggregates as compared to the control. In CAPS3, the soil nitrogen content
increased by 0.10 to 0.18% at the 0-5 cm depth and by 0.09 to 0.14% at the 5-10 cm depth
over the periods. Water stable aggregate stability of the soil was also changed by 20%
however there is no any significant change in water stable aggregate due to high
variability. Tillage did not have significant effect on yields of maize, millet and legumes.
other
Yet, maize yield from the CAPS1 (2194 kg ha-1) was significantly higher than all
treatments. The results provide evidence for improving soil fertility and productivity
through conservation agricultural production systems focused on minimum tillage and
legumes integration in the maize based farming system in mid hill of Nepal.
Keywords: Conservation agriculture, nitrogen, slopping land, soil properties,
strip.Tillage.
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24-25 March 2015
Introduction
More than 50 percent farmers in Nepal are smallholders who have less than 0.5 ha
landholding. Large population the Nation depends on slopping land agriculture in midhill region. Such rain-fed terrace agriculture lands are characterized by excessive
drainage, shallow soil depth, moisture deficit and acidic reactions. Maize and millet
grown during the summer season in the mid hill region is prone to soil erosion, which
is a serious problem through time. Due to excessive soil loss, plant nutrients are lost,
soil structure deteriorates and the production capacity of the soil is reduced (Troeh et
al. 1980). The annual loss of soil from agricultural land ranges from a mere 0.1 t ha-1
level to a very high of 105 t ha-1 in Nepal (Chalise and Khanal 1997). The soil loss
from surface soil from agriculture land is highly related to slope gradient in the hills
(Shrestha et al. 2004).Such continuous soil loss is adversely affecting crop productivity
as well as the environment specifically the quality of downstream water resources in
the mid-hills of Nepal (Atreya et al.2005 and Tripathi et al. 1999). Agriculture land in
mid hills of Nepal is highly exploited with intensive cultivation of crops with
conventional tillage practices.
Nepalese rural farmers have little awareness of crop rotation, tillage and nutrient
management systems to match the soil type for long-term sustainability. They follow
the cropping system which is mostly baled on sole cropping with limited integration of
legume crops. Reducing soil loss from sloppy mid hills needs to be one of the top
priorities of Nepalese agriculture. Because the declining situation of agriculture land in
the mid hill makes it clear that current farming practices are inadequate to sustain these
agricultural systems. Declined soil fertility status of maize growing areas in the mid hills
is one of the major constraints for increased productivity and sustainability.
Conservation agriculture (CA) technologies are the suggested methods to address the
problem of soil degradation in slopping agriculture lands. CA technology offers
optimal growth conditions to crops for increased yield along with a balance between
long term agricultural, economic and environmental benefits (Lal 1983). The concept
suggests that the combined environmental and economic benefits gained from reduced
input, soil erosion and optimal cropping pattern are more sustainable than current
production practices. CA follows three principles viz. no or minimum tillage, cover
crops and crop rotation. Crop which have greatest potential to protect and enhance soil
and yield productivity in the mid-hills of Nepal. Conservation or minimum tillage
enhances crop production by decreasing soil bulk density, increasing infiltration,
decreasing surface runoff and conserving soil moisture (Licht and Al-Kaisi 2005). The
second and third components of CA are intercropping and optimal crop rotation.
Compared to conventional agriculture, CA offers the potential to increase crop
productivity (Sayre 2010), reduce production costs, increase soil organic carbon (Lal et
al. 2010) and decrease soil salinity in the long run. At the same time, in spite of the
lower yield performance initially due to reduced tillage methods, they are essential to
reduce soil erosion on highly erodible, sloping silt-loam soils like the mid-hills of
Nepal (Howard 1998).
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24-25 March 2015
Conservation Agriculture Production System (CAPS) supports CA. CAPS is supposed
to help smallholder marginal farmers sustainably by to addressing the soil fertility
depletion from their land. Following CAPS, farmers can use various options like crop
relay farming, crops rotation, mulching, dibbling practices etc. to get greater benefit
from the cultivated land. Integration of legume crops like rice bean, cowpea, soybean
in mid-hill terrace farming which has maize-millet based cropping system.
Chepang are marginalized people who cultivate on marginal land especially following
shifting cultivation in sloping and steep land in the mid hills of central and western
Nepal (Regmi et al.2004). The main territory of Chepang lies along the Mahavarat
range from south of Trisuli river, North and west of Rapti river and east of Narayani
river one of the indigenous nationality of Nepal (Maharjan et al. 2010). They have their
own traditional system of farming and followed the traditional farming system from the
very beginning. They have followed the conservation system on their own which are
more traditional and less effective to the modern farming system. They are less
influenced by the government activities and other non government agencies due to
inaccessible places. Often they are living in sloping land nearby forest and they are
more close to the nature.
By this study we have tried to assess the effectiveness of various CAPS combinations
against traditional way of cultivation practice in terms of soil fertility and crop
production. Conventional tillage and strip tillage as well as legume crops as relay crop
in maize-millet cropping system are the main comparisons. The research has been
believed to contribute to enhance the soil health and efficiency of agro-economic status
of smallholder farmers in mid hills of Nepal through the application of conservation
agriculture production system.
The study was conducted in three villages of Chepang community viz. Thumka in
Gorkha, Hykrang in Dhading and Kholagaun in Tanahun. These three sites were
purposively selected on the basis of conservation agriculture production system in
Chepang tribal community with sloping terraces land. All three sites were located on
same agro ecological zone and the altitude was rangedfrom 600-800 meter above the
sea level. In Thumka of Gorkha site was dominated by red soil and other two sites
were found grayish brown soil with sandy loam. Thumka and Kholagaun were located
in the southern aspect and Hykrang of Dhading was faced to the northern aspect. The
average rainfall was ranged from 1200 to 2000 mm per year in the study sites.
Trial was designed on RCBD method with four treatments including control in each
plot. In each plot the number of farmer’s field was replication of the trial and there
were eight farmers selected for the trial in each site. The area of a treatment was 20
square meters with 50 cm gap in between the treatment plots. The treatments in the
study were as follows:
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24-25 March 2015
Table 1: Treatment allocation in the experiment.
Treatments
Tillage
1st crops
system
T1
(Farmers
practice: CT
Maize
Control)
CT
Maize
T2 (CAPS 1)
CT
Maize
T3 (CAPS 2)
Strip
Maize
T4 (CAPS 3)
tillage
2nd crops
Millet
Black gram
Millet mixed black gram
Millet and black gram
T= treatment, CT = conventional tillage, CAPS = conservation agriculture production system
During the crop plantation the farm yard manure(FYM) was applied according to
farmer’s practice in all treatment. There was no any application of synthetic
manure/fertilizer in the treatments.
Soil sample collection and analysis
In total 192 soil samples were collected for analysis of soil properties each year for
three years. 64 soil samples were collected from each study sites from fallow land after
designing treatment plots. SoilpH, organic matter, nitrogen, available potassium,
available phosphorus, texture, bulk density, and water stable aggregate wereanalyzed.
Water Stable Aggregate (WSA) was analyzed by using 250um and 53um size of sieves
mesh by washing with water and dispersion solution. The final result shows total
percentage of water stable aggregate.The data obtained in the study were analyzed
using MSTAT, Excel and Duncan Multiple Range Test as a measurement of inferential
statistical for data analysis.
The overall result of soil analysis data was compiled and analyzed over three years. No
significant difference was found innutrient retention among the treatments in short run
or within one year. However, the result shows that there is significance difference in
soil potassium content in second year as well as total soil nitrogen in thethird year
(Table 2).
Soil parameters
Organic matter content in the soil was found to be increased by adopting CAPS but the
result was not significantly different. Similarly in case of pH, it has been increased in
the II year butdecreased in the IIIyear. Bulk density of the soil has also been decreased
from Y1 to Y3 at higher degree in case of CAPS as compared to the traditional
practice, though variation is not significantly different (Table 3)
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24-25 March 2015
Table 2: Change in Nitrogen, phosphorus, potassium content in soil over three years.
Treatment
Nitrogen, %
Y1
Phosphorus, ppm
Y2
Y3
Y1
75.3
72.97
45.43
75.7
73.62
46.86
0.091
0.169
0.182
T2
0.113
0.186
0.188b
0.156
0.157
c
a
0.113
Potassium,ppm
Y3
b
T1
T3
Y2
77.4
68.59
40.39
Y1
Y2
Y3
73.6
70.3
b
73.29
79.5
77.8a
91.16
92.5
56.9
c
66.25
b
82.29
T4
0.100
0.163
0.234
71.8
84.56
47.81
78.4
71.9
±SEM
0.011
0.012
0.017
4.18
5.23
11.72
9.14
4.09
9.01
LSD
NS
NS
0.049**
NS
NS
NS
NS
NS
CV,%
15.3
10.3
23
36.2
33.8
56.6
64.4
12.0*
*
24.6
35.1
Table 3: Change in soil Organic matter, pH and bulk density in soil over three years.
Treatment
Organic Matter, %
Bulk density gcc -
pH(1:2.5)
1
Y1
Y2
Y3
Y1
Y2
Y3
Y1
Y3
T1
2.69
3.12
2.76
6.21
6.47
6.08
0.801
0.72
T2
2.82
3.32
2.81
6.26
6.32
6.03
0.784
0.59
T3
T4
2.73
2.64
2.99
3.27
2.45
2.83
6.39
6.33
6.29
6.48
6.09
6.18
0.846
0.815
0.69
0.61
±SEM
0.122
0.147
0.171
0.071
0.104
0.057
0.048
0.033
LSD
NS
NS
NS
NS
NS
NS
NS
NS
CV,%
23.2
14
19
4.00
5.6
6.65
14.7
10.6
Especially in case of pH, the data was recorded from two different soil depths viz. 05cm and 5-10cm in each trial. In both of the soil depth, pH was found to be increased
in higher degree as compared to other tillage systems (Figure 1).
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24-25 March 2015
pH(0-5cm)
pH(5-10cm)
6.52
6.55
6.50
6.50
6.48
6.45
pH(2:2.5)
6.46
pH(1:2.5)
T1
6.40
6.44
T1
6.42
T2
T3
6.40
T3
T4
6.38
T4
T2
6.35
6.30
6.25
6.36
6.20
6.34
2012
2013
2012
2014
2013
2014
Figure 1: Soil pH values in different treatments within three years in two soil depths.
Soil organic matter is more important parameters of soil health and it has dynamic
properties to conserve the living soil. It affects the various properties of soil positively
such as water holding capacity, soil porosity, cation exchange capacity, soil pH and
nutrient availability in soil. Soil organic matter was also increased over the year in strip
tillage and transferred from the lower level of organic matter to medium and high
level.Similarly soil nitrogen is more correlated with soil organic matter (Figure 2).
Organic matter
Nitrogen
Organic matter
Nitrogen
Figure 2: Organic matter and nitrogen content in two different layer of soil changed
year by year
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24-25 March 2015
In conservation agriculture farming, physical properties of soil were enhanced due to
minimum disturbance of soil and accumulation of carbon and moisture content. The
moisture content was increased along with soil compactness viz. soil bulk density
which plays the important role to plant growth. The result showed soil bulk density
also decreased in strip tillage in 0-5cm depth and5-10cm soil depth in third
year.Analysis of water stable aggregate(WSA)was done in the soil samples form depth
of 0-5cm and 5-10cm for all the treatments. Figure 3 shows that the WSA was highly
changed in increasing trend on basis first year. Both in 0-5cm and 5-10cm depth the
increasing trend of water stable aggregate over the year in all trial plots has been
clearly seen. However the improvement in WSA of soil is in higher rate in case of
CAPS (T2, T3 and T4) as compared to conventional practice (T1) (Figure 3).
Water stable aggregate (5-10cm)
75
Water stable aggregate (0-5cm)
65
% WSA
55
% WSA
75
70
65
60
55
50
45
40
35
30
25
20
T1
T2
T3
T4
T1
T2
T3
T4
45
35
25
2012
Year
2012
2014
Year
2014
Figure 3: Water stable aggregate analysis over the year 2012 and 2014.
Crop Yield
The result of crop yield for different treatments is shown in the following table (Table
4). The treatments CAPS1 and CAPS3 were higher in terms of yieldduring 2nd and 3rd
years. Overall maize equivalent yield was higher in CAPS 3 (T4) in the 3rd year.
Table 4: Result of crop yield on different treatments by years.
Year
2012
2013
2014
CAPS
treatment(n=24)
Traditional(T1)
CAPS1(T2)
CAPS2(T3)
CAPS3 (T4)
Traditional (T1)
CAPS1(T2)
CAPS2(T3)
CAPS3(T4)
Traditional(T1)
CAPS1(T2)
CAPS2(T3)
CAPS3(T4)
Maize
(t ha-1)
1.77±0.12b
2.07±0.17a
1.90±0.13ab
1.69±0.14b
1.95±0.11b
2.12±0.11a
1.75±0.13b
1.80±0.14b
1.74±0.10c
2.15±0.13a
1.93±0.11b
2.06±0.09ab
Millet
(t ha-1)
0.86±0.10a
0.66±0.09b
0.67±0.10b
1.02±0.10a
0.62±0.08b
0.57±0.07b
1.19±0.10a
0.72±0.07a
0.83±0.07b
427
Black gram
(t ha-1)
0.34±0.04a
0.12±0.03b
0.17±0.02b
0.44±0.04a
0.34±0.03b
0.31±0.02b
0.75±0.09a
0.45±0.06b
0.51±0.06b
Maize equivalent
yield ((t ha-1)
2.45±0.17b
2.83±0.1ab
2.88±0.18a
2.60±0.21a
2.84±0.11b
3.13±0.17a
3.09±0.14ab
3.02±0.16ab
2.75±0.16b
3.88±0.23a
3.59±0.16a
3.93±0.15a
24-25 March 2015
Conservation agriculture production system is a sustainable practice in sloping terraces
land with different tillage system and leguminous crop intervention. The results from
the experiment reveal that it does not show a huge difference in the
beginning.Howeverthe effect of adopting CAPS (stripe tillage and legume integration)
is seen with years of implementation. In the case of nitrogen content in soil, the
significant increment in third years of implementationhas been found. The result is
supported by Lopez-Fando and Pardo (2009), Khan et al. (2010) and Wienhold and
Halvorson (1998). This is mainly due to increase in organic matter, as well as legume
crop integration in the cropping system. Generally small holder farmers in the mid hills
of Nepal use leaf litter and farm yard manure for improving soil fertility. They don’t
use synthetic fertilizer for their field due to inaccessible and paying for high price.
Research suggested that the use of organic manure is inevitable for sustained
agricultural production by reducing dependence on inorganic fertilizers and to build the
soil fertility and improve the soil biological activity(Vijaymahantesh et al.2013).
Along with the availability of organic matter in the soil can improve the soilpH
towards the neutralization within the treatments but there is less improvement in pH
over the each year due to increase in organic matter and low leaching with minimum
tillage. But pH showed the increasing trend in each year on both conventional and strip
tillage. The tillage system plays the importance role in conserving soil moisture and its
subsequent beneficial effect on crop productivity has long been recognized. Dograet
al.2002 reported that the adequate tillage operations controlled weeds and resulted
higher crop productivity, but caused more soil loss and were more capital intensive.
Soil nitrogen is key to crop performance. The two parameters,soil organic matter and
soil total nitrogen, have been found positively correlated throughout the years. The soil
analysis report shows low level of total nitrogen ranges from 0.08% to 0.18% in the
soil (Figure 2). Soil organic matter has also been increased in second and third years as
compared to first year and relatively higher in CAPS adopted conditions. Nitrogen
content also positively increases in both depths (0-5cm and 5-10cm) each year in strip
tillage as compared to first year.
Bulk density is the major component of soil that shows the compaction of soil that is
measured by bulk density. Bulk density does not vary with other soil properties
because it is measured on dry soil basis. Bulk density mainly relates with pore size
distribution that plays the important role in water holding capacity and aeration in the
soil. Bulk density of soil is also decreased over the year due to influence of organic
matter and tillage system. The lower soil bulk density produced by higher level
ploughing could be attributed to the loosening effects of tillage (Lal 1997 and
Hulugalle et al.1985). Regmi et al. 2004 also supported the management of bulk
density with presenceof organicmatter and soil tillage practices.Increase in bulk density
limits the root penetration in soil and decline the root development. Bulk density
declines gradually in the soil with added organic matter each year as well as reduced
tillage. Soil structure is an importance feature of the soil which is defined as the mutual
arrangement of primary mineral and organic particles into larger formation of various
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24-25 March 2015
sizes and shapes.The increase in water stable aggregate improve more water space or
porous in soil. Consequently the increasing trendin WSA due to CAPS has been shown
by the experiment which means CAPS has positive effect on soil structure of continued
over years.
Overall crop performance has been found superior in the case of CAPS 3 (strip tillage
along with legume integration mixed with millet) followed by CAPS 1 (Conventional
tillage along with legume integration replacing millet). The production in these case
was supported by improved soil nutrient supply especially N by legume crop. Strip
tillage helped the soil to retain soil nutrients and moisture consequently helping crop
production (Paudel et al. 2014).
Conclusion
Overall findings of the experiment suggested that, among the four different
combinations of tillage and crop rotation, stripe tillage along with legume integration
as the most effective system in regards to the soil physical properties, nutrient holding
and crop production. The stripe tillage helps to trap water in the soil by providing
shade, which reduces water evaporation. It also helps to slow runoff and increases the
opportunity for water to soak into the soil. Similarly once adopted, stripe tillage, will
increase soil particle aggregation making it easier for plants to establish roots which is
directly related with the plant growth and development. All of these ultimately help to
sustainably increase crop production. Effect of tillage and crop combination as various
treatments was varied year to year. Mostly, the effect of CAPS found positively
changed over the years. Therefore, after this experiment, it has been revealed that such
experiments requires at least few years of study to see the real effect of conservation
agriculture practices, for example reduced tillage.
Resource poor farming households from the hill area of Nepal, who follow slopping
land agriculture and have restricted access to chemical fertilizer can adopt stripe tillage
together with legume as relay crop with maize/millet to increase crop return and make
the system sustainable for the long term. In the sloping hills of Nepal, where maize is
cultivated as the main crop, this technology could help to sustain production by
restricting soil degradation, which is perhaps the most serious threat to the agriculture
system as a whole. Additional research and on farm demonstrations should be pursued
in order to encourage regional farmers to take benefit from these new ideas.
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RCT-2
Tillage Affects the Soil Properties and Crop Yields
Tika Karki1 and Jiban Shrestha2
1
National Maize Research Program (NARC), Rampur, Chitwan
2
Abstract
With the aim of consolidating the information of soil tillage and its effect on soil
properties and crop yields, a brief review of the works being done within and
outside the country was carried out. The review revealed that conventional
agriculture system with intensive tillage practices deteriorated the soil quality and
affected the crop yields. Tillage decreased the soil organic carbon, the crucial
store house of soil-plant system and the major nutrient nitrogen over longer run.
Conservation tillage (CT) also called the minimum or no tillage where soil is
covered with crop residue, significantly improved the physical, chemical and
biological properties of soil. CT increased the soil aggregates of more than 2 mm
by 134%, increased water availability by 36-45 %, and porosity. Similarly, higher
thermal conductivity in CT soils produced the lower increase in soil temperature
in the upper soil profile. In CT, soil pH was higher in surface but lower in sub
surface. CT had higher organic matter along with the increased amount of
mineralizable organic forms of plant nutrients and microbial activities. CT
increased the soil N (24%) and P over conventional tillage in 9 years period and
also increased their availability at soil depth of 5 cm. Several studies revealed that
soil flora and fauna are more abundant under CT than conventional tillage. Soil
microbes play an integral role in nutrient cycling, soil stabilization, and organic
matter decomposition. Despite having some of the contracdictory results, many
workers reported firmly that CT improves soil moisture, regulates soil temperature
and minimize weed pressure, increases organic matter and hence crops yield.
Therefore, in Nepal studies are to be convergent towards the generation,
verification, and scaling up of conservation tillage based technologies for various
agro-ecologies and cropping systems.
Keywords: Conservation tillage, soil properties, yields.
Introduction
Agriculture is an engine of economic development and is integral to any agenda for
addressing global issues of the twenty-first century (e.g., food and nutritional security,
climate change, growing energy and water demands, and biodiversity). Nepalese
agriculture sector have also moved off course onto a path of declining productivity and
increasing negative externalities, a path that is considered to be unsustainable
ecologically as well as economically and socially. Indeed, the intensive tillage-based
farming with its high and addictive dependence on manual labor in the hills and sloppy
terrain to heavy machinery in the Terai and flat lands is no longer fit to meet the
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24-25 March 2015
agricultural and rural resource management needs and demands. It seems to us who
deal with agricultural production systems that with intensive tillage as a basis of the
current agriculture production and intensification paradigm we have now arrived at a
“bit dangerous” point in agro-ecosystem degradation globally (Figure 1). Worldwide,
more than 10 million hectares of productive arable land are severely degraded and
abandoned each year (Pimentel et al. 1995). Therefore, an attempt has been made in
this article to highlight briefly the significance of conservation tillage in terms of soil
restoring and improving soil properties and crop yields.
Figure 1.How tillage degrades the soil consequently soil organic carbon.
A review work on the performance of tillage and residue management methods on soil
properties and grain yield was carried out from within and outside the country. Results
of a factorial design having two factors of tillage and residue management each with
two levels i.e. with or without tillage and with or without residue under rice-maize
system carried during 2010 to 2013, in Rampur, Chitwan are also presented in the
paper.
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24-25 March 2015
Bulk density of soil as affected by tillage and residue
Tillage alters the physicochemical and biological properties of soil and provides the
congenial condition for better growth of maize. Four different till system, viz.,
conventional tillage (CT), zero tillage (ZT), raised bed (RB) and ridge and furrow (RF)
were tried with two mulch viz. no mulch (NM) and paddy straw mulch (PSM at
4.0 t ha−1). Bulk density of soil at different soil depths were lower in RF followed by
RB. Soil organic carbon (SOC) changed with tillage and higher SOC was recorded on
ZT at top 0–10 and 10–20 cm soil depths but below 20 cm there was no significant
difference. Consequently, all the physical and chemical parameters were better with
PSM over NM. The measured growth and yield attributes of maize depended on soil
properties like bulk density, porosity, water potential, texture, aggregation and soil
organic carbon (Table 1).
Table 1. Bulk density (mg m3) of soil as affected by tillage and residue at different soil
depths.
Tillage
Residue
0-10cm
10-20cm
20-30cm
CT
NM
1.21
1.30
1.44
PSM
1.18
1.38
1.13
ZT
NM
1.24
1.40
1.45
PSM
1.20
1.39
1.44
RB
NM
1.15
1.35
1.42
PSM
1.13
1.33
1.42
Source: Chaudhary et al. (2013)
Soil moisture storage as affected by tillage and residue
The long-term effects of no tillage (NT) and conventional tillage (CT) on soil
properties and crop yields were investigated in annual double cropping system of
winter wheat–summer maize in the Gaocheng in Hebei, North China Plain over an 11year period (1998–2009). Long-term NT significantly (P < 0.05) increased soil organic
matter, available N and P in the top 10 cm by 16.1%, 31.0% and 29.6% as compared to
CT treatment. Soil water storage (0-30cm soil depth) at the time of winter wheat
seeding in CT soils from 1999-2009 was 55.8mm, while in NT soils it was higher (60
mm). In the dry years of 2001(annual rainfall: 347mm, 2004 (373mm), 2006 (400mm)
and 2009 (389mm), particularly, soil water storage in NT were higher representing a
mean improvement of 19.43% in NT treatments (Table 2).
Table 2:Soil water storage (mm) in Wheat at 0-30cm soil depth (1999-2009).
Treatment
Annual rainfall (mm)
NT
1999
583
601
2001
347
409
2003
614
725
2005
521
586
2007
521
773
2009
389
459
CT
613
403
706
558
749
343
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24-25 March 2015
Total soil porosity (%)
Soil porosity
In general macro and mesoporosity were greater in no-till soils, but microporosity was
less than that in ploughing soils. In the 0-10cm soil depth macro and mesoporosity on
NT plots were 51.2% and 4.6% greater, but microporosity was 3.8% less than on CT
plots. In deeper soil layers NT treatment also had 61.6% higher macroporosity in the
10-20cm soil depth, and statistically greater (17.8%) mesoporosity in the 20-30cm soil
layer, but mean microporosity in the 10-30 cm soil layer was 18.3% less.
Consequently, mean total porosity was 9.0% greater in NT (47.9%) than that in CT
(43.9%) largely due to an increase in macroporosity on the NT plots. Mean percentage
of macro-aggregates (>0.25 mm, +8.1%) and macroporosity (>60 μm, +43.3%) was
also enhanced statistically (P < 0.05) in the 0–30 cm soil layer (Figure 2).
49
48
47
46
45
44
43
42
41
40
39
0-10cm
0-10cm
10-20cm
10-20cm
20-30cm
20-30cm
CT
NT
CT
NT
CT
NT
Figure 2: Soil porosity as affected by tillage methods at different soil depths.
An experiment of tillage with two levels (NT: no till planting of maize and direct
seeding of rice and CT: Conventional tillage for both the crops) and residue
management with two levels (RK: Residue Kept i.e. maize residue anchored at 40cm
above the ground for rice planting and rice residue anchored at 30cm for maize
planting and RR: Residue Removed) under maize-rice system was carried out at
Rampur, during 2010 to 2013.
The effect of tillage and residue on the soil organic matter, N, P2O5 and K2O content
was found to be significant. No tillage and residue kept plots had higher amount of soil
organic matter, N, P2O5 and K2O compared to conventionally tilled and residue
removed plots (Table 3). Conventional tillage practices cause change in soil structure
by modifying soil bulk density and soil moisture content. In addition, repeated
disturbance by conventional tillage gives birth to a finer and loose-setting soil structure
while conservation and no-tillage methods leave the soil intact (Rashidi and
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Keshavarzpour 2007). This difference results in a change of characteristics of the pores
network. The number, size, and distribution of pores again control the ability of soil to
store and diffuse air, water, and agricultural chemicals and, thus, in turn, regulate
erosion, runoff, and crop performance (Khan et al. 2001). Losses of soil organic C
(SOC) and deterioration in other properties exaggerated where conventional tillage was
employed (Powlson et al. 2012). With time, conservation tillage, on the other hand,
improves soil quality indicators (Plaza et al. 2013) including SOC storage (Sharma et
al. 2013). It was observed that the total N (%) content gradually increased in ZT and
MT with progressing time. In 2011 and 2012, the highest phosphorus content (18.54
and 20.32mgkg−1 for 2011 and 2012, respectively.) was found in ZT which was
significantly higher than the other tillage practices. The lowest phosphorus content
(13.76 and 14.32mg kg−1) was recorded in DT. ZT showed the highest concentration of
K in all the years and the minimum was in DT.
During the first 4 years of tillage, (Rhoton 2000) determined a 10% loss of initial soil
organic matter content with plough tillage.Positive impact of residue retention on soil
quality is partly due to the nutrient recycled into the soil. On an average crop residue
contains 0.8% N, 0.1% P and 1.3% K. Consequently the long term impact of residue
retention on soil quality is both due to elemental cycling and to providing food and
habitat for soil biota especially for microorganisms and earthworms (Lal 2005).
Table 3: Effect of tillage and residue methods on soil chemical properties in rice field
at Rampur, Chitwan, Nepal(2010-2013).
Soil organic matter, N, P and K content in soil
Treatments
OM %
N%
P2O5kg ha -1
K2O kg ha-1
Tillage
b
CT
3.994
b
0.172
a
NT
LSD
SEm±
Residue
4.886
0.275
0.129
3.155
0.193
0.008
0.004
LSD
SEm±
5.725
0.292
0.137
93.3
a
107.5
5.01
2.35
94.0
4.60
2.16
b
b
90.7
a
0.190
0.009
0.004
b
a
b
0.176
a
RK
93.6
a
b
RR
b
83.5
a
110.3
5.31
2.49
a
103.8
4.88
2.29
No of tillers, thousand grain weight and grain yield of rice
The effect of tillage and residue was evident on the number of effective tillers and
grain yield of rice. It might be due to the effect of improved soil qualities as presented
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24-25 March 2015
in the previous tables (Table 4). Similarly, the effect of tillage on the grain yield of
maize was obvious (Figure 3) and the reasons might be the same for rice.
Table 4: Effective tillers, thousand grain weight and grain yield of rice as affected by
tillage and residue, 2013, Rampur.
Treatments
Effective tillers ,
1000 grain weight,
Grain yield,
Sq.m,nos
g
t ha-1
b
123.0
CT
19.8
2.281b
a
168.3
NT
20.2
3.668a
18.2*
LSD
NS
0.476*
3.27
SEm±
0.2
0.935
123.1b
20.1
2.225b
RR
a
168.3
RK
19.9
3.723a
22.18**
LSD
ns
0.084*
2.77
SEm±
0.3
0.043
Figure3. Grain yield of maize as affected by tillage and residue levels, 2013, Rampur.
Conclusion
Conservation Tillage (CT) = no tillage+ residue kept improves soil’s physical
(porosity, bulk density and water holding capacity) and chemical properties (organic
matter, N, P and K in the longer run.Crop yields and related parameters are comparable
or higher than conventional tillage system.The CT technology being new frontier as
well as a low cost and climate smart agriculture in Nepalese agricultural research and
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24-25 March 2015
development, needs to back by strong policy and collaboration between research and
extension.
Acknowledgement
Authors are highly thankful to NARC management and NMRP family for their
continuous support rendered during the course of this study period. They are also
thankful to Second National Soil fertility Workshop organizing committee and Soil
Science Division, NARC for providing the opportunity to present this paper.
References
Khan FUH, AR Tahir and IJ Yule. 2001.Intrinsic implication of different tillage
practices on soil penetration resistance and crop growth.Int. J. Agric. Biol. 1:
23–26.
Lal R. 2005. World crop residues production and implications of its use as a biofuel.
Environ. Int. 31(4):575-84.
Pimentel D, C Harvey, P Resosudarmo, K Sinclair, D Kurz, M McNair and S Crist.
1995. Environmental and Economic Costs of Soil Erosion and Conservation
Benefits. Science New Series Vol 267 No 5201 : www.sciencemag.org
Plaza C, D Courtier-Murias, JM Fernández, A Polo and AJ Simpson. 2013. Physical,
chemical, and biochemical mechanisms of soil organic matter stabilization
under conservation tillage systems: a central role for microbes and microbial
by-products in C sequestration. Soil Biol.Biochem. 57: 124–134.
Powlson DS, A Bhogal and BJ Chambers. 2012. The potential to increase soil carbon
stocks through reduced tillage or organic material additions in England and
Wales: a case study. Agric. Eco. Environ.146 (1): 23–33.
Rashidi M and F Keshavarzpour. 2007. Effect of different tillage methods on grain
yield and yield components of maize (Zea mays L.), Int. J. Rural Devel.2:
274–277.
Rhoton FE. 2000. Influence of time on soil response to no-till practices. Soil Sci. Soc.
Amer.J. 64 (2): 700–709.
Sharma KL, J K Grace, R Milakh. 2013. Improvement and assessment of soil quality
under long-term conservation agricultural practices in hot, arid tropical
aridisol. Comm.Soil Sci.Pl. Anal. 44 (6): 1033–1055.
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7.
SP-1
Soil cientists ngaged in esearch, evelopment and
cademic nstitutions in Nepal: Where o e o?
Keshav R Adhikari
Tribhuvan University, Institute of Agriculture and Animal Sciences (IAAS),
Rampur, Chitwan, Nepal
Abstract
Nepalese soil scientists have come from diverse socio-cultural settings and largely share a
common rural agricultural background. From this perspective, the term ‘soil’ was not new
as we made our career in the field of soil science. Our common future lies in continued
fostering of the principles and practices of this subject and use this knowledge to support
programs and activities leading to sustainable soil resource development. Today, we are
engaged in diverse research, development and academic institutions in the country and
abroad. Nevertheless, it appears that we are still far behind our potentials to contribute to
agricultural and environmental objectives of the 21st century.
Complying with this global agenda and local circumstances of Nepal, we have to come
forward from our respective corners and play several key roles to promote interinstitutional cooperation and make these institutions more vibrant for this cause. While
food
, it is
soil scientists’ role is primary for improved soil fertility to
also necessary to shift priority on the environmental issues in areas of food sufficiency. It
would not be surprising to foresee that the current management level of related institutions
) in Nepal will not sustain long-term. Therefore, the question is to what
(public
extent soil scientists (or, our institutions) are prepared to transform conventional
production system. It would be
agriculture into eco-agriculture to
hard to realize these achievements without an appropriate decision-making policy
to produce capable human resources for the future. More importantly,
agricultural universities, NARC, Ministry of Agriculture and Environment
should venture for developing local and national partnership, networking,
coordination and sharing information to work as a team. New policies should evolve such
that farming communities and agro-based entrepreneurs are benefited from these
institutions and intellectual contributions including that of Soil Science Society of Nepal.
No doubt, for the next generation, concentrations will have to go to develop a suit of interdisciplinary approaches to protect soil resources and maintain environmental quality.
Keywords: Institutional networking, intellectual contribution, inter-disciplinary
approaches, partnership
Why learning soil science is so important?
Nepal is predominantly an agrarian country. Over 70% of population is still engaged in
this sector accounting for about 40% of the GDP. Nepalese agriculture is said to be rich
in a number of so called good indigenous practices sustaining rural livelihood since
time immemorial. However, taken evidences from the historical trend, this sectoralone
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could not drive the national economy. Nevertheless, Nepal government pours a large
share of national budget to produce an adequate supply of food for the growing
population. But it is often said that farmers have continuously faced limited access to
support services, such as improved seeds, irrigation, fertilizers, new technologies,
transportation, off-season storage facilities, crop insurance, extension education and
market opportunities and so on. Accepting to what has been said would mean that
agricultural production system in Nepal is dwindling leaving rural economies
depressed and hunger, malnutrition, unemployment and urban migration increased.
However, not going into the details behind these consequences, I would safely argue
that science on which agriculture develops succumbed to receive low priority in the
country. Drawing on regional and global experiences, it appears that only consistent
and sincere efforts of generations could perpetuate into scientific development of
agriculture. Have we done that? And, as said earlier, we are rich in traditional cultures
but a blend of these two would work only after advancing the scientific domain of
agriculture. This requires modernization of traditional cultures which must be
supported by scientific principles of agriculture. Not underestimating the role of other
fields of agricultural science, it is widely accepted that the science on which the whole
spectrum of agriculture sustains is the soil science –the physical reality and a basis of
whole ecosystem functions providing all kinds of services to the mankind. It is
therefore, very important that unless a value is placed on soil, agriculture will remain
backward as we have been facing today.
It would be helpful to learn from the history. “Great civilizations collapsed because
they failed to prevent soils from degradation on which they were founded,” Wits
University Professor Mary Scholes and Dr. Bob Scholes write in ScienceDaily on
November 4 of 2013. It is not uncommon with the national government that
development of plans and programs and resource allocation are often made on narrow
and ad-hoc approaches most likely leading to slip off the target. Therefore, it is still
hard to figure out when the value of soil science and the art of using soil will emerge in
the mainstream of national priority. Based on these premises and current national
development contexts, this paper aims to put forward some ideas helpful for taking
benefits of this vast resource by utilizing knowledge and expertise of Soil Science
developed in the country.
Emphasize the Role of Soil Scientists
Agricultural development
As pointed out earlier, agriculture sector alone cannot drive the national economy but
still demands more investment ontechnological innovations to the extent that food
security is maintained in the country. This then would help to meet a necessary
condition to relieving from a painful food deficit. Once the food security is maintained,
agriculture would serve as a precursor for furthering the economy. From this
perspective, agriculture could be said a basic pillar of national economy.Conversely, a
target of very high return would also ruin the land and water resources quickly.
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Let me go in a bit detail into this point. Most farmers in Nepal have now switched over
to the use of improved crop varieties but suffer economic losses partly due to low or
imbalanced input (fertilizer, irrigation, seed etc.)rates. Nation must be prepared to grow
more food tofeed ever growing population. In the name of sustainable food production
or sustainable agriculture or organic agriculture, Nepal cannot keep starving while
neighboring countries have skyrocketed their economy, advanced technologically and
improved amenities of living standards.Soilsare dynamic bodies in nature but Nepalese
farmers are still using the same age-old fertilizer recommendation rates of the
government (just an example). Why can’t we review those age-old fertilizer rates and
provide farmers with current rates of fertilizer application? Similarly, despite plenty of
water resources in Nepal, irrigation is highly a matter of luck for most farmers. Being a
student of soil science, we have studied topics of soil-water relationships or soil-plant
relationships. These courses have taught us that irrigation alone can increase crop
productivity by 50%. To what extent do the Nepalese farmers know if there are any
irrigation technologies available to meet their local needs? Soil scientists are the most
appropriate professionals who should take a lead role to untiringly carry out field and
laboratory research activities to answer these questions. To contribute to this goal, Soil
Science Division of NARC and University must work jointly on long term basis. But
do we have enough number of soil scientists and resources developed in NARC and
universities in Nepal? If the commitment comes from the political sphereto eradicate
food insecurity which we are looking forward;in the next few years, we need over one
hundred of soil scientists with the highest university degree (PhD) and same number of
research staff (half from MS degree and half post-doctoral) to advance fundamental
and applied research with target of attaining food security.A significant restructuring of
NARC system willthen be needed to bring in more infrastructures, stringent manpower
hiring policy for qualified soil science experts, encourage advanced research and
equipment, and more importantly introduce regulations and monitoring for better
work-ethics and accountability.
National Parks and Forest Development
It is a well-established fact that protection of natural environment (plant, animals,
water and the landscapes) is the key to successful tourism in any country. Principles
and practices of soil and water conservation including nutrient enrichment in watershed
management are the major areas that soil scientists must undergo through detailed
training courses for university graduation. This knowledge and experience earned
through rigorous and expensive training is wasted in most of the current areas in the
government system where soils scientists are given placement. Let us be more
flexibleand go beyond the traditional boundary of ministry of agriculture and
development for the use of soil scientists’ expertise in nation building process. For
example, using advanced knowledge of the subject matter, they can successfully model
the environment and demonstrate as to what kind of scenario we would like to choose
for future nature conservationprogram. Not just conservation, by virtue of their
professionalism, they are supposed to successfully work in restoration of wetlands and
degraded lands which could be a good contribution to develop government managed
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forest,protected areas under national parks and those scattered and ruined areas in
Chure mountain range.
It is increasingly important that a technical wing consisting of a team of soil scientists
be deputed under the Ministry of Culture, Tourism and Civil Aviation to promote the
tourism component of the Ministry. Similar teams of soil scientists forming technical
units should be provisioned to serve Ministry of Forest and Soil Conservation. It is
pathetic to learn that there is not even a single high level soil science professional in
any of these five departments under this Ministry. As far as my knowledge goes, each
of these departments (dept. of forest, research and survey, soil conservation, plant
resources, and dept. of national parks and wildlife conservation) need at least two high
level soil science professionals and at least 5 mid-level technicians without delay to
help meet the national park, forest and tourism development objectives of the
government.
Irrigation Development
In Nepal, Irrigation and Agriculture (especially paddy rice) are almost synonymous
terms. Ministry of Irrigation is the competent government authority to develop
irrigation facility for increased food production in the country. There are specialized
irrigation engineers in the ministry who design, and develop physical infrastructures to
provide farmers with access to supply of irrigation water. But then, questions arise how
much, how long, how fast, and how often farmers need water to irrigate their crops.
When irrigation canals were built, they were made under certain design principles and
engineers might have donetheir jobs well. But when farmers ask as to when, why, and
how much to irrigate, soil-water and plant relationships drive the principles. The
answers usually involve a combination of soil characteristics, plant growth stage and
weather conditions; however, how fast to apply water is based solely on soil type.
There are good and bad points with each soil types with respect to retain, loose or
supply water. Soil physics and soil conservation are two major branches of Soil
Science that cover theories and practices of irrigation for different soil types, times and
supply quantities in detail. No doubt irrigationand water conservation also involves
some engineering principles and in some cases, advanced mathematical models used to
quantify the flow of water in and through the soil. Moreover, Soil Scientists also study
‘Statistics and Mathematics for Soil Science.’ It is also certain that they study in more
details about physical, chemical, and biological dimensions of soil science and have
dealt with cultural practices of several kinds of field crops, horticultural and flower
plants. So, when it comes to the point of water management of any specific crop, soil
scientists should have more expertise and professionalism developed in this field than
do the engineers.Therefore, here comes the role of soil scientists – as an appropriate
professional who could contribute greatly to this function of Ministry of Irrigation
(MOI). I doubt MOI has any hiring and recruiting policy and directives for Soil
Scientists. Well, Ministry of Agriculture and NARC have positions for soil scientists,
would be an easy answer for many.I don’t think blaming each other helps much.
Definitely, MOI will be better served given that they strengthen their own technical
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team of Soil Scientists working in harmony with agricultural engineers just like social
scientists are doing in MOI since over two decades.
Maintaining Environmental Quality
It is globally accepted that soil plays a great role not only to provide support for plant
growth, but also decompose waste materials, filter, transform and to regulate the risk
and effects of climate change. Some professionals who have learnt about the soil
resource in detail are the most appropriate candidates required by the Department of
Environment of Nepal. This department was established in Nepal in 2012 under the
Ministry of Science, Technology and Environment. It clearly says that the Department
will be instrumental in dealing with environment related problems such as air
pollution, water pollution, soil pollution, sound pollution and so on. I understand that
there should be clear and attractive policies and directives for hiring scientists in the
department, among others, to recognize and make use of soil scientists’ expertise in
maintaining environmental quality of Nepal. We often say that brain-drain is a great
problem in Nepal, but at the same time, government policies have always remained
passive to attract those capable high level technical manpower in the country.
Therefore, we will be glad to see if there is a team of soil scientists officially deputed
to study soils pollution (collect soil samples, analyze, report, present, and publish
related information) for the department. Soil scientists could, for example, help
monitoring of polluted soils due to potentially harmful materials such as heavy metal
and/or persistent organic pollutants and the impacts, and study of amendments for crop
production thus improving the environmental quality and enhancing farmers’ income.
Land Survey for Land Resource Utilization
Some soil scientist are more specialized to deals with the preparation of land use
classification maps and planning of land uses by utilizing the basic soil map,
LANDSAT data, and GIS system databases. Exposure to recent advances in science
have made the younger soil scientists capable of evaluating soil-vegetation-water
continuum system of a wide variety of terrestrial ecosystems and landscapes produced
by regionality and humanity. All these help in evaluation, conservation, rehabilitation,
and restoration of the terrestrial environment, closely related with soils. Land survey is
done for better utilization of land resources. It is therefore, also important to analyze
the vegetation cover changes from past to present, and to provide necessary data for
predictions, and future preventions and amendments.Sustainable utilization of soil
resources is also studied through mapping of soil units and evaluation of potential
utility for agriculture and forestry.
People are mostly confused with the terms ‘land’ and ‘soil.’ Land is a collective term
denoting kinds of soils distributed in a given area as seen from a vantage point. But we
must scale down ifwe want to make a detailed observation of the land. Then, we collect
soil samples representing different land systems. Land survey department of Nepal
under Ministry of Land Reform and Management provides,land maps for various
purposes. One of those is for agricultural purpose, such as those with legal parcel
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boundaries of farmers’ fields.In this process, soil scientists could play a great role to
improve the scope of Ministry’s work by providing soils data. Based on scientific
learning, soil scientists have abilities to analyze and delineate boundaries between
different types of soils suited to different purposes. This would then help in developing
quality data from which more reliable inferences could be drawn. Department of Land
survey of Nepal could be in a stronger position to have its own team of soil scientists to
serve this purpose.
Energy Development
In the modern context, the energy sector comprises the totality of all industries
involved in the production and sale of energy, including hydropower, solar power, fuel
extraction, manufacturing, refining, distribution, and marketing. Modern society
consumes large amounts of fuel, and the energy sector is a crucial part of the
infrastructureto maintain society in almost all countries.Government’s petroleum
supplying sector of Nepal is weak and often fails to meet the fuel demand of Nepal.
There is doubt that imported petroleum quality meets the current environmental
standards. Likewise, being one of the largest hydropower potential country. Nepalese
spend half of their time in the dark. We have a full-fledge Ministry in the name of
Energy. This ministry is responsible for the production and sale of hydropower per se.
If we have to develop our nation, the question is to what extent, Nepalese will tolerate
these situations?
Time has come we must think forward, be fast and bring in modern science and
technologies, invest on research and serve the energy need of society. Due to many
technical, political and treaty reasons, it appears that Nepal can’t grow just on
hydropower and also should not depend on oil imports. Government must speed up
with alternative approaches, such as go for a massive scale of solar power production,
which is very successful in most of Nepal Mountains. Similarly, it is important that
part of oil/fuel demands be met increasingly from exploring and processing local plant
resources which we call ‘green energy.’ A number of technologies are available in the
international market. For example, Kathmandu urban waste could be used to produce
energy and at the same time, also produce environmentally sound manure for urban
horticulture/flower production. Both Ministry of Energy and Petroleum sectors of the
Government should forge ahead for a joint-renewable energy production program.
Universities could help in initial research phase.
Soil scientists could be very instrumental in this initiative. For example, their expertise
could be used in producing bio-fuels. This can be derived directly from plants, or
indirectly from agricultural, commercial, domestic, and/or industrial wastes.
Renewable biofuels generally involve contemporary carbon fixation, such as those that
occur in plants or microalgae through the process of photosynthesis. Similarly, bioethanol is another approach in which an alcoholis made by fermentation, mostly from
carbohydrates produced in sugar or starch crops such as corn, sugarcane or sweet
sorghum. Cellulose biomass derived from non-food sources, such as trees and grasses,
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is also being developed as a feedstock for ethanol production.Bio-diesel produced from
oils or fats could be an example of biofuel. A lot of chemistry, soil quality and plant
factor and growing environment affect the oil production. Past project-based and piecemeal types of research works carried out by some individuals or NGOs failed to
contribute to this end because they were not driven by the cause of sustainability.
Hence, government must drive a new vision, and come forward with a longrangingsustainable policies.
New Frontiers Facing Soil Scientists and Academic Institutions
Historically, soil scientists were confined to research related to agricultural production.
More recently, they are involved in several kinds of disciplines and do the research in
cross-cutting areas including the role of soils in dry and wet-land ecology, hydrology,
and biogeochemistry of diverse landscapes, environmental interactions in energy
transformations and many others. Since soils form the interface of these environmental
interactions, soil scientists should take an initiative to advance interdisciplinary
research for climate change impact mitigation, developing green energy technology,
and develop greater understanding of soil as an importantproduct of nature constituting
diverse ecosystem functions and multitudes of services.Moreover, they should be
actively engaged in research, teaching, extension, consulting, and formulating regional
and national levelpolicy and regulations for protecting soil resources.Similarly, food
security and environmental protection are serious overarching challenges of 21st
century where soil scientists should trigger trade-off between them so that technologies
are in place to increase production to the extent of attaining food security while
keeping the negative environmental impacts low. All this led to widening of the soil
science education to various directions of scientific and humanistic area. A review and
updating of old academic curricula would be imperative so that future scientists are
capable of delivering modern theories, tools and practices successfully.
A bitter truth is that number of soil science students at all levels is decreasing in the
universities globally with time. This point had pulled attention of the participants
during 20th World Congress of Soil Science in S. Korea back in 2014. It was
concluded that the subject be reviewed and made more friendly, broaden the teaching
to include environment and human health aspects. As one of the effective ways to
development attraction into the subject of soil science, the congress also agreed to
discusswith respective government line agencies to develop policies forintroducing
soils education at lower levels of schooling.
Summary
Through this paper, I think I have tried to express sincerelyand straightforwardly my
observations and experiences accumulated over two decades of working as a teacher of
soil science in the university in and outside the country. Let me summarize by making
four points: First,although much remains to learn about the soils’ role in humanity, it
has played a vital role in history and will be more important for survival and
maintenance of our living environment in the future. So, it should be understood that
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Soil Scientists’ role in drawing agricultural and environmental benefits utilizing soil
resources will be imperative. Second, Soil Scientists in Nepal should be prepared to
accept new challenges by expanding their scope of work from traditional agricultural
sector to many others areas including national park and forest development, irrigation
management, maintaining environmental quality, land surveying for improved land
resource utilization, energy development and university teaching with broadened soil
science curricula. Three, the related line ministries in Nepal would be better served if
they develop policies and programs to strengthen their own technical manpower
involving a team of soil scientists to address soils and environment related issues.
Four, these Soil scientists will then trigger an effective coordination plan across
Ministries natural resource management and sustainable development programs in the
country.
References: (Not cited in the text).
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SP-2
Chemical Pesticide Application: An Impending Threat to Soil-Health
Maintenance
Ram Babu Paneru, Sunil Aryal and
Yagya P Giri
Nepal Agricultural Research Council (NARC)
Entomology Division, Khumaltar, Lalitpur
PO Box 976, Kathmandu, Nepal
Email: rambpaneru@narc.gov.np/rbpaneru10@gmail.com
Abstract
The use of chemical pesticides has become a common practice to manage pest problems in
commercial farming in Nepal. The chemical pesticides are becoming popular because of
their quick knock-down effect on targeted pests and its easy availability in the market.
They are generally applied in the form of foliar sprays as well as directly to the soil. Due
to such application of pesticides leave considerable quantities of pesticides and their
degraded products accumulated in the soil ecosystem. The soil needs to be healthy and
productive to produce more food. Chemical pesticides cause harmful effect to soil
microbials, soil respiration and soil fertility. Soil microflora, mainly bacteria, fungi, algae
and protozoa make valuable contribution in making the soil fertile through their primary
catabolic role in the degradation of plants and animal residues in the cycling of the organic
and inorganic nutrients content of soil. Effects of different pesticides in soil have been
studied abundantly in elsewhere but very less in Nepal. Few evidences show presence of
organophosphate (OP) and organochlorine (OC) on soil of Nepal though import of
chemical pesticides has been increasing over the year in Nepal.
It would be better to use selective toxic substances which effect only to the target
organisms; which is readily biodegradable and undesirable residue would not affect nontarget surfaces. The fate of the pesticides in the soil environment in respect of pest control
efficacy, non-target organism exposure and offsite mobility has to be given due
consideration. So it is very important to monitor the persistence, degradation of pesticides
in soil and also the effect of pesticide on the soil quality or soil health by in depth studies.
It would be better to give emphasis on integrated pest management (IPM) approach
through reducing pesticide use, using pesticides judiciously and promoting technology
other than the use of chemical pesticides for crop pest management.
Key words: Pesticide, soil, microflora, toxic, residues, biodegradable, micro organisms,
ecosystem.
Background
Pesticide is any chemical used to control pest. It includes a wide range of substances
that kill insects (insecticides), fungus (fungicides), rodents (rodenticides), nematodes
(nematicides) slug and snails (molluscicides), weeds (herbicides) and others. This is
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any component of organic or inorganic origin which is used in order to reduce the
growth of any limiting factor which affects the growth of a particular crop thereby
facilitating better growth. Some pesticides may break down quickly when applied to
soils, while others may persist for longer periods. The type of soil and the type of
pesticide can also affect pesticide persistence.
Soil is a “living and life-giving” natural resource. The soil needs to be healthy and
productive to produce more foods. Soil health will have a great role in national
productivity enhancement. Major components of organic matters are present in Table 1
below.
Table 1: Major Components of Organic Matters.
Type
Humus
Fats, resins and waxes
Components
Degradation-resistant residue
from plant decay, largely C,
H and O.
Lipids extractable by organic
solvents
Fats, resins and waxes
Lipids extractable by organic
solvents
Saccharides
Cellulose, starches, hemicellulose, gums
Phosphate
esters,
phospholipids
Phosphorus compounds
Significance
Most abundant organic component,
improves
soil
physical
properties,
exchanges nutrients, reservoir of fixed N.
Generally, only several percent of soil
organic matter , may adversely affect soil
physical properties by repelling water,
perhaps phytotoxic
Generally, only several percent of soil
organic matter , may adversely affect soil
physical properties by repelling water,
perhaps phytotoxic
Major food source for soil microorganisms,
help stabilize soil aggregates.
Source of plant phosphate
Once a pesticide has been released into the environment, it can be broken down by:
• exposure to sunlight (photolysis)
• exposure to water (hydrolysis)
• exposure to other chemicals (oxidation and reduction)
• microbial activity (bacteria, fungi, and other microorganisms)
• plants or animals (metabolism)
Indiscriminate, long-term and over-application of pesticides will have severe effects on
soil ecology that may lead to alterations in or the erosion of beneficial or plant
probiotic soil microflora. Weathered soils lose their ability to sustain enhanced
production of crops/grains on the same land. Soil can be degraded and the community
of organisms living in the soil can be damaged by the misuse or over use of pesticides.
Some pesticides are more toxic to soil organisms than others.
Scientists have done several experiments to determine how long pesticides last in
various environments. They apply pesticides to soils, leaves or other surfaces and
measure the time it takes for half of the pesticide to break down called the half-life.
After one half-life, half of the chemical may be broken down. Following another half448
24-25 March 2015
life, half of the 50% remaining may be broken down, leaving 25% of the original
amount and so on. The half-life can be a useful measure of how long a pesticide may
last, but studies have found a wide range of half-lives for the same pesticide under
different environmental conditions. In Nepal such studies are lacking.Several reports
indicate that farmers are using various types of pesticides at dosage and frequency
higher than their recommendations. They do apply chemical pesticides mixing two or
many types without considering compatibility, waiting period and precautionary
measures for application.
Overview of Chemical Pesticide Use
Until 1950s, Nepalese farmers remained unaware of modern chemical pesticides. By
that time, traditional techniques were only the means for the management of insect
pests and diseases of agricultural importance. The evidence shows that chemical
pesticides were first entered from USA to Nepal in 1952. The Ministry of Health/Nepal
Government introduced DDT for the first time in Nepal in order to eradicate malaria in
the country (Kandel and Mainali 1993). The DDT was profusely used under USAID
aided malaria control program. Nepalese farmers started to use DDT against crop pests
as well on the basis of what were recommended elsewhere. The understanding of
insecticidal properties of DDT was soon followed by the development of other
synthetic organochlorines (in 1950s), organo phosphates (in 1960s), carbamates (in
1970s) and synthetic pyrethroids (in 1980s) (Table 2). During 1960s, the government
line agencies encouraged the use of pesticides in order to achieve higher yields from
the cultivation of new crop varieties in location specific basis.
Table 2:Era of Pesticide Introduction in Nepal.
Year
Pesticide groups
Common name of major
pesticides
Toxicity
humans
to
Persistence
food chain
1950s
Organochlorines
Organophosphates
High due to
long residues
High
High
1960s
1970s
1980s
Carbamates
Synthetic pyrethroids
DDT,
BHC,
Aldrin,
Chlordane, Dieldrin
Methyl parathion, Nuvan,
Malathion
Sevin, Thimet, Furadan
Sumicidin, Decis, Ficon
High
Low
Low
Low
in
Moderate
Source: Baker and Gyawali (1994).
The use of toxic pesticides to manage increasing pest problems has become a common
practice in commercial farming in Nepal because of their quick knock-down effect on
targeted pests and its easy availability in the market. They are generally applied as
foliar sprays as well as directly to the soil. In Nepal, 8 types of pesticides with 117
common names and 1561 trade names have been registered to use (Table 3).
449
24-25 March 2015
Table 3:No of Pesticides Registered in Nepal.
S.N.
1.
2.
3.
4.
5.
6.
7.
8.
Pesticides
Insecticides
Acaricides
Fungicides
Bacteriacides
Herbicides
Rodenticides
Molluscicides
Biopesticedes
Total
Common name (No.)
47
6
34
1
20
2
1
6
117
Trade name(No.)
889
19
408
11
168
23
1
42
1561
Source: PRMD (2014)
The government agencies took part for the import, distribution and use of
pesticides.Import of pesticides is increasing over the year though has fluctuated in
some years. The Fungicides contained the highest quantity of active ingredients import
followed by insecticides, herbicides, others and public health. The detail is presented
below (Figure 1 and Table 6 and Table 7).
Pesticide residues on soil and water
There are few evidences of the analysis of pesticide residue on soil and water in
Nepalese context. Less than 1.0 ppm γ-BHC existed in water and fish of Phewa, Rupa
and Begnas lakes of Pokhara, Kaski district (ED, 1998). Altogether, six composite
soils– three from Kathmandu, one from Kavre and two from Bhaktapur) showed some
indications of Lindane at detection level (0.001 to 0.002 ppm) but far below the US
EPA (1999) standard values for DDT (0.053 ppm) and Lindane/BHC (0.023 ppm)
(Anonymous 2005).Giri (2010) analyzed 15 soils samples at 10cm depth and 4 soils
samples at 3 different depths (10 cm, 30 cm and 50 cm) from farmer’s field of
neighboring districts of Kathmandu. The equipment used to analyze was Agilent 1100
HPLC, LC/MS-MS Triple Quadrupole mass spectrometry and the extraction method
adopted for extraction was QuEChERs (Quick, Easy, Cheap, Effective, Rugged and
Safe). She found that soil samples were contaminated with different pesticides
(Chloropyrifos, Metalaxyl, Methyl Parathion, Omethoate, Dimethoate, Dichlorovous
and Imidacloprid) at different concentrations. Similarly, Manandhar (2002) reported
the presence of Persistence Organic Pollutants (POP) residues in the soil collected from
different location of the Kavrepalanchowk, Dhading, Chitwan and Bhaktapur districts.
Out of 21 soil samples analyzed, γ-BHC was detected in 13 samples whereas α-BHC
was detected in 7 soil samples. The maximum level of γ-BHC detected was 0.001 ppm
and that of α-BHC was 0.0003 ppm. Aldrin was also detected on one sample.
450
450000
400000
350000
300000
250000
200000
150000
100000
50000
0
Insecticides
Fungicides
Herbicides
1997
1998
1999
2000/01
2001/02
2002/03
2003/04
2004/05
2005/06
2006/07
2007/08
2008/09
2009/10
2010/11
2011/12
2012/13
Qty. of Pesticides AI in Kg or L.
24-25 March 2015
Years
Figure 1:Pesticides (active ingredient in kg or l) imported in Nepal from 19972012/13.
Nepal government has banned persistence and hazardous chemical pesticides on
human health and environment. So far, 15 Pesticides have been banned to import and
use (Table 4).
Table 4: Pesticides Banned in Nepal.
S.N.
Name of Pesticides
1.
chlordane
2.
DDT,
3.
dieldrin,
4.
endrin,
5.
aldrin,
6.
heptachlor
7.
mirex,
8.
toxaphene
9.
BHC
10.
linden
11.
12.
13.
14.
15.
phosphamidon
organomercury compound
methyl parathion
monocrotophos
endodulfan
Group
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Organochlorine
Year
2001
2001
2001
2001
2001
2001
2001
2001
2001
2001
organophosphate
2001
2001
2007
2007
2012
organophosphate
organophosphate
organochlorine
Source: PRMD (2014)
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24-25 March 2015
Pesticide Residues on Vegetables
Paneru et al. (2012) reported that residues of insecticides continually decreased with
the increasing time period of their application with varied rate of degradation.
According to him, residues of monocrotophos, dimethoate and chlorpyriphos in tomato
fruits were higher than their acceptable daily intake (ADI) level up to 15 days of last
application and residue of methyl parathion was higher than its ADI level up to 7 days
of its last application. Similarly, residues of cypermethrin, dimethoate and fenvalerate
in the cauliflower curds were found higher than their ADI level up to 15 days of last
application whereas residues of endosulfan, fenvalerate and cypermethrin were higher
than their ADI level in cauliflower up to 25 days. The residue levels of these
insecticides in the tomato fruits and cauliflower curds at commercial growing areas
could be higher than this because farmers usually apply such insecticides frequently in
higher doses than recommended.
Effect of Pesticides on Soil Health
Effects on Soil Process
The use of pesticides on the crop fields contaminate soil ecosystem and pose threat to
the balance equilibrium among various groups. Important process of soil such as
mineralization, nitrification and phosphorus recycling are dependent much on the
balanced equilibrium existing among various groups of organisms in the soil. They
disturb the presence of soil enzymes which are very essential for the above processes
and for matter turnover.
Effects on Soil Microorganism
Soil has millions of tiny organisms including fungi, bacteria and a host of others. These
microorganisms play a key role in helping plants in utilizing soil nutrients needed to
grow and thrive. Microorganisms also help soil store water and nutrients, regulate
water flow and filter pollutants. The growth and beneficial activities of soil microflora
such as algae and bacteria are hampered by pesticide application. Healthy levels of soil
microorganisms are important for maintening soil fertility and soil structure. Soil algae,
fungi , actenomycetes and cyanaobacteria all help to decompose organic residues and
release nutrients including phosphorus which will enhance plant growth and contribute
to pollution control. Non target effects of some pesticides on soil microorganisms are
presented below (Table 5).
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24-25 March 2015
Table 5:Effects of Pesticides on Soil Microorganisms.
Pesticides
2, 4-D-iso-octyl ester
(H)*
Bromopropylate (I)*
Organisms
Culturable soil bacteria,
fungi and actinomycetes
Azospirillumbrasilense
Captan (F)*
Culturable soil bacteria,
fungi and actinomycetes
Diazinon (I)*
Fenamiphos (I)*
Fenpropimorph (F)*
Glyphosate (H)*
Imazaquin (H)*
Metsulfuron
methyl
(H)*
Methidathion (I)*
Simazine (H)*
Algae and Cyanobacteria
Actinomycetes,
Pseudomonas sp., active
fungi
Bradyrhizobiumjaponicum
Heruncolagrisea
and
Alternoniaterins
Culturable soil bacteria
and fungi
Pseudomonas sp.,
Azotobacterchroococcum
Effects
Reduced
soil
populations
No effect on growth or
N2 Fixation
Reduced
soil
populations
No effect on growth or
N2 Fixation
None
Active fungi reduced,
no effect on others
Reference
Schjonning et
2003
Schjonning et
2003
Schjonning et
2003
Schjonning et
2003
al.
al.
al.
Schjonning
2003
et
al.
Schjonning
2003
Schjonning
2003
Schjonning
2003
Schjonning
2003
et
al.
et
al.
et
al.
et
al.
Inhibition, death
Death
No effect
Growth inhibition
Reduced
nitrogen
fixation
No effect on growth ,
high
concentration
increased N2 fixation
Source: Schjonning et al. 2003, *F, fungicides; *H, herbicides; I, Insecticide
453
al.
24-25 March 2015
Table 6:Pesticides (active ingredient in Kg or L) imported in Nepal from 1997-2004/05.
SN
Pesticides
1997
1998
1999
2000/01
2001/02
1
Insecticides 31818
28728
43465
62439
60324
2
Fungicides 17438
37679
54531
102773
75445
3
Herbicides 6123
9566
2679
14943
3259
4
Others
793
1883
7753
15909
7125
5
Public
Health
Total
56173
77857
108428
196065
146152
2002/03
60391
90570
6844
19786
2003/04
85610.9
55199.0
11239.0
24323.9
2004/05
43993.8
97036.0
6386.4
5259.4
1406.3
177591
176372.8
154082.1
Source:PRMD (2014)
Table 7 : Pesticides (active ingredient in Kg or L) imported in Nepal from 2006/07-2011/12.
SN
Pesticides
2005/06
2006/07
2007/08
2008/09
2009/10
2010/11
2011/12
1. Insecticides
65113.6
46553.3
60282.4
105814.6
61615.8
96115.3
114717.7
138761.7
2. Fungicides
47702.0
74368.5
237372.2
203392.0
129567.0
183893.0
166815.43
163890.8
3. Herbicides
11030.0
5701.7
6574.1
11124.3
15683.1
46696.0
53476.66
100833.3
4. Others
4047.5
2104.2
40562.9
33204.0
2613.1
6693.2
9848.89
5. Public Health
3377.3
2556.8
2703.0
2811.0
1600.0
2276.0
174
131270.4
131284.6
347494.6
356345.6
211079.3
335673.5
345032.7
Total
Source:PRMD (2014)
454
2012/13
6841.8
410327.6
24-25 March 2015
Effects in Successive Food Chains
Pesticide destroys beneficial insect species, soil microorganisms, and worms which
naturally limit pest populations and maintain soil health; reduce concentrations of
essential plant nutrients in the soil such nitrogen and phosphorous. Some pesticides can
be biomagnified when it enters into one trophic to higher trophic level (Figure. 2).
Figure 2: Effects in successive food chains in the soil food web.
Effect on ground and surface water
There is potential risk of ground water contamination with pesticides due to very
simple carelessness during tank filling, chemical mixing, spraying, re-filling, hand or
utensil washing, tank emptying and cleaning, disposal of pesticides especially near the
ground water sources (tube well, well, deep boring etc.). Even accidental spell of
pesticides poses dangerous threat to ground water contamination.If ground water is
contaminated it will be a chronic problem. It will take years before such chemicals are
degraded because it remains away from active microbial zone.There are chances of
abuse and misuse of persistent chemical pesticides because of ignorance and lack of
knowledge on their effects on soil and environment as whole.Even if fields are left
fallow and not sprayed with pesticides, the chemicals can still get into the soil through
groundwater or irrigation systems.There are chances of abuse and misuse of persistent
chemical pesticides because of ignorance and lack of knowledge on their effects on soil
and environment as whole.
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24-25 March 2015
Conclusion
• Study on the fate of the pesticides in the soil environment in terms of
– Pest control efficacy,
– Non-target organism exposure,
– Offsite mobility (leaching effect).
• Monitor the persistence and degradation of chemical pesticide in soil.
• Study the effect of chemical pesticides on the soil quality and health.
• Encourage farmers to adopt IPM methods for controlling pests which can reduce
the need for pesticides application to soils.
• Promote technology other than the use of chemical pesticides for controlling soil
pests.
• Encourage to use selective pesticides which effects only to the target organisms;
which is readily biodegradable and which has no undesirable residue on non-target
surfaces.
• Review the "Environmental hazards" section of the product label of pesticides, and
always follow the label directions (waiting period, MRL value) .
References
Anonymous. 2005. Identification of a POPs hotspot: examination of DDT and Lindane
(BHC) residues in potato and farm soil. The International POPs Elimination
Project, Pesticide Watch Group, Nepal Forum of Environmental Journalists,
Kathmandu, Nepal. www.ipen.org.
Baker SL and BK Gyawali. 1994.Promoting proper pesticide use: Obstacle and
opportunities for an integrated pest management program in Nepal.
HMGN/MOA/WINROCK International, 1994.
E D. 1998. Annual technical report, 2053-54 (1996-97). Nepal Agricultural Research
Council, Entomology Division, Khumaltar, Lalitpur.
Giri N. 2010. Pesticide use and food safety in Kathmandu valley/ Nepal. An Master
thesis. Institute of Soil Research University of Natural Resources and Life
Sciences (BOKU). 48 p.
Matthew EBand JA McLachlan.2007. Pesticides reduce symbiotic efficiency of
nitrogen-fixing rhizobia and host plants.In: Proc. of National.Academy of
Sciences. USA, 2007, Doi: 10.1073/pnas.0611710104.
Kandel KR and M Mainali. 1993. Playing with poison. NEFEJ, Kathmandu, Nepal.
Manandhar DN. 2002. Analysis of POP pesticide residues on soil and water samples
collected from vegetable growing fields of Bhaktapur, Kavre, Chitwan and
Dhading districts. Status of POP and PIC related pesticides in Nepal. DN
Manadhar and S Bista (eds). Entomology Division. Nepal Agricultural
Research Council.Khumaltar.Lalitpur. P.O.Box 976, Kathmandu, Nepal. June
2002.
456
24-25 March 2015
Paneru RB, S Aryal and YP Giri. 2012. Insecticide residue analysis in tomato fruits
and cauliflower curds. Entomology Division, Nepal Agricultural Research
Council, Khumaltar, Lalitpur, Nepal rbpaneru@yahoo.com .Nepal Agric. Res.
J. Vol.12.
Schjønning PS, BT Elmholt and Christensen. 2003. Technology & Engineering.Nontarget effects
of pesticides on soil microorganisms....https://books.google.com.np/books?isb
n=085199850X.
PRMD.2014.Updated list of registered pesticides upto 2071/3/32
www.prmd.gov.nphttp://www.prmd.gov.np/publication/panjikrit%20bisadi.pd
f
Ubuoh EA, SMO Akhionbare and WN Akhionbare. 2012. Effects of pesticide
application on soil microbial spectrum: Case study- Fecolart Demonstration
Farm, Owerri-West, Imo State, Nigeria. Int.J.Multidis. Sci.Engin.3(2): 34-39.
US EPA. 1999. EDQL (Ecological Data Quality Level), MRL values for all media.
United States Environmental Protection Agency, Region 5, 77 West Jackson
Boulevard,
Chicago,IL,
0604-3590.
http://www.epa.gov/Region5//waste/cars/pdfs/r5-qapp-policy-199805.pdf.
[Accessed dated June 11, 2012].
457
24-25 March 2015
8. Workshop Recommendations
The Second National Soil Fertiity Research Workshop was held during 24-25 March,
2015 (10-11 Chaitra, 2071) at NARI Hall, NARC Khumaltar Lalitpur. On the second
day, the participants were divided into 3 groups to develop recommendations based on
the research papers presented in the Workshp. The group developed recommendation
on soil science policies, soil science education and strengthening the research in the
field of Soil Science in Nepal. A detailof the recommendations is given below.
Some of the recommendations of the workshop are:
1. Policy Development Group
Problem on declining soil fertility and shrinking productive arable land.
a. Soil health policy:
Subsidy based on soil health report/card or analysis- (agricultural inputs like
manures/fertilizers)
Human resource (Soil scientists and technicians) and modest laboratory
facilities at least in 35 commercial districts
Strengthen/Upgrade existing 5 regional soil labs (Hitech training to the
existing resources and recruitment)
b. Enforce policies for Protection of Arable Land
c. PPP model
Encourage to establish soil labs in Pvt. Sectors
Subsidy for equipment, and MSTL in private sectors
d. Use of ICT (Mobile apps.) in soil fertility
management
e. Collaborative soil fertility research among DoA, NARC
and
Academic
institutionsDefine scale of collaboration at local, regional and central level.
f. Management (Recruitment) of soil scientists across the various line ministries
(Ministry of land reform, Ministry of Science and technology, Ministry of
Irrigation, Ministry of Tourism etc.)
g. Encourage use of Organic sources of plant nutrients, Bio-pesticides, Botanicals
h. Scale up Subsidy for SSM practices
2. Soil Science Education Group
Problems of soil science education sector
In national context, there is lack of textbooks and study materials on soil science
(higher secondary and university level).
1. Lack of practical skills on soil analysis among students with higher education.
2. Lack of updated knowledge; age old curriculum unable to deliver updated
knowhow in the field.
3. Lack of collaboration and co-operation among Universities, NARC, DoA and
private sector.
4. Teaching quality and coverage is very limited.
5. NARC and DoAD should ask applicants for ‘No objection letter’ from
university
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24-25 March 2015
Recommendation from the Group
1. Preparation of textbooks by scientists, scholars, readers.
2. Strengthen the laboratory facilities in the university and colleges to support
practical work.
3. Revisit the old curriculum and develop new curriculum based on current state
of knowledge (standardize the curriculum in the SAARC level.
4. Develop the multilateral collaboration among different universities, MoAD and
NARC organisations.
5. Teaching methodology should be improved by conducting training, visits and
research activities.
6. Recognise the NARC scientists as teaching personals in university.
7. Providing space for elite scholars, researchers working in foreign countries.
8. Reemployment / Extension scheme for retired prof. scientists, etc. should be
enforced.
3. Research Strengthening Group
Problems
 Soil fertility decline
 Soil erosion
 Soil acidity – fertilizer
 pollutant – agrochemicals, chemical pesticides
 Decreasing of OM
 Nutrient mining
 Declining of soil beneficial microorganisms Soil scientist critically lacking in different programs and research station
Recommendation from the Group:
 Functional Analytical facility extend- heavy metals, micronutrients, pesticides
residues and GHGs- Methodology validation and harmonization
 Soil microbiology- active (PLFA, Genomics )and biomass- biological
control agents, pathogenic organims exploration, pesticides effect on
beneficial soil micro-organisms
 Soil physics- SWCC- terminal drought
 Central laboratory concept
 Manpower development
 Laboratory security and incentives
 Separate soil science form agronomy- Status of the soil before application of
nutrients –
 Multidisciplinary research – academic type of research also very important to
address the national problem
 GIS use in soil Science Soil sampling
 Variogram modeling and map Validation- via training
459
24-25 March 2015
 Research priorities on the basis of Agroecology
 intensive cultivation in terai
 Conservation agriculture
 Minimum tillage
 Soil ammendment- biochar, FYM, another soil (deposited soil ),
Vermi-compost, biofertilizer, crop residues managemnt
 Use local materials
Future Focus
 National Nuclear Technology Center- stable isotope use in agriculture
 Bioremediation
 Soil Genomics
 Nano-technology- e.g. coated fertilizer
 National soil museum
General Recommendations
1. Mobile soil Testing laboratory should expanded in the regional soil testing
lab of DOA and SSD, NARC.
2. In long term, in sloppy hill ecology, the ST could have more beneficial
environmental and economical services than CT.
3. 10 ton/ha FYM along with 50 N and K2O each kg/ha is recommended for
sustainable yield in rice-rice-wheat in Western terai condition
4. Application of biochar to soil at the rate 2-4 t ha-1 showed good performance
in coffee and radish.
5. Soil fertility status map of National wheat research program showed low
status in soil organic matter, potassium and Boron. Therefore, proper care
should have to adopt for manage research farm.
6. Use of Azolla to rice was found beneficial so it should be promoted and
disseminated and should reach to the rice farmers.
7. Application of micronutrients such as Boron@1 kgha-1 and Mo @ 500 gha-1
has been recommended for acidic soils for soybean crop.
8. Productivity of rice and wheat can be increased and sustained by improving
nutrient content in the soil through the judicious use of organic and inorganic
manures in long run.
9. Design of experiments should be made considering the soil fertility status
map of concerned stations.
10. Location of soil samples should be recorded in the soil testing laboratories. If
possible note the geographic coordinates, otherwise name of VDC, ward no
and local place name should be noted.
11. Use of Trichoderma should be promoted and should be made available to the
farmers to discourage use of chemical pesticides.
12. Application of 180:90:60 kg NPKha-1 should be used for increased
productivity of OPV maize.
13. Application of 30 t ha-1 FYM is recommended for maintaining earthworm
population and soil properties in field where cole crops and legumes are
grown in rotation.
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24-25 March 2015
Way forward and Future Consideration
• Soil survey works and GIS programmes should be promoted and reached to the
farmers’ level for assessing information by the farmers.
•
Soil fertility map should be prepared representing all types of Nepalese soils
at periodic interval.
• Fertilizer recommendation based on sites, crop, and variety should be prepare
and revised.
• Laboratory extraction method should be identified based on the suitability in
Nepal.
• Use of Optical Sensor for In-season Nitrogen Management and Grain Yield
Prediction in Maize
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24-25 March 2015
9. Questions and Answers
Some comments and answers and suggestion during the oral, poster presentation and
discussion in 2nd soil fertility research workshop are mentioned below.
Question: Dr. Tej Bahadur K. C to Rita Amagain
Did you analysis boron in Rampur?
Ans: No, lab facility is not available there.
Q. Dr Tej Bahadur K.C to B.B Tamang
Did you mention in your presentation which size water stable aggregate were there?
Ans: Soil aggregate size was analyzed with the method adopted at Hawai University.
Q. Dr. Keshab Raj Adhikary suggestions to all
Farm yard manure is very complex and its reaction is very complicated then we should
include quality of FYM, sources of FYM, and nutrient content of FYM, total soluble
salt necessary to see the function in the soil and environment aspect.
Q. Dr. Krishna Tiwari to B. B. Tamang
Bulk density was decreased with minimum tillage why? FYM can be replaced with
alternative option?
Ans: Farmers only apply FYM and less tillage may be the cause. There is no option for
alternative to FYM. They cannot afford chemical fertilizer.
Q. Dr. K. B, Karki to B.H. Adhikari
What was the uptake of P in plant with azolla application?
P analysis of plant is still remaining, P was applied basal. Split application of P showed
good result in N uptake in rice.
Q. Dr K.B. Karki to Dr. Renuka Shrestha
Are the cowpea and Masang are similar legume? then it would be better to include
masang in research. Masang is very useful soil conservation point of view.
Ans: No cowpea and Masang are different species. Cowpea is dual purpose crop. But
grain legume research program focuses on pulse crop not for vegetable or oil pupose.
Q. Dr.K. B Karki to Dr. R. D Timila
What type of technology did you seek?
Ans: In farmers field farmers can apply trichograma in FYM or compost. Commercial
formulation is not yet in the market. It remains to work on this aspect. Media use
research is still going on.
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24-25 March 2015
Suggestion from Dr. Tej Bahadur K.C.: Soil type and soil borne diseases may be better
to see in this aspect. Soil life how to make healthy by this kind of microorganism
inoculation. Collaboration with others would be better.
Q. Deepak Rijal three suggestions
-Research approach multilocation or multi environment? Or district different
ecosystem, can we develop for wide adoption outcome
-Agrometrologist also include in the research
-High input and low input, for controlled environment , how we go research strategies?
Q. Tej Bahadur Subedi to B.H Adhikari
Use of azollea in rice is already proven technology not new one adoption is problem.
Ans. Still more research before going to the farmers field in different environmental
condition is limited. We will go adoption process.
Q Dr. Dhruba Joshi suggestions and comments
No change in my time and present research pattern. As Deepak Rijal said but no one
present such kind of research, use of information technology (IT) and modeling for
short time and resources conservation. One of the challenges is to grow more food and
other is to preserve soil. We should combine these things. Research for research is
nothing. Modern technology adoption coming research should focus on new
technology. We have not strong regulatory mechanism for different fertilizer product.
Storage of product has not been done properly. If those product use then farmer will be
reluctant due to its ineffectiveness. Therefore quality control is another most important
issue. Conservation agriculture (CA) has different limitation as population is increasing
exponentially then how to tackle with this by increasing food production. We should
emphasize were to focus.
463
24-25 March 2015
ANNEXES
Annex 1: Authors Index
Manandhar S, 295
Maskey KH, 6
Merz J, 68
Mishra K, 88
Ojha RB, 210
Pande KR, 53, 413
Pandit BH, 102
Pandit NR, 102
Panta PR, 262
Rai R, 317, 359
Rajbhandari NP, 68
Rajbhandari RM, 375
Raut S, 258
Rawal N, 234, 331, 346
Regmi AP, 53
Rijal B, 6
Risal CP, 6
Sah K, 394
Sah MP, 167
Sah SN, 88
Saha D, 179
Schmidt HP, 102, 175
Shackley S, 175
Shah SC, 413
Shrestha A, 152
Shrestha G, 167, 245
Shrestha J, 191, 433
Shrestha R, 62, 200
Shrestha S, 129, 164, 167
Shrestha SK, 68
Tandan RP, 317, 359
Thapa B, 136, 331
Thapa KB, 234
Thapa M, 42
Thapa TB, 6
Timalsina HP, 129
Timila RD, 295
Tripathi BP, 26
Twanabasu B, 346
Upadhayay HR, 217
Vaidya SN, 394
Vista SP, 36, 136, 142, 145, 175, 179, 258, 274,
331
Yadav NK, 88
Yadav RD, 88
Adhikari BN, 200
Adhikari KR, 440
P, 80
A
Adhikary BH, 36, 164, 167, 175, 191, 258, 274,
302
Adhikary R, 191, 274
Allen R, 68
Amgai S, 346
Amgain R, 62
Baillie IC, 68
Bajracharya S, 274
Bajracharya SK, 302
Bam CR, 346
, 80, 191
B
Basnet L, 359
Bhantana P, 145
Bhurer KP, 167, 274
Bishwakarma BK, 68
Boeckx P, 217
Chalise DR, 234, 331, 346
Chaudhary BP, 129
Chaudhary ON, 129
Dawadi DP, 6, 42
Devkota KP, 433
Devkota S, 142, 164
Dhital BK, 68
Eichert T, 152
França SC, 217
Gautam A, 413
Ghimire AG, 175
Joshi A, 346
Kandel S, 413
Karki KB, 317, 359, 375
Karki T, 433
Katuwal RB, 145
KC SK, 302
Khadka D, 136, 234, 258, 331
Khan S, 164
Khatri N, 88
Lakhe L, 258, 331
Lamichhane S, 331
Mahato BR, 53
Mahto BN, 295
Malla R, 129
Manandhar C, 295
464
24-25 March 2015
Annex 2: Keywords Index
acidic condition, 42
acidic soil, 129, 136
a
, 136
agro-chemicals, 36
agro-forestry, 112
agro-forestry system, 26
available potassium, 346
Azolla pinnata, 275
bacteria, 262
better availability, 179
biochar, 112, 175
bio-indicators of fungi, 262
biological control agent, 295
bioremediation, 36
boron, 152
Bradyrhizobium, 282
carbon dynamics, 414
carbon sequestration, 112
chemical fertilizer, 142, 258, 302
chemical nitrogen, 275
club-root disease, 295
CO2 emission, 414
component of soybean, 62
conservation agriculture, 422
conservation tillage, 433
cost benefit analysis, 102
cowpea, 200
crop diversification, 112
crop productivity, 26, 164, 369
cropping pattern, 309
cropping system, 167, 245
current dose of potassium, 245
degraded and spoiled lands, 175
dicotyledonous plants, 152
di-nitrogen, 275
early rice, 234
earthworm population, 210
effect of boron and molybdenum, 62
extractable magnesium, 331
farm yard manure (FYM), 68, 142, 210, 234
fertilizer and manures, 191
field survey, 369
foliar-application, 152
GDD, 80
GIS, 359, 369, 375
global positioning system (GPS), 331
GPS points, 317
grain N demand, 80
grain yield, 164, 167, 191, 200
healthy soils, 36
higher infiltration rate, 317
HWSD, 394
incorporation, 275
inner-sphere complex, 217
inorganic fertilizer, 145
INSEY, 80
institutional networking, 440
integrated nutrient management, 129
intellectual contribution, 440
inter-disciplinary approaches, 440
invasive plant species, 102
iron slime, 179
jeevatu jhol mal, 302
jeevatu treated compost, 302
Jhorahat VDC, 359
judicious use of organic manures,, 88
kriging, 375
land capability, 346
land use, 346, 359
liming, 129
long-term soil fertility, 145, 167, 234, 245
ong-termsoil fertility, 88
maize genotypes, 191
mapping, 369
mobile soil testing laboratory (
), 6
mobility, 152
mulching, 414
mungbean, 282
NDVI, 80
nematodes, 262
nepalese agriculture, 175
nitrogen, 422
nitrogen fixation, 282
nitrogen levels, 53
nutrient, 68, 200
nutrient content, 309
nutrient management, 167, 257
object based image classification, 375
organic manure, 145
organic matter, 42, 68, 136, 179
partnership, 440
phosphorus, 42
phosphorus adsorption capacity (PAC), 217
phosphorus pool, 217
physico-chemical, 394
physico-chemical properties, 179
pollution, 36
potash, 42
potentiality, 175
poultry manure, 142
465
24-25 March 2015
pyrolysis, 102
randomized complete black design, 62
rapeseed yield, 129
rice and wheat, 88
rice production, 258
rice yield, 282
rice-wheat system, 164
satellite images, 317
sesquioxides, 217
slopping land, 422
soil classification, 309, 359
soil fertility, 42, 234, 262, 359, 369, 375
,6
soil fertility aps, 331
soil fertility status, 331
soil health, 403
, 394
soil nitrogen, 68
, 136
soil organic carbon, 210, 369
soil pH, 346
soil productivity, 101
soil profile, 309
soil properties, 422, 433
soil quality, 112
soil-borne diseases, 295
sowing dates, 53
sowing time, 200
soybean, 282
straw yield, 167
sustainable, 164
symbiotic efficiency, 282
toxic chemicals, 36
tribeni organic complexal, 258
tropical climate, 209
unbalanced use of chemical fertilizer, 6
uptake, 53
vermicompost, 142
wheat yield, 234
WRB, 394
yield, 53, 62, 93
yield attributing traits, 200
yields, 433
zero tillage, 53, 414
466
24-25 March 2015
Annex 3: List of Participants
S.N.
1
2
Name
Mr. Nabin Poudel
Dr. Shambhu Dhital
Designation
Chief
Chief
3
4
5
Dr. SP Khatiwada
Dr. Ananda Gautam
Mr. Hari Pd. Parajuli
6
7
8
9
10
Dr. Bhaba P. Tripathi
Dr. Bharatendu Mishra
Dr Shyam Kishor Sah
Mr Surya P Poudel
Mr Manas Kadel
Director
Chief
Hon, Agriculture
Minister
Soil Scientist
Member
Officiating Secy
DDG
Chief
11
12
13
14
Mr. Bibek Sapkota
Dr. Giridhar Subedi
Mr. Dayananda Mandal
Dr. Hira Kaji Manandhar
15
16
Dr. Keshav Raj Adhikari
Dr. Krishna B. Karki
17
Dr. YG Khadka
Scientist
Chief
Senior Scientist
Country
Representative
Associate Professor
Ex. Chief, Soil
Scientist
Director, NARI
18
19
Dr. Krishna R Tiwari
Mr.Ram B Bhujel
Professor
Senior Scientist
20
Mr. Juerg Merz
21
Dr. Ram B K.C.
International
advisor
Director, Finance
22
23
Dr. Ram Devi Timila
Dr. Ramananda Yadav
Senior Scientist
Chief
24
25
26
27
Dr. Ramita Manadhar
Dr. Renuka Shrestha
Dr. Shree Prasad Vista
Dr. Sudha Sapkota
28
Dr. Surya Laxmi Maskey
29
Dr. Surya P. Pandey
30
31
32
33
Dr. Krishna P Timsina
Dr. Tej Bahadur K.C.
Mr. Shanker Bhattarai
Dr. Tika Karki
Joint Secretary
Chief
Senior Scientist
Master of
Ceremony
Former Executive
Director
Ex. Senior Soil
Scientist
Scientist
Ex. Dean
Advisor
Senior Scientist
34
35
36
37
Mr. Umesh K Mandal
Dr. Baidya Nath Mahato
Dr. Krishna Pd. Poudel
Dr. Yagya Prasad Giri
Associate Professor
Chief
Chief
Chief
467
Office
Admin, NARC
National Potato Research Program,
NARC
Crop and Horticulture, NARC
Agri. Environment Division, NARC
IRRI, Nepal Country Office
National Planning Commission
DoA
Internal Audit, NARC
SARPOD, NARC
Horticulture Division, NARC
NARI
AFACI
IAAS, TU
Soil Science Division, NARC
National Agricultural Research Institute
(NARC)
Institute of Forestry Campus, Pokhara
(NARC)
SNV
(NARC)
Plant Pathology Division, NARC
Dept. of Soil Science and Agri.
Engineering, IAAS
Agronomy Division, NARC
Monitoring Division, NARC
(NARC)
SARPOD, NARC
IAAS, Rampur
SNV, Nepal
National Maize Research Program,
Rampur
Central Dept. of Geography, TU
CPDD, NARC
Entomology Division, NARC
24-25 March 2015
38
39
Mr. Dhruva N Manandhar
Dr. YR Pandey
Chief Scientist
Executive Director
40
41
42
Dr. Yubak Dhoj G.C.
Mr. Ananta G Ghimire
Mr. Anil Khadka
Director General
Consultant
43
44
Mr. Arjun Shrestha
Mr. Balaram Rijal
Scientist
45
Mr. Bandu Raj Baral
Senior Soil Scientist
46
Mr. Beni B. Basnet
47
48
49
Ms Sharada Joshi
Mr. Binod Silwal
Mr. Bir Bahadur
Tamang
Mr. Nunulal Uraw
Mr. Bishnu Das Joshi
Mr. Bishnu H. Adhikary
Deputy Director
General
Senior Scientist
Technical Officer
Programme Officer
50
51
52
54
Mr. Bishnu K
Bishwakarma
Dr. Chandra Prasad Risal
Sr. Soil Scientist
Senior Scientist
Chief Soil Scientist,
Workshop Coordinator
Senior Program
Officer
Senior Officer
55
56
Ms. Reena Sharma
Mr. Dev Raj Chalise
Assist Prof
Scientist
57
58
Mr. Anish Sapkota
Mr. Dhruba Joshy
59
Mr. Dila Ram Bhandari
60
61
Mr. Dinesh Khadka
Mr. Durga Prasad Dawadi
62
63
64
Mr. Gautam Shrestha
Ms. Rashila Khadka
Thapa
Mr. Hari R. Upadhayay
65
66
67
68
69
70
71
Mr. Udaya Subedi
Mr. Janma Jaya Tripathi
Mr. Kamal Sah
Mr. Ram Dular Yadav
Mr. Kulananda Mishra
Mr. Laxman Lakhey
Mr. Laxman Lal Shrestha
72
73
Mr. Shanker Shrestha
Mr. Naba Raj Pandit
53
Former Executive
Director
Crop Development
Directorate
Technical Officer
Chief
Scientist
GIS Expert
Chief
Technical Officer
Technical Officer
Senior Technical
Officer
Technical Officer
Research Scholar
468
NARC
(NARC)
Department of Agricultural Development
Landell Mills Limited
Cereals Initiatives for South Asia,
Nepalgunj
Agro Enterprise Center, FNCCI
Soil Management Directorate,
Rampur
NARC
LIBIRD
RSTL, Sunderpur
HELVETAS
IAAS, TU
National Wheat Research Program,
Bhirahawa
IAAS, TU
(NARC)
RARS, Khajura Banke
Rajdevi Consultancy
Dept. of Environmental Sc. and
Engineering, KU
IAAS, TU
ABD, NARC
RSTL, Soil Management Directorate
NRRP, Hardinath
Agriculture Research Station, Jumla
SRP, Jitpur
NMBU, Norway
24-25 March 2015
74
Mr. Nabin Rawal
Technical Officer
75
76
77
78
79
80
Mr. Narayan Khatri
Mr. Padma Raj Shakya
Mr. Parashuram Bhantana
Ms. Laxmi Basnet
Mr. Kumar Mani Dahal
Mr. Bishnu P Bhattarai
Scientist
Ex. Soil Scientist
Scientist
GIS Expert
JT
Head, Agri
Program
81
82
83
84
Mr. Subash Bhandari
Mr. Gyaneshwor Khanal
Mr. Ragindra Man
Rajbhandari
Mr. Razan Malla
85
86
87
88
89
90
91
Mr. Rajendra P Tandan
Mr. Deepak Rijal
Mr. Raju Rai
Ms. Srijana Phuyal
Mr. Ram Babu Panerpu,
Mr. Ram C. Munankarmy
Mr. Ran B. Mahato
92
93
94
95
Mr. Rishi Ram Adhikary
Ms, Parbati Chapagain
Mr. Roshan Babu Ojha
Mr. Roshan Man
Bajracharya
Mr. Sambhu Raut
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
Mr. Sankar Bastola
Mr. Shree K K.C.
Mr. Shreemat Shrestha
Mr. Subhasha N Vaidya
Mr. Sukraraj Shrestha
Mr. Surendra.P.
Srivastava
Mr. Sushil Lamichhane
Mr. Udaya C. Thakur
Mr. HKUpreti
Mr. Shyam K Chaulagain
Ms. Binita Thapa
Ms. Niru Dahal
Ms. Rashila Manandhar
K.C.
Ms. Rita Amgain
Ms. Sanu Kesari
Bajracharya
Ms. Sarala Sharma
Ms. Saraswoti Kandel
National Wheat Research Program,
Bhirahawa
Rice Research Program, Hardinath
Agriculture Research Station, Pakhribas
Chure
MoAD
HICAST
SFCCSN
Hellokantipur.com
NEST Pvt. Ltd.
Journalist
Technical Officer
GIS expert
Program Officer
GIS expert
Technician
Senior Scientist
Agriculture
Extension Officer
Technical Officer
Farmer
Assistant Professor
Professor
National Oilseed Research Program,
Nawalpur
Rajdevi Engineering Consultancy
LIBIRD
Rajdevi Engineering Consultancy
Entomology Division, NARC
District Agriculture Development Office,
Gulmi
CPDD, NARC
Kalanki Sewa Kendra
HICAST
KU
Senior Technical
Officer
Account Officer
Technical Officer
Chief
Soil Scientist
Scientist
Ex. Chief Soil
Scientist
Scientist
Joint Secretary
Chief
Farmer
Technical Officer
Chief, Agro
Extension
Directorate
Technical Officer
Technical Officer
Rampur
Senior Technical
Officer
Senior Scientist
Scientist
469
Agri. Engineering Division, NARC
RARS, Tarahara
Seed Science Division, NARC
Bhumi thumka Krishi Samuha, Lalitpur
National Grain Legume Research
24-25 March 2015
114
115
116
117
Dr. Madan Raj Bhatta
Ms. Shova Shrestha
Mr. Pradeep Yadav
Mr. Tej Bahadur Subedi
118
Mr. Buddhi Bahadur
Pant
Mr. Jiban Shrestha
Mr. Kailash Bhurer
Mr. Pramesh Pokharel
Mr. Hem Chandra
Pokharel
Mr. Dinesh Thapa Magar
Dr. Binesh Man Sakha
Mr. Arjun Prakash Poudel
Mr. Prakash Chapagain
Mr. Suraj Kunwar
Mr. Manohar Neupane
Mr. Rajesh Verma
Mr. Suman Panha
Mr. Sanjay Luitel
Mr. Arjun Pokhrel
Mr. Gopal Saud
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
Chief
Scientist
Chief
Regional Agri.
Director
Technical Officer
Programme, Nepalgunj
Gene Bank, NARC
Commercial Crop Division, NARC
Eastern Region
Scientist
Director
Personal secretary
Personal secretary
NMRP, NARC
RARS, Parwanipur
MoAD
MoAD
Scientist
Senior Scientist
Scientist
Journalist
Subeditor
Cameraman
Sub-editor
Journalist
Cameraman
Journalist
Journalist
SARPOD
Biotechnology Division, NARC
ORD, NARC
Sahara news and hellokantipur Pvt Ltd
Kantipur daily
AICC
Annapurna Post
Kantipur TV
470
Ujjyalo 90 Network
Chakrapath.com
24-25 March 2015
Annex 4: Workshop Programme Schedule
Day 1: Chaitra 10, 2071 (24 March 2015)
Master of Ceremony: Dr.
Sudha Sapkota
Time
Activity
8:30-9:00
Breakfast and Registration of the Participants
9:00-11:40
INAUGURAL SESSION
9:10-9:20
9:20- 9:30
9:25-9:55
9:55- 10:15
10:1510:35
10:3511:05
11:0511:20
11:2011:30
11:3012:00
12:0012:50
12:50-1:30
1:30-1:50
1:50-2:10
2:10-2:30
2:30-2:50
Chief Guest: Mr. HP Parajuli, Honorable Minister, Ministry of Agricultural
Development
Chairperson: Dr. YR Pandey, Executive Director, Nepal Agricultural Research
Council (NARC)
Special Guest: Dr. Bharatendu Mishra, Member, National Planning Commission
(NPC)
Other Guest: Dr. Shyam Kishor Sah, Officiating Secretary, Ministry of Agricultural
Development (MoAD)
Dr. Yubak Dhoj G.C. Director General, Department of Agriculture (DoAD)
Mr. Udaya Chandra Thakur, Joint Secretary, MoAD
Dr. S P Khatiwada, Director, Crop and Horticulture, NARC
Dr. Ram Bahadur K.C., Director, Finance, NARC
Dr. Krishna Prasad Poudel, Director, National Agricultural Research
Institute (NARI)
Dr. Bhoj Raj Joshi, Director, National Animal Science Research Institute
(NASRI)
Mr. Bishnu Hari Adhikary, Chief, Soil Science Division, NARC
Mr. Durga Prasad Dawadi, Chief, Soil Management Directorate, DoAD
Mr. Beni Bahadur Basnet, Deputy Director General, DoAD
Mrs. Niru Dahal, Chief, Agri.Extension Directorate, DoAD
Mr. Dilaram Bhandari, Crop Development Directorate, DoAD
National Anthem
Welcome Address: Dr.S P Khatiwada, Director, Crop and Horticulture, NARC
Inauguration Remarks: Mr. HP Parajuli, Honorable Minister, MoAD
Strategic paper on soil and food production: Mr. D Joshy
Few Words: Dr. YD GC, Director General, DoAD
Dr. Shyam Kishor Sah, Officiating Secretary, MoAD
Dr. Bharatendu Mishra, Member, NPC
Honouring program by Dr. Bhartendu Mishra , Member , NPC (Awarded to IRRI
Principal Scientist, Dr. JK Ladha ; Ex Chief Soil Scientist, Mr. Bidur Kumar Thapa
and Mr. Dhruva Joshy, Ex ED, NARC)
Vote of Thanks: Mr. Bishnu Hari Adhikary, Chief, SSD, NARC
Closing Remarks: Dr. YR Pandey, Executive Director, NARC
Poster Presentation
Lunch Break
Plenary Session
Chair Person – Dhruva Joshy, ex-ED, NARC
Strategic paper from Dr. Krishna Bahadur Karki, Ex-SSD
Chief
Strategic paper from Mr. Anil Khadka,CEISA
Strategic paper from Dr. Bhaba Prasad Tripathi, IRRI,
Kathmandu Office
Strategic paper from Mr. Durga Prasad Dawadi, SMD (DoA)
471
24-25 March 2015
2:50-3:10
3:10-3:25
3:25-3:35
3:35-3:45
3:45-3:55
3:55-4:05
4:05-4:15
4:15-4:25
4:25-4:40
4:40-4:50
4:50-5:00
5:00-5:10
5:10-5:20
5:20-5:45
6:30-9:00
Strategic paper from Dr. Shree Prasad Vista, SSD, Khumatlar
Closing and Tea Break
Technical Session 1 ( Soil Fertility)
Chair Person – Prof. Tej Bahadur K.C. Ex Dean, IAAS, TU
Soil Fertility Status of Nepal: Report from Laboratory Analysis
of Soil Samples of five Developmental Regions
Yield trend and soil fertility status after a 36 years rice-ricewheat experiment
Sowing time and nutrient management in cowpea under light
textured soil of Rampur, Chitwan
Sustainability of long-term soil fertility management in rice
wheat cropping pattern in eastern mid hills of Nepal
Potential Options for Sustainable Land Management and
Intensified Agriculture
Determination of different level of Nitrogen, Phosphorus,
Potash and Farm yard manure (FYM) in wheat – French bean
system in Jumla condition
Discussion, Tea and Closing
Chairperson: Mr. Tej Bahadur Subedi, Regional Director,
Eastern Development Region
Response of soybean to the application of Boron and
Molybdenum in Rampur condition.
On-Farm Monitoring of Improved Management of Farmyard
Manure and Soil Nutrient Fertility in the Middle Hills of Nepal
Use of optical sensor for in-season nitrogen management and
grain yield prediction in maize
Biochar: its role in soil management and potentiality in
Nepalese Agriculture
Discussion and Closing
Dinner at Hotel Himalaya
Day 2: Chaitra 11, 2071 (25 March 2015)
8:30-9:00
Registration and Breakfast
Technical Session 2 (Soil Microbiology and RCT)
Chair Person: – Prof. Tej Bahadur K.C. Ex Dean, IAAS, TU
9:00-9:10
9:10-9:20
9:20-9:30
9:30-9:40
9:40-9:50
9:50-10-15
Efficacy of Azolla pinnata in Rice (Oriza sativa L.)
Production in The Central Region of Nepal
Symbiotic Characterictics of Nepalese Bradyrhizobium Isolates
from Soybean (Glycene max) and Mungbean (Vigna radiata)
Crops
The Trichoderma spp.: A Biological Control Agents from
Nepalese Soil
EN hancing soil fertility and crop production through
promoting conservation agriculture production systems(CAPS)
in the mid hills of western Nepal
Evaluation of Conservation Agriculture based Practices under
Rice-Wheat Cropping System in inner Terai region of Nepal
Discussion and Closing
Technical Session 3 (Soil Survey, GIS and Policy)
472
Rapporteur
Dr. KR Adhikary
Mr. S Lamichanne
Durga Prasad
Dawadi
N Rawal
R Shrestha
Parashuram
Bhantana
RM Bajracharya,
Laxman Lal
Shrestha
Rita Amgain
BK Bishwakarma
BR Baral
SP Vista
Rapporteur
Mr BR Baral
Ms R Amgain
BH Adhikary
Chandra Prasad
Risal
RD Timila
BB Tamang
A Khadka
Rapporteur
Dr. CP Risal
24-25 March 2015
Chairperson : Dr. S P Khatiwada, Director, Crop and
Horticulture, NARC
10-15:10:25 Soil Types and Fertility status in Western Terai region of
Nepal.
A case from the BankatawaVDC of the Banke District
10:25-10:35 Assessment of soil fertility status and preparation of their maps
of National Wheat Research Program (NWRP), Bhairahawa,
Nepal
10:35-10:45 GIS and RS Supported Soil Fertility Mapping
10:45-10:55 Soil organic carbon stocks estimation and mapping by using
GIS in Rautahat district
10:55-11:05 Modeling of soil organic matter content from world view to
satellite imagery in Nayavelhni VDC of Nawalparasi district,
Nepal
11:05-11:15 Preparation of data base and soil map of Nepal using WRB
2010 classification system
11:15-11:35 Discussion and Tea
11:35-11:45 Soil scientists engaged in research, development and academic
institutions in Nepal: Where do we go?
11:45-11:55 Soil health and future research strategies in Nepal
11:55-12:05 Effects of pesticides in soil health: Areas of study
Ms. Shova
Shrestha
Krishna R Tiwari
D Khadka
Ragindra Man
Rajbhandari
K Sah
Umesh K Mandal
SN Vaidhya
Keshav Raj
Adhikari
Sarala Sharma
RB Paneru, YP
Giri
12:05-12:30 Discussion and Closing
12:30-1:10
1:10-2:50
2:50-3:05
3:05-3:20
3:20-4:30
Lunch Break
Group Formation : Facilitator : Dr. KB Karki
Group formation and recommendation (1st group for
technology recommendation and 2nd group for policy/strategy
recommendation/way forward : Discussion within groups and
recommendation compilation for presentation
Closing Session
Chair Person : Dr. YD G.C., Director General,
Dr. SP Khatiwada, Director, Crop and Horticulture, NARC
Chief guest: Mr. Udaya Chandra Thakur, Joint Secretary,
MoAD
Presentation from Group 1 (Technology Recommendation)
Presentation from Group 2 (Policy recommendation)
Award - Certificate Distribution by the chairperson to
awardees of 3 posters
Main author collect their certificate of participation
Few words: Dr. SP Khatiwada, Director, Crop and
Horticulture, NARC
Mr. Udaya Chandra Thakur, Joint Secretary,
MoAD
Vote of Thanks: Mr. BH Adhikary, Chief, SSD, NARC
Closing Remarks: Dr. YD G.C., Director General, DoA
Announcement for the National Level meeting of Soil
Scientist for next day (Society of Soil Science Nepal)
Refreshment: Snacks and Tea/cold drinks
473
Rapporteur
Mr. BD Joshi
Mr. N Rawal

proceeding of 2nd national soil workshop

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