Acknowledgements
This poster is made possible by the support of the American People provided to the Feed the Future Innovation Lab for
Sustainable Intensification through the United States Agency for International Development (USAID). The contents are the
sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government.
Program activities are funded by USAID under Cooperative Agreement No.AID-OAA-L-14-00006.
Raising Crop Response: Bidirectional Learning to Catalyze Sustainable Intensification at Multiple Scales
Team:
Dr. Sieg Snapp, Professor Plant Soil Microbial Sciences, Michigan State University
Dr. Thom Jayne and Dr. Nicky Mason, Ag. Economists, Michigan State University
Dr. Hamisi Tindwa, Lecturer, Applied Soil Biology, Sokoine University of Agriculture
Dr. Ken Giller, Professor, Plant Production Systems, Wageningen University
Mr. Jean-Claude Rubyogo, Seed Systems Scientist, CIAT-Tanzania
Mr. Jovin Lwehabura , SIIL-EA coordinator CIAT-Tanzania
Dr. Neema Kassim, Dept. Food Biotechnology and Nutritional Sciences
Prof. Mateete Bekunda, IITA ESA Africa RISING
Domain Scale Indicators
Productivity Regional (600 households,
southern & northern
highlands), local (field trials)
Yield
Yield variability
Fertilizer response
Economics Country-wide survey,
regional
Profit
Profit variability
Environ-
mental
Regional, local (field trials) Soil organic matter
Nitrogen Fixation
Human
Condition
Country, regional, local Nutrition
Food security
Social Southern highlands
bidirectional
experimentation, local
Extension Advice, Farmer
engagement
Gender aware advice
Objective: Improved knowledge of the nutrition impacts of adoption of SI.
Figure 3. Sustainable intensification indicators including per capita income, yield and child health
gains among farmers who use improved (intensified, sustainable and SI) practices relative to
farmers who don’t employ improved maize production practices, as indicated by height and weight
for age scores, based on panel survey data from Tanzania-wide representative household survey.
The data is being processed still, so this indicative not final findings.
Results: A marked effect of sustainable practice was observed for income and child nutrition on
farms where sustainable, and sustainable intensified maize production practices were employed
across the farm. The primary sustainable practice consisted of maize-legume intercrops, along with
manure or compost amendment in some cases, and fertilizer was the primary intensification
practice. There were income gains associated with these practices in most cases due to yield
improvements, however this data still requires quality checks.
This will require further study, to elucidate the mechanisms involved whereby SI practices are
associated with less stunting and growth gains along with income benefits.
Next Steps
Findings reported here are preliminary and should not be cited as yet, considerable data cleaning,
synthesis and evaluation of indicators involved in multiple domains all are in process.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Maize yield (Max =
3500Kg/ha))
Variability of Yield (Max
= 3)
Gross Margin (Max =
500000)
Percentage of maize sold
(max=100%)
Kg of N/Ha (Max
=50KgN/Ha)
% of food secure
households (Max =1)
Dietary Diversity
(Max=12)
Total cultivated area
(Max = 5)
Performance of households in Ludewa and Sumbawanga
Ludewa Sumbawanga
Figure 1. Vital Signs Example: This radar chart illustrates case study examples from Ludewa
and Sumbawanga, two village clusters in the Southern Agricultural Growth Corridor of
Tanzania chosen for monitoring by the Vital Signs project. Performance is shown for
representative households based on a range of SI indicators (unpublished data, Cheryl Palm
and colleagues, University of Florida).
Note that above radar chart was produced by C. Palm and M. Musumba and is included
here to illustrate how the Vital Signs project is evaluating performance indicators at two
sites in Tanzania. In our SIIL project in Tanzania we plan to use a similar mixed methods
approach, utilizing survey data along with modeling to evaluate performance of rural
households carrying out technological maize-based practices that vary in terms of
intensification, and sustainable management, at locations across Tanzania.
Figure 2. Africa RISING Malawi Example: This radar chart illustrates a case study
example from Golomoti, a village cluster in Central Malawi where three maize-based
systems are evaluated, sole maize unfertilized (Mz0), sole maize fertilized with 69 kg N
ha (MzNPK), pigeonpea-maize intercrop half rate fertilizer (PP-Mz) and groundnut-PP
doubled up legume rotated with maize fertilized quarter rate (DLR). Performance is
evaluated based on mixed methods, crop simulation modeling using APSIM, a panel
survey and agronomic performance from field experimentation (Snapp et al., in press).
Table 1. Indicator source and how data was calculated to generate
sustainable intensification performance evaluation shown in figure 2 for
four technologies in Golomoti, Central Malawi (Snapp et al., in press).
Figure 3. An example radar chart based on Tanzania IHHS panel survey. Domains include
Economic (per capita income proxy), Nutrition (Z-scores for ht and wt), and Productivity (farm
yield estimate) domains, I, S and SI farmer, data presented relative to farmers who use no
improved maize production practices.
-30
-20
-10
0
10
20
30
40
50
60
Income
Ht-for-age
Wt-for-age
Yield
Intensified
Sustainable
Sust. Intensified