During the Africa Regional Planning Meetings held at Harare on 26, 27 April 2016 reviewed the overall programs and action plan and discussed on these objectives :Improved understanding of consumer demand for sorghum and millets in four ESA countries (Kenya, Ethiopia, Tanzania, Uganda). Consumption disaggregated by rural/urban, income, and proximity to centres of productionTrends in cereal prices, price and income elasticities of consumption Set research priorities for CGIAR research program for Dryland Cereals

1. Social Sciences
A. Orr, K. Mausch, A. Gierend, T.
Tsusaka, S. Homann Kee-Tui,
H. Msere, C. Mwema, B. Munyua
Regional Planning and Strategy Meeting
Harare 26-27 April 2016

2. What’s ahead
1. Foresight Analysis & Priority Setting
2. Adoption
3. Post-harvest losses
4. Gender-Plus
5. Plans for 2016

3. Sorghum and Millets in ESA:
Facts, Trends and Outlook
Source: Orr, Mwema, Gierend, and Nedumaran (2016) ICRISAT Working Paper No. 62
A.Orr,C.Mwema,A.Gierend,S.Nedumaran

4. Sorghum and Millets in ESA:
Facts, Trends and Outlook
A.Orr,C.Mwema,A.Gierend,S.Nedumaran
Results, 2015-2050:
 Faster growth in income and
slower population growth reduces
projected production of sorghum
by 9%.
 25 % faster yield growth for
maize reduces the projected
production of sorghum by 1%.
 Climate change increases the
projected production of sorghum
by 11-13 %.
 25% faster yield growth for
sorghum increases the projected
production of sorghum by 31%.
 Combined scenario: sorghum
production increases by 33% over
the baseline projection.
Key messages:
 Outlook is positive
with upward trend
 Positive effects
outweigh the negative
effects
 Climate change and
R&D offset effects of
higher income and
faster maize yields

5. Consumer Demand for Sorghum and Millets
in ESA
Objectives
 Improved understanding of consumer demand for sorghum and millets in
four ESA countries (Kenya, Ethiopia, Tanzania, Uganda).
 Consumption disaggregated by rural/urban, income, and proximity to
centres of production
 Trends in cereal prices, price and income elasticities of consumption
 Set research priorities for CGIAR research program for Dryland Cereals
Methods and data sources
 Analysis of raw data from nationally-representative household
expenditure surveys conducted by national statistical offices
 Secondary literature on food expenditure and price/income
elasticities
AlbertGierend,AlastairOrr

6. Key results
Consumption pattern: Rural/urban & proximity to production
AlbertGierend,AlastairOrr
Source: Gierend and Orr (2015). Consumer Demand for Sorghum and Millets in ESA. Priorities for the
CGIAR Research Program for Dryland Cereals. ICRISAT Socio-Economics Discussion Paper # 35.
Sorghum:
 Ethiopia (highest #
consumers, per capita
consumption, potential urban
demand)
 Tanzania, Uganda: Urban
consumers
 Kenya: market for clear beer
Millets:
 Niche markets (Smart
Foods)
 Middle-class consumers
($4-20/day)
 Will have 46% of total
consumer expenditure on
food by 2040

7. Can sorghum compete with maize? A time-space
analysis for Ethiopia
Methods:
 Update MapSpam grid cells with CSA crop statistics (2000, 2005, 2014/15)
 Add zonal data on input levels and costs from CSA and calculate Gross
Margins (GMs) for all sorghum/maize grid cells
 Blend MapSpam crop data including GMs info with temp, rainfall, elevation
and LGP maps
Data:
MapSpam spatial crop data set (version 2014), CSA (Central Statistical Agency of
Ethiopia), Input level and costs for maize (CIMMYT), GIS material (temperature and
precipitation maps from worldclim.org, altitude map from CGIAR-CSI GeoPortal,
length of growing period maps from ILRI/ICRAF
Research questions:
 Is sorghum a niche crop confined only to the SAT?
 Has maize displaced sorghum from high-potential agro-ecological zones?
 Is sorghum more profitable than maize?
 Has sorghum become less competitive over time?
 Does sorghum compete with maize or complement it?
AlbertGierend

8. Is sorghum a niche crop confined to the SAT?
Has maize displaced sorghum from high-potential AEZs?
 Sorghum and maize increased their
share of the area planted in high-
potential AEZs, while the share of
millets, wheat and barley declined
Semi-
humid
180-269
Moist
semi-arid
120-179
Dry semi-
arid
75-119
Arid
< 75
Humid
>270
low potential high potential
2014/15 26.0 25.9 26.1
2005 23.0 22.9 23.4
2000/01 22.8 23.0 22.2
sorghum area in % of cereal area
Nat
Av
LGP
sorghum 4.7 38.3 36.0 15.8 0.8 4.4
maize 6.8 23.5 39.2 20.7 1.6 8.2
millet 0.4 9.9 61.0 28.2 0.1 0.5
barley 4.9 44.6 38.5 5.9 1.4 4.7
wheat 4.2 44.7 39.3 6.1 2.7 3.0
Moist
semi-arid
120-179
Dry semi-
arid
75-119
Arid
< 75
Humid
>270
Moist semi-
humid
240-269
Dry semi-
humid
180-239
 Sorghum is grown in ALL agro-
ecologies: in the arid Tigray region,
the cold highlands > 3000 m in the
dry and wet eastern lowlands, and in
the humid areas in the South with
rainfall > 1500 mm
 More than 20% of sorghum is
cultivated in the semi-humid and
humid areas
AlbertGierend

9. Is sorghum more profitable than maize and if so, where?
 Gross margins (cash-cost) include costs
of seeds, pesticides, fertilizer, and hired
labour.
 Pairwise comparison of gross margins
ONLY for those grid cells where both
crops are grown.
 Graphs show gross margin differences
between sorghum and maize by LGP for
the 2014/15 Meher season.
 Positive values show where sorghum
has a higher gross margin than maize
 On a cash-cost basis, sorghum is more
profitable than maize across a range of
AEZs.
 On a full-cost basis, sorghum is more
profitable than maize in arid and dry
semi-arid AEZs.
AlbertGierend

10. Objectives:
 Verify adoption and diffusion of new varieties for selected priority countries
and food crops in SSA
 Minimize time and cost of future adoption studies
Comparative analysis of adoption patterns across
ESA, WCA and Asia
KaiMausch,FranklinSimtowe
0%
10%
20%
30%
40%
50%
60%
70%
Kenya Malawi Tanzania Uganda Zambia Kenya Malawi Tanzania Kenya Tanzania Sudan
Groundnut Pigeonpea Sorghum
% Area MVs

11. Methods:
 Compare community, expert-based
and survey estimates of adoption
Results:
 Mixed results - Tanzania: no
correlation: experts, household
and community; Malawi: better
match: experts and households
 Experts overestimate adoption of
widely adopted varieties and
underestimate adoption of less
common ones
MV pigeonpea, Tanzania
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
household community Expert
Source: Walker, T. and Alwang, J. (eds.) (2015). Crop Improvement, Adoption, and Impact
of Improved Varieties in Food Crops in Sub-Saharan Africa, CAB International,
Wallingford, UK.
KaiMausch,FranklinSimtowe

12. KaiMausch,DaveHarris,UniversityofBangor
Smallholder income diversity and effects on
technology preferences and adoption
Research problem:
 “Smallholders” a diverse group
 Growing reliance on off-farm,
especially non-farm, employment
 Reduced demand for new
agricultural technologies to meet
basic needs?
Objective:
• Understand motives, incentives and
barriers for smallholders to adopt
new agricultural technologies
Methods:
• Household Survey, 2015

13.  Perceptions on importance and reliability of income sources vary
greatly
KaiMausch,DaveHarris,UniversityofBangor
 The
assumption is
that this will
influence the
technology
attributes
households are
looking for
• Influence on
decision
making will be
investigated in
2016
 Crop sales are ranked the most important income
source, but non-farm wage employment plays a
major role in livelihoods
 Aspirations are towards farming rather than moving
out of farming even though wage employment offers
important and stable income
Importance
(rank) of
income
sources
Increase
Decrease
No
change
Ambitions for
change in
engagement
by source
Preliminary results:

14. Research Question:
What is the post-harvest loss in quantity and quality of groundnuts
among smallholders, and how can we mitigate it?
Methods:
 2015: On-farm assessment of quantity loss with a small sample by
on-site enumerators and extension staff, in partnership with DARS.
 2016: Interviews with producers and buyers on value loss using
survey tool and analytical program developed by IFPRI and
ICRISAT.
 Methods in 2015 and 2016 complementary in scope and nodes of
value chain.
Post-harvest loss for Groundnuts in MalawiTakuTsusaka,HarryMsere,SeethaAnitha

15. Key results for 2015:
Quantity Loss
(% Weight)
Mchinji Lilongwe Kasungu Average Factors
Lifting 22.9 9.8 6.8 14.9 hoe damage, weed, theft
Drying & Stripping na 2.3 17.3 4.3 spillage (children), eating, rodents
Transport to Homestead 0.20 0.66 0.02 0.29 torn sacks, no use of sacks on ox-cart
Sum ~27.4 12.8 24.2 19.4
Value Loss (US$/ha) 113 63 104 76
Aflatoxin in crop
sample (ppb)
Mchinji Lilongwe Kasungu Average Factors
After Drying 1.08 0.54 na 0.87 termite, hoe damage, post-harvest rainfall
After 1-month Storage 0.68 1.80 0.16 0.88 storage condition (humidity, temperature)
Value Loss (US$/ha) Will be studied in 2016 using price-differential tool
Significant loss in quantity. The extent and factors differ by district.
TakuTsusaka,HarryMsere,SeethaAnitha

16. What do we mean by ‘women’s crops’?
A mixed methods approach
Research question: does
commercialization of ICRISAT’s
mandate crops disempower women?
Methods:
Development of ‘Women’s Crop
Tool’, tested with:
1. FGDs with groundnut seed-
producer groups, with and without
access to the machine sheller (2014)
2. Household survey of groundnut
growers with and without access to
machine sheller (2014, 2015)
Location: Eastern Province, Zambia
The Women’s Crop Tool
A.Orr,T.Tsusaka,S.HomannKee-Tui,HarryMsere

17. Dependent Variable: Women’s Gender Control Index (WGCIf) for groundnuts
Treatment Variable: Sheller Group (yes=1)
Variable Coefficient t-statistic p-value
Sheller Group (yes=1) 6.56 *** 3.17 0.002
Area planted to groundnuts 1.82 1.37 0.172
Spouses of same religion (yes=1) 0.88 0.41 0.681
Husband has official position in EPFC group (yes=1) -2.00 -0.53 0.594
Wife has official position in EPFC group (yes=1) 1.80 0.48 0.632
Polygamy (yes=1) 10.71 ** 2.31 0.022
Sum of age 0.11 ** 2.00 0.047
Gap in age (age of husband – age of wife) -0.37 ** -1.79 0.076
Sum of experience with groundnuts -0.11 -1.42 0.157
Gap in experience with groundnuts
Experience of husband – experience of wife)
0.09 0.28 0.782
Household size -0.37 -0.74 0.462
Household adult female ratio -31.60 ** -1.71 0.089
Area planted to improved seed, all crops (%) -8.57 ** -2.16 0.033
Constant 59.69 5.68 0.000
Household survey results, 2014-2015:
Access to a machine sheller increases women’s control over
groundnuts…
A.Orr,T.Tsusaka,S.HomannKee-Tui,HarryMsere

18. 0
20
40
60
80
Area
planted
Land
preparation
Hired labour
Weeding
Inputs
Harvesting
Selling
Use of
income
Focus Group Discussions
Groundnuts Cotton
Maize Sunflower
Results
1. Both men and women perceived
groundnuts as a women’s crop.
2. Different perceptions between men
and women on degree of women’s
control.
3. Women with access to machine
sheller perceived they had greater
control over shelling, marketing and
use of income.
4. Women willing to trade some control
in exchange for men’s help with
shelling and higher income from
groundnuts.
5. These are short-run effects. Future
research will focus on longer-term
consequences.
Orr, Tsusaka, Homann Kee-Tui & Msere (in press). What do we mean by women’s crops?
Commercialisation, gender and the power to name, Journal of International Development
A.Orr,T.Tsusaka,S.HomannKee-Tui,HarryMsere
Tsusaka, Msere, Orr & Homann Kee-Tui "Do Mechanization and Commercialization
Disempower Women Farmers? Panel Evidence from Malawi and Zambia“. Accepted
for American Association of Agricultural Economists Conference, 2016.

19. Plans for 2016
Foresight Analysis & Priority Setting
Value Chains for Sorghum and Millets in ESA. Priorities for the CGIAR Research Program for
Dryland Cereals. A. Orr, A. Gierend, D. Choudhary (CGIAR Research Program, DC)
Smallholder Value Chains as Complex Adaptive Systems: Case studies. A. Orr, J. Donovan
(ICRAF), D. Stoian (Bioversity), R. Lamboll (NRI) (CGIAR Research Program, PIM)
Typology for subsistence- and market-oriented smallholders, Tanzania, Ethiopia.
K. Mausch, A. Orr + 2 MSc. Students (BEAF)
Adoption
Baseline Survey, Feed the Future, Kenya. D. Choudhary, K. Mausch (USAID)
Smallholder Income Diversity and Adoption. K. Mausch, D. Harris (CGIAR Research Program,
PIM)
Verifying adoption rates using DNA fingerprinting, selected TL3 crops & countries. K. Mausch
(TL3, BMGF)
Tracking adoption by seed distribution, and farmer feedback on small seed packs, Ethiopia.
A. Gierend (HOPE 2, BMGF)

20. Plans for 2016
Adoption (cont.)
Synthesis of adoption constraints for sorghum and millets, target countries. A. Gierend, A.
Orr (HOPE 2, BMGF).
Gender-Plus
Gender disaggregated impact for selected TL3 crops & countries. K. Mausch (TL3, BMGF)
Gender and commercialization, using experimental games. T. Tsusaka, A. Orr (CGIAR
Research Program, PIM)
Post-harvest losses
Producer and buyer survey on groundnut post-harvest losses. T. Tsusaka (CGIAR Research
Program, PIM)
Farmer sensitization and post-harvest technology demonstration for NASFAM, FUM, and
ICRISAT groundnut producers. T. Tsusaka (McKnight Foundation)