Current status of MSIRI germplasm collection

ICT Applications in Research & Development in
Agriculture
World Telecommunication and Information Society Day 2015
Telecommunications and ICTs: Drivers of Innovation
Mauritius Sugarcane Industry Research Institute, MCIA
18 May 2015
• GEOGRAPHICAL INFORMATION SYSTEM
• SOFTWARE DEVELOPMENT
• BIOINFORMATICS
GEOGRAPHICAL INFORMATION SYSTEM
Examples of output for decision-support:
Maps & added-value data
Geographic Information System (GIS)
is an information system
for storage and
management
for describing places on earth
SUGARCANE FACTORY AREAS SUPPLYING ALTEO
LEGEND
Planters category
Miller/corporate - 14 557 ha
Other
Total
- 8 294 ha
- 22 851 ha
Other features
Factory area boundary
Main roads
Rivers
Motorway
Isohyets (mm/yr
Prepared by Irrigation & Land Resources Department, MSIRI
July, 2014
Source :
i.
GISCANE (MSIRI, 2012)
ii.
SIFB data, 2012
iii.
Topographic Map of Mauritius 1:25,000 Series Y881 (D.O.S 329);
Ed 6-OSD 1989
Iv
FORMOSAT image (CNES, 2008)
v.
Mauritius Meteorological Services
vi.
Factory area boundary (SIFB, 1995)
MECHANISATION SUITABILITY MAP OF MAURITIUS
(PROVISIONAL)
Fully mechanisable
Intensive derocking
Derocking,redesign drainage & special harvest
Redesign drainage & special harvest
Mechanical loading only
Marginal land
Water body
Factory area limit
Ex-tea land
2010 Land use map of Mauritius
Preparation of Land Use
map using satellite image
(2009-2011)
N
Approx.
Scale 1: 350 000
Source:
CHUNG TZE CHEONG, M., RAMASAMY, S. and ADELAIDE, S. (2011).
The 2010 Land use map of Mauritius. Reduit: Mauritius Sugar Industry
Research Institute. 22 p.: 7 tbls, 1 fig., and 1 map (scale 1:100 000).
(MSIRI Occasional Paper No. 41).
© MSIRI, 2011.
Sugar cane varieties recommendation
for small planters
PETIT RAFFRAY
LA SALETTE
MON LOISIR FACTORY AREA
SOILS
GOODLANDS
ESPERANCE
TREBUCHET
RECOMMENDED VARIETIES
H
M3035/66, M695/69, M52/78, M1246/84, M1394/86, M1400/86, M2256/88,
M703/89, M1861/89, M2593/92, R570, R573, R575, R579
L1
M1176/77, M261/78, , M1246/84, M1400/86, , M2024/88, M2256/88,
M703/89, M1672/90, M2593/92, M1989/99 R570, R573, R575
L2
M695/69, M1176/77, M52/78, M261/78, M1246/84, M1400/86, M2024/88,
M2256/88, M703/89, M1672/90, M2593/92, M1989/99, R570, R575, R573,
R579
P1/P2
P3
ROCHE TERRE
POUDRE D’OR HAMLET
SCHOENFELD
PITON
RIV. DU REMPART
AMITIE
PLAINES DES ROCHES
BELLE VUE MAUREL
M1176/77, M261/78, , M1246/84, M1400/86, , M2024/88,
M2256/88, M672/90, M2593/92, R570, R573, R575
D
M1176/77, R570, R573
S
M3035/66, M1176/77, M1400/86, R570, R573, R575
T3/T4 M1176/77, R570, R573
No recommendation
SUGGESTED VARIETIES
Source : Recommendation sheet No. 183, June 2012 – MSIRI, MCIA
AMAURY
La Nicolière
MARE
D’AUSTRALIA
Future outlook: Convergence of ICT solutions for farmers
Digital data capture
Drone
The overall objective is to improve the
a) field productivity for adapted cultural practices to reduce the
production costs and increase yield; and
b) the capacity in the industrial/regional resource planning.
Data viewing or situation assessment
for almost Real-time solutions
GPS survey
Overlays of
related
spatial data
Through
Web portal
and Server
agricultural land
Isohyet
Soil Family
Satellite imagery
Digital
Elevation
Model
SOFTWARE
Irrigation management
APPLICATION OF ICT FOR IRRIGATION
• Development of an irrigation scheduling software
• For management of an irrigated block
• Integrated irrigation management tool
• Irrigation Management Information System (IMIS) for sugar cane
FEATURES OF SOFTWARE IMIS
 GIS-based and integrating biophysical factors related
to irrigation in a farm
 provision of standard format for data capture,
storage & manipulation
 enable unbiased decision-making in
irrigation management.
IMIS
Development of software
• Data collected from sugar estates in Mauritius & overseas partners
• GIS map layers prepared
• Irrigation optimization models developed and tested
• Software designed
• Interfaces, screens & reports developed
• Software modules developed and integrated
• Modules tested individually, system tested as a whole
1. Main menu
Projet ACP/EU 2.4
2. Required Inputs
The IMIS software
- GIS map
- Irrigation
Systems
Administrator
Input of parameters
Log in /Password
- Fields details
- Soil data
- Water flow
IMIS
Users
Log in /Password
Daily data input
- Rainfall
- Evaporation
- Previous irrigation
3. Outputs – Irrigation priority, Soil Moisture graphic displays
Testing in the field: easy to use
Table of irrigation recommendations & priority
30B
43B
30A
43A
17A
4C
17B
17D
17C
4D
4B
4A
44A 44B
29A
52B
53B
29C
29B
53A
52A
51B
6B
6A
6C
6D
51A
22D
22A
22C
22B
Graphical display: Rainfall, Irrigation, Soil Moisture Status
Soil moisture status of irrigated block
BIOINFORMATICS
Analysis of complex biological data
Sugarcane Variety Identification
Morphological characteristics – subject to interpretation
Fullstand
internode
bud
ligule
DNA Fingerprinting of Sugarcane – less subjective
DNA from sugarcane analyzed in genetic analyzer
Use Bioinformatics software for data analysis
Peaks/profile pattern unique to the variety obtained
Varieties
Profile
Allows identification of unknown Variety
Varieties
‘Unknown’
M 1334/84
R 570
R 575
Profile
Allows paternity testing – identification of the parents from
which a variety was derived
Construction of sugarcane chromosome map
Generate nearly 1 terabyte of DNA sequence data
Process data using bioinformatics software and high performance workstations (servers)
Identify molecular markers and construct genetic map (chromosome) of sugarcane
(SBI-01)
(SBI-02)
(SBI-03)
(SBI-04)
(SBI-05)
(SBI-06)
(SBI-07)
(SBI-08)
(SBI-09)
110-130 chromosomes in sugarcane
Approximately 30-50 markers placed
along each chromosome
(SBI-10)
Marker Assisted Breeding
Associate presence of marker to presence of desirable trait
Identify markers linked to
1) resistance to disease
2) Early ripening and high sucrose
16
14
12
10
8
6
4
Minor
gene
Major gene conferring resistance
Indirect selection of resistant plants at an earlier
stage of breeding cycle
2
0
0 3 6 9 121417202224262932353841444750535659626568717477798285889194
Sugarcane chromosome 28
Accelerate sugarcane breeding cycle
Reduce resources and cost
Increase efficiency of breeding
Morphological identification of pests
6 species of the sugarcane armyworms pest present in
Mauritius
M. pseudoloreyi
M. phaea
M. insulicola
Mythimna sp. larvae
M. loreyi
Confusions in identification due to similarity at species level
DNA barcoding
Specimen
Extract DNA
DNA barcoding enables precise
identification of pest species
Measures to mitigate impact of
the pest can be taken rapidly
COI gene PCR
DNA sequencing
Sequence analysis
L loreyi Australia
M. loreyi
Lepidoptera sp
l.stenographa
M curvula (Kenya)
M. pseudoloreyi
M conigera
L ursula
L adjuta
L lapidaria
M. phaea
M phaea (Kenya)
Lepidoptera sp.
L insueta
M. insulicola
L striata (Madagascar)
L striata (Madagascar)
M. tincta
M ferrago
M. pyrausta
Lepidoptera sp. HM914193
M Ferrago HM874912
Development of specific pathogens
PER
HAW
BRA
REU
CHN1
IND
Highly specific primer design using bioinformatics
software – enables precise and sentive diagnostic
Conclusions