Science and Technology for Food Security in Africa Mark W. Rosegrant Director Environment and Production Technology Division Technical Meeting in Support of S&T Partnerships in Africa IFPRI, Washington, DC September 8, 2014
Science and Technology for Food Security in Africa
Mark W. Rosegrant
Director
Environment and Production Technology Division
Technical Meeting in Support of S&T Partnerships in AfricaIFPRI, Washington, DCSeptember 8, 2014
Outline
Baseline Projections of Supply, Demand and Food Security
Irrigation Potential in Africa
Science and Technology for African Food Security
Moving Forward
Baseline Projections of Supply, Demand and Food Security
Annual Average Growth in GDP in Africa: Baseline Projections between 2010 and 2050
0
1
2
3
4
5
6
7
Pe
rce
nt
Gro
wth
Rat
e p
er
Year
Source: IFPRI IMPACT Model
Annual Average Growth in Per Capita GDP in Africa: Baseline Projections between 2010 and 2050
Source: IFPRI IMPACT Model
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Pe
rce
nt
Gro
wth
Rat
e p
er
Year
Annual Average Growth in Population in Africa: Baseline Projections between 2010 and 2050
Source: IFPRI IMPACT Model
0
0.5
1
1.5
2
2.5
Pe
rce
nt
Gro
wth
Rat
e p
er
Year
Cereal Yields – Africa Regions: Annual Average Growth Rate, 2010 - 2050
Source: IFPRI IMPACT Model
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
Pe
rce
nt
Gro
wth
Rat
e p
er
Year
Source of Cereal Production Growth: 2010 - 2050
Source: IFPRI IMPACT Model
-20
0
20
40
60
80
100
120
Pe
rce
nt
Ch
ange
Area Expansion Yield Improvement
Total Irrigated Area by Africa Regions: Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
0
2
4
6
8
10
12
14
CentralAfrica EasternAfrica NorthernAfrica SouthernAfrica WesternAfrica
Mill
ion
He
ctar
es
2010 2050
Percent Change in World Prices of Cereals between 2010 and 2050
Source: IFPRI IMPACT Model
0
10
20
30
40
50
60
Rice Wheat Maize Other Grains Soybeans Sorghum
Per
cen
t Ch
ange
Percent Change in World Prices of Meat between 2010 and 2050
Source: IFPRI IMPACT Model
0
10
20
30
40
50
60
Beef Pork Lamb Poultry
Per
cen
t Ch
ange
Africa Per Capita Cereal Demand: Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
0
50
100
150
200
250
EasternAfrica NorthernAfrica SouthernAfrica WesternAfrica CentralAfrica
Kg
pe
r C
apit
a
2010 2050
Africa Per Capita Meat Demand: Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
0
10
20
30
40
50
60
EasternAfrica NorthernAfrica SouthernAfrica WesternAfrica CentralAfrica
Kg
pe
r C
apit
a
2010 2050
Africa Net Trade Cereals: Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
-70
-60
-50
-40
-30
-20
-10
0
EasternAfrica NorthernAfrica SouthernAfrica WesternAfrica CentralAfrica
Mill
ion
Met
ric
Ton
s
2010 2050
Africa Net Trade Meat: Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
-5
-4
-3
-2
-1
0
1
2
EasternAfrica NorthernAfrica SouthernAfrica WesternAfrica CentralAfrica
Mill
ion
Met
ric
Ton
s
2010 2050
Population at the Risk of Hunger : Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
0
100
200
300
400
500
600
700
800
900
Developing SubSaharanAfrica
Mill
ion
s
2010 2050
Population at the Risk of Hunger – Africa: Baseline Projections, 2010 and 2050
Source: IFPRI IMPACT Model
0
20
40
60
80
100
120
140
EasternAfrica NorthernAfrica SouthernAfrica WesternAfrica CentralAfrica
Mill
ion
s
2010 2050
How can Science and Technology Improve the Outlook for Food
Security in Africa?
Assessment Framework for Smallholder Irrigation Potential in Sub-Saharan Africa
Potential large-scale and small-scale based irrigated areas, alternative IRR levels
Source: IFPRI 2010
Potential increase in gross revenue per hectare from small-scale irrigation
Source: IFPRI 2010
Large-scale irrigation potential: location specific
Source: IFPRI 2010
Dam typeInvestment expenditure
Internal rate of return
Increase in irrigated area
(US$ million) (%) (hectares)
Operational 16,299 7.16 8,351,423
Rehabilitated 1,954 11.32 1,000,944
Planned 13,465 5.27 6,899,376
Total 31,718 6.61 16,251,744
Small-scale irrigation potential: widespread, more profitable, but sensitive to cost
Source: IFPRI 2010
Cost typeInvestment expenditure
Internal rate of return
Increase in irrigated area
(US$ million) (%) (hectares)
Low 24,315 104.00 15,785,617
Medium 21,835 27.00 7,340,964
High 1,969 9.00 321,727
User-Friendly Models for Scenario Analysis
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Science and Technology Potential in African Agriculture
Potential Impact of Agricultural Technology Adoption on Global Food Security
Impacts of agricultural technologies on farm productivity, prices, hunger, and trade flows were site-specifically estimated using DSSAT biophysical model linked with IMPACT global partial equilibrium agriculture sector model.
Rosegrant, M.W., J. Koo, N. Cenacchi, C. Ringler, R. Robertson, M. Fisher, C. Cox, K. Garrett, N.D. Perez, and P. Sabbagh. 2014. Food security in a world of natural resource scarcity: The role of agricultural technologies.IFPRI, Washington, D.C.
http://www.ifpri.org/publication/food-security-world-natural-resource-scarcity
Global & Regional
Eleven technologies
Three Crops• Wheat
• Rice
• Maize
No-Tillage
Integrated Soil Fertility Management
Organic Agriculture
Precision Agriculture
Crop Protection
Drip Irrigation
Sprinkler Irrigation
Water Harvesting
Drought Tolerance
Heat Tolerance
Nitrogen Use Efficiency
Technology Assessment Scope
Modeling Tools
DSSAT• Biophysical model - assesses impact of single
technology or technology mix
˗ Productivity (yields)
˗ Resource use (water, N losses)
IMPACT• Global economic agricultural model - assesses
changes in productivity due to technology adoption
˗ Food production, consumption, trade
˗ International food prices
˗ Calorie availability, food security
Crop model (DSSAT) linked with Global Partial Equilibrium Agriculture Sector Model (IMPACT)
DSSAT
Technology strategy (combination of
different practices)
Corresponding geographically
differentiated yield effects
IMPACT
Food demand and supply
Effects on world food prices and trade
Food security and malnutrition
Global DSSAT ResultsYield Change (%) – Maize, Rice, & Wheat, 2050 vs. Baseline
Source: Rosegrant et al. 2014
Source: Rosegrant et al. 2014
Regional DSSAT Results, Maize:NUE, ISFM, and No-till, 2050 vs. Baseline
Source: Rosegrant et al. 2014
Source: Rosegrant et al. 2014
Regional DSSAT results, Maize: Drought Tolerance, Heat Tolerance and Crop Protection (disease), 2050, compared to baseline
Source: Rosegrant et al. 2014
Price Effects of Technologies, 2050, compared to Baseline: Global – Combined Technologies
Source: Rosegrant et al. 2014
-60.0
-50.0
-40.0
-30.0
-20.0
-10.0
0.0
Maize Rice Wheat
No-Till Drought toleranceHeat Tolerance Nitrogen Use EfficiencyIntegrated Soil Fertility Mgt Precision AgricultureWater Harvesting Irrigation - sprinklerIrrigation - Drip Crop Protection
Percent Change in Harvested Area, 2050, Compared to Baseline: Global – Combined Technologies
Source: Rosegrant et al. 2014
-60.0
-50.0
-40.0
-30.0
-20.0
-10.0
0.0
Maize Rice Wheat
Perc
enta
ge
No-Till Drought tolerance Heat Tolerance
Nitrogen Use Efficiency Integrated Soil Fertility Mgt Precision Agriculture
Water Harvesting Irrigation - sprinkler Irrigation - Drip
Crop Protection
Food Security Effects of Technology relative to 2050 Baseline
Source: Rosegrant et al. 2014
-40.0
-35.0
-30.0
-25.0
-20.0
-15.0
-10.0
-5.0
0.0
Malnourished Children Pop. at-risk-of-hunger
No till Drought tolerance Heat tolerance
Nitrogen use efficiency Integrated soil fertility mgt Precision agriculture
Water harvesting Sprinkler irrigation Drip irrigation
Crop Protection - insects
www.ifpri.org
Online Tool with Downloadable Data
http://apps.harvestchoice.org/agritech-toolbox/
The African Agriculture Technology PlatformMulti-Level, Face-to-Face, and Virtual
Locally appropriate technology
products and services
Supporting evidence-based investment decision and priority setting
NEW ALLIANCE TECHNOLOGY PLATFORM
Providing technical support to the New Alliance partners:1) Setting priorities for
national commodity value chains and their targets
2) Geospatial targeting and ex-ante impact analysis to optimize investments
3) Design of the Technology Platform components and development of prototype platform S
up
po
rtin
g D
ata
/ A
na
lysis
Figure 1: New Alliance Technology Platform - National Target & Technology Analysis
Other Investment Plans
CAADPNational Agricultural
Investment Plans
Development PartnersGovernment and National Partners Private Sector
New Alliance Technology Platform Country Steering Group
Status & Trends
•Nationalproduction,consumption, tradeand price statistics
- FAO, Ministry, Statistics Offices
Productivity Enhancement Potential
• Assess achievable yieldscompared to currentfarmer yields (yield gaps)
- farmer and experimentdata
- crop models
Demand & Welfare
•Trends in demand - sectoral studies, IFPRI
IMPACT model• Contribution to nutrition• Poverty & gender factors
- HH survey data
Yield Gap and Adoption Studies & Literature
• Field trials (on station, on farm)•Modeling studies• Dissemination pathway
assessments • Diffusion and Adoption
Studies (e.g. DIVA)
Nationalstatistics, household survey data, experimental data, farmer plots (e.g., own management and demonstrations), performance trials, adoption studies, crop models, technology evaluations, national data and thematic expertize, national technology and development scenarios
Sub-NationalAnalyses
•Multi-location trials• Location specific crop
modeling (e.g. IFPRI)• Investment
Document & Evaluate Focus Technologies
• Seeds• Fertilizers (e.g., ISFM)• Small scale irrigation• Agronomy (e.g. tillage)•Institutional Capacities (e.g. FARA)
National Priority
Commodities (All)
National Technical Group(including Technical Partners: CGIAR, AGRA, FARA)
Co
ord
ina
tio
n &
Re
sp
on
se
C
ore
Activ
itie
s
Technology Packages to Meet Sub-National
Yield & Adoption Targets (2022)
Sub-National Adoption Targets
Sub-National Yield Targets
National Yield Targets (2022)Achievable
Yields
Adoption Targets (2022)New Alliance
Focus Commodities
New Alliance National Technology Coordination and
Investment Plan
Identify focus commodity sub-set for
New Alliance
Moving Forward
Under the CAADP-CGIAR MoU – develop/support new ways of doing business in Africa
Partnerships – explore synergies and capacity development for additional technology sharing
Scaling of agricultural technologies to help achieve food security goals (Malabo Declaration)
Develop and transfer models for foresight and scenario analysis for policies and technologies
Develop and transfer decision-support tools for sustainable technology development, applied across scales from household/micro level to national/macro
Directions for Science and Technology Partnerships and Analysis