fitting technology options to farmer context in mali
TRANSCRIPT
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Fitting technology options to farmer context in Mali
Mary Ollenburger, Wageningen University and Research Centre
Africa RISING West Africa Review and Planning Meeting, Accra, 30 March–1 April 2016
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AfricaRISING sites in Mali
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Maize
Sorghum
Soya
Cowpea
On-farm trials of options
Options
INTENSIFICATION
OF CURRENT
CROP
CEREAL
LEGUUME
INTERCROPPING INTE
NSIFI
CATIO
N OF
DIVE
RSIFI
CATIO
N
CROP
S
DIVE
RSIF
ICAT
ION
CROP
SIM
PROV
ED
FEED
ING
OF
LIVES
TOCK
T2Ctrl
T4T3
Intercrop
Falconnier 2015
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???
Analysis of on-farm trials
Falconnier 2015
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Average Sorghum yield on clay soils
Average soybean yield on clay soils after cotton
ΔGM = 334 USD/year/ha
!!!
Analysis of on-farm trials
Sorghum
Soya
Grain Yield (kg/ha)
Gros
s mar
gin
(USD
/ha/
year
)
Falconnier 2015
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Intensification
of current crops
CEREAL LEGUME
INTERCROPPING Inte
nsifi
catio
n of
di
vers
ifica
tion
crop
s
DIVE
RSIF
ICAT
ION
CROP
Options
CROP DIVERSIFICATION:
Replacement of sorghum by soya
CEREAL LEGUME
INTERCROPPING:
Maize-cowpea
CROP DIVERSIFICATION: replacement of sorghum by cowpea
Niches for developing new systems
Falconnier 2015
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Farm types in Koutiala
Falconnier et al. AgSys 2015
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MRE farms – replacement of sorghum by soya
HRE and HRE-LH farms – replacement of maize by maize-cowpea intercrop
LRE farms – replacement of sorghum by cowpea
1 ox
1 cow
1 donkey/calf
Farm-scale explorations: Trade-off analysis
Falconnier 2015
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Farm distributions
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Solution Space
• Many scenarios, using limited data, to quickly explore options• Input data:
• Household survey at district level for yields, input costs (AfricaRISING baselines), market survey for crop prices
• Rapid characterization of population of 109 farm households in 3 villages (crop areas, livestock and equipment), plus detailed characterization of 19 farms based on types
• Calculated income from crops and food self-sufficiency for each farm in several scenarios
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Scenarios
• Yields• 50th percentile (median) yields [MARBES]• 90th percentile (best farmer practice) yields [MARBES]• Experimental potential yields [ICRISAT/IER]
• Prices• Averaged market prices from monthly market survey in
2014-2015
• Calculated income and food self-sufficiency
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• Current crop allocation• Optimized crop allocation
• Maximize gross margins • Meet household calorie requirements with staple grains • Maize area < twice cotton area (fertilizer availability
constraint)
• Crop area expansion
Land use scenarios
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Food self-sufficiency
Yield Scenario≥80% food self-sufficient
≥100% food self-sufficient
Median 91% 79%Best farmer 99% 99%Potential 99% 99%
• Median yields: most farms self-sufficient• All other scenarios: all but one farm is self-sufficient
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Results: Gross Margins
$1.25/person/day poverty level$1225 mean yearly income from gold mining
Median
Best farmer
Potential
C
C
C
O
O
O
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Results: Gross Margins
$1.25/person/day poverty level$1225 mean yearly income from gold mining
Median
Best farmer
Potential
COOO
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What can we learn from simple scenarios?
• “Rapid prototyping” of farm designs to explore potential
• Estimating cost-benefit of a new technology should be a first step not a last step
• Staple crop improvement research should target food-insecure households
• Livestock and off-farm income income sources are important for improving livelihoods
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Typologies for Targeting and Scaling
• Simple indicators allow researchers to place farmers within types
• Important to target a diverse group of farmers for testing technologies
• Farmer evaluations can aid in analysis of variability and in targeting technologies to types
• Ex-post typologies based on initial adoption can be useful for scaling
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IFPRI ARBES teamOusmane Sanogo, Institut d’Economie Rurale
Mouvement Biologique MalienneICRISAT Technicians
The McKnight Foundation
Africa Research in Sustainable Intensification for the Next Generationafrica-rising.net