Integrated assessment of the determinants of the maize yield gap in Sub-Saharan Africa: towards farm innovation and enabling policies

Lead Research Organisation: Wageningen University
Department Name: Dept. of Plant Sciences

Abstract

Yield gaps estimations and explanations provide important information on the scope for production increases on existing agricultural land through better farming systems, farm management and enabling policies. The aim of this project is to develop and implement a framework that identifies the key bio-physical and management factors that influence the maize yield gap in SSA and how these are related to existing institutional, infrastructural, socio-economic and policy constraints. The research focuses on the major food crop in SSA, maize, mainly produced by small scale farmers. Maize is an important food crop in almost all Sub-Saharan African countries. Addressing yield performance in maize is therefore valuable from both a food security and poverty perspective. The project will focus on Ghana and Ethiopia as maize-growing case study countries where it builds on existing data and local partnerships. It is assumed that enhanced understanding for these two countries from West and East Africa will have wider meaning.

The innovative part of this project is the use of a framework that integrates agronomic and economic approaches to assess the yield gap and analyse agricultural performance at the farm and plot level. The analysis consists of three stages. In the first stage crop growth and economic production models are used to calculate potential, technical efficient ('best practice') and economic ceiling yields at the national and regional level, which are subsequently combined with actual yield data from surveys to compute the various yield gaps. In the second stage, econometric techniques are used to analyse variations in the observed yield gaps in space and relate them to plot-level, farm-level and context determining factors. In the third stage, a small number of local case studies are organised at the village level to deepen the analyses and to thoroughly understand the determinants of yield gaps to allow identification of farm and management innovations and policy interventions.

Information on yield potentials and actual yields will be taken from the Global Yield Gap Atlas (GYGA) that is currently being developed by University of Nebraska, Wageningen University and many partners from SSA. Farm/household level data and plot level information for Ethiopia and Ghana will be taken from the World Bank's Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) and EGC-ISSER Ghana (expected to become available end of 2013). In addition, a survey in each of the case-study regions will be organised to collect additional and detailed information on plot-level crop production and management such as soil characteristics, cultivation history and agronomic management.

The results will be used to derive targeted policy and farming recommendations that account for the complex environments in which male and female farmers in the SSA-region operate and incorporate the basic mechanisms that link farm performance to the broader enabling environment. This process will be supported by initiating participatory on-farm demonstration trials on the one hand and a policy dialogue with stakeholders on the other hand.

Planned Impact

The research will benefit:
(1) Local and national policymakers and planners in Ghana and Ethiopia that are responsible for agricultural policy formulation in the target countries.
(2) National agricultural research institutes that partner in the project.
(3) Farmers and national/regional farmers associations, in particular those that are active in the target regions and countries.
(4) International donors that support agricultural development in the target countries.
(5) International institutions and research organisations that are engaged in future assessments of food security, climate change and economic development.

How will they benefit from this research?
(1) The identification of major constraints and drivers of agricultural performance will provide policymakers with essential information to design targeted interventions at farm management and policy level that may narrow the yield gaps in the study regions and the wider economy. Yield gap estimations will also provide policymakers with information on the potential to increase maize production in the future and the implications for future food security in the region.
(2) Participating in the project will contribute to the capacity of national agricultural research institutes to combine socio-economic and bio-physical theories and approaches to analyse yield gaps and agricultural productivity.
(3) Through their engagement in village level demonstrations, farmers and extension agents will acquire useful information and knowledge on improved practices, leading to the adoption of these practices and ultimately higher agricultural productivity. farmers will benefit from enhance agricultural support policies.
(4) International donors can use the outcomes of the research to better target their agricultural and food security initiatives.
(5) It is expected that the framework to integrate bio-physical and economic approaches to yield gap analysis that will be applied and deepened in this project can also be applied to other regions and countries. It would be interesting to explore possibilities to combine this framework with existing integrated global and national models to assess future land use, climate change and food security (e.g. GTAP, IMPACT and IMAGE).

What will be done to ensure that they have the opportunity to benefit from this activity?
Information on promising options for improved farm management will be communicated to farmers and agricultural extension agents who are the primary actors operating at farm level in the case study sites. Joint learning by researchers, farmers and extension agents will be fostered through on-farm demonstration trials and field visits during which the trialled options are evaluated and discussed.
For policy makers, information on where yield gaps are large, potential areas where yield gaps can be narrowed relatively easily, and the necessary policy interventions and enabling institutions, are critical. The project will engage with policy makers by providing a platform for them to access this information and share and discuss it with other stakeholders such as farmer representatives, public and private sector agents, NGOs and local and international researchers. This will encourage mutual understanding, lead to better targeting of necessary policy interventions and ultimately to socio-economic-institutional environments that are more conducive to high agricultural productivity. In total two roundtables (each in one of the case-study countries) will be organised with policy makers and other stakeholders.
Besides the engagement activities, which form the core of our strategy to impact, farmers and extension agents will be informed through leaflets and radio broadcasts on good management practices. Furthermore, country-specific policy briefs in which the main findings and policy recommendations are summarised will be prepared.
 
Description The project had a methodological and an applied focus. We argue that the methodological component of the project was very successful, i.e. we developed a generic, multi-scale analytical framework to decompose and understand the causes of maize yield gaps from an integrated biophysical and socio-economic perspective. We also linked the different components and causes of yield gaps to technological and policy interventions to overcome or narrow yield gaps. This methodological framework is of broad applicability, also beyond Ethiopia and Ghana, and fills an important niche as to yield gap analysis and analysing pathways for sustainable intensification of crop production. We already experienced significant interest in our framework developed in the IMAGINE project. The methodology has been published in a scientific paper (Van Dijk et al., 2017) and a second, more comprehensive manuscript on the methodology and an application for Ethiopia is ready for submission (but, see also below). We conclude from the analysis that for Ethiopia the economic yield gap (40%) makes up the largest component of the yield gap, followed by the technology yield gap (38%), the allocative yield gap (11%) and the technical efficiency yield gap (10%). For Ghana the technology yield gap makes up the largest component of the total yield gap, followed by the economic yield gap, the allocative yield gap and the technical efficiency yield gap. For two specific regions in both Ethiopia and Ghana, we performed more detailed analyses on the causes of maize yield gaps and possible mitigation options, using a combination of farm household surveys and on-farm demonstrations focusing on specific technological options (fertilizer rates, cultivars and planting density). In regions with low yields and low inputs, the influence of different factors was difficult to disentangle because of interacting effects, but regions with higher inputs and yields showed significant effects of fertilizers, which was also confirmed by the demonstrations. Demonstrations also showed that yields much closer to the water-limited potential can be achieved with improved planting density and cultivars. Results confirmed that yields can only be increased with multiple changes in management.
There is an important BUT as to the national applications of the project methodology, which rely on data derived from the LSMS survey of the WorldBank (Ethiopia) and Yale University (Ghana). We discovered important data quality problems as to the national level data for Ghana in year 2 of the project, and very recently (just two months ago) we discovered there are also problems with the data for Ethiopia. In short, this relates to misreporting units of fertilizer use, field areas and yields (amongst other variables that also comprise misreporting) in part of the data which represent important strata of the entire sample. The finding is an important outcome of the project itself: LSMS data have been and are widely used in the research community, and dozens of papers based on these data have been published. We have evidence that much of the results in these papers are substantially affected by the problem we identified. We are currently preparing a publication to report and analyse the problems of the LSMS data. As we discovered the data problem late in the project it is hindering the (timely) publication of our national analyses. For Ghana a peer-reviewed publication is not possible; for Ethiopia we still hope to submit a largely methodological paper that uses the data for illustration only.
Exploitation Route The framework developed in IMAGINE to analyse yield gaps will be applied in follow-up research projects, and used in teaching. Academics can now use the framework as an operational approach that integrates economic and agronomic yield gap measurement, using survey data. We showed that a combination of surveys, experiments, crop modelling and statistical techniques enables a deeper understanding of maize yield gaps. In Ethiopia, two new PhD students are applying the framework and combined methods in deepening the analysis for maize. As data and code are all open-source, others can easily use it, and the increasing amount of data becoming available globally will also help in operationalizing the framework. The Global Yield Gap Atlas will act as a global network to help spread the findings and approaches developed.
The on-farm demonstrations exposed farmers and extension agents to various options to narrow maize yield gaps. The large number of visiting farmers is a good basis for further uptake of the demonstrated technologies.
Through the policy workshops and briefs, policy makers and extension workers have been made familiar with the integrated assessment, the factors explaining yield gaps, and the resulting policy and farm management recommendations. We expect them to use this knowledge in future policy making and farmer advisory. We anticipate the engagements contributed to the realization by policy makers and extension officers that integrated measures are needed, as yield gaps can only be reduced if multiple changes are made, both at the policy level and the farm management level.
Follow-up research projects (e.g. the Crop Nutrient Gap and TAMASA projects) are actively continuing and deepening the stakeholder interactions through additional policy workshops, and on-farm and on-station experiments.
Sectors Agriculture, Food and Drink

 
Description Two policy workshops were organized in Ethiopia, in April 2017 and January 2018, and one in Ghana in December 2017, with regional stakeholders from the two study regions. The first workshop in Ethiopia had 24 attendees, and the second 30. Policy makers expressed interest in follow-up workshops in relation to related projects TAMASA and Crop Nutrient Gaps. As a direct follow-up and outcome, our collaborator in Ethiopia was invited two times in March 2018 by the Minister of Agriculture to present the results of the project; the 2nd time to the annual national development agent training of trainers (>300 participants). We were asked for follow-up presentations to trainings organized in Oromia, Amhara and Southern Nations and Nationalities regional states. The policy workshop in Ghana had 49 attendees. The latter was published on the website of the government of Ghana: http://www.ghana.gov.gh/index.php/media-center/news/4266-isser-hosts-roundtable-policy-workshop-on-reducing-maize-yield-gap. In addition, two policy briefs were published and disseminated in Ethiopia and Ghana. Later, in December 2018, an additional policy brief was published and disseminated in Ethiopia (https://ccafs.cgiar.org/publications/can-ethiopia-feed-itself-2050-estimating-cereal-self-sufficiency-2050#.XH-O5hJ7mUk). Further, a high level delegation from Ethiopia visited Wageningen in 2018, and the concepts and results from IMAGINE were presented. In general, the concept of yield gaps, indicating the scope for yield increase, is gaining much visibility. The paper by Van Ittersum et al. (2016), 'Can Sub-Saharan Africa feed itself?' in PNAS has received much media attention across the globe. The application of the framework by Van Dijk et al. (2017) for Ethiopia has been extended by emphasizing the link to policies, and presented in the policy workshops. Policy makers and extension officers start to realize that integrated policies are needed, as yield gaps can only be reduced if multiple changes are made, both at the policy level and the farm management level. To show the effect which needs to be made at farm management level, in both Ethiopia and Ghana demonstration experiments have been held in 2016 and 2017. During those experiments farmers have been exposed to different cultivars, fertilizer regimes, planting densities, to evaluate yields and (dis)advantages of different treatments. In Ghana, a total of visits of 713 persons have been made, and the attendance in Ethiopia was at a similar high level. Farmers indicated that they are very interested in trying the different treatments on their fields, but that they needed some support for this. Three new research projects build upon the work of the IMAGINE project or take the work forward, also with extensive interactions with users and stakeholders (both public and private sector): 1. A project funded by CCAFS (one of the CGIAR CRPs) "Bringing climate-smart agricultural practices to scale: assessing their contributions to narrow nutrient and yield gaps" on the necessary nutrient requirements and climate-smart management to increase maize productivity in Ethiopia (and Kenya and Tanzania); 2. A project funded by the Dutch science foundation "Understanding and improving scaling readiness of climate smart, nutrient management Decision Support Tools" on nutrient management decision support tools and their scaling readiness in Ethiopia and Tanzania; 3. A project funded by CIMMYT-Wheat on " Disentangling agronomic and economic yield gaps in Ethiopian wheat based systems for better targeting of development interventions" in which IMAGINE methods are extended to wheat crops.
First Year Of Impact 2017
Sector Agriculture, Food and Drink
Impact Types Policy & public services

 
Title Demonstration trails Ghana 
Description Field book for demonstration trails, Ghana 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Household Questionnaire Ethiopia, 2015 
Description This research tool facilitates the recording of household and agronomic data for maize produciong households in Ethiopia. The questionnaire is developed in such a way that records can be used by another research project (TAMASA; see collaborations). 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact Sharing of data with another research project is enhanced. 
 
Title Household Questionnaire Ghana 2015 
Description This research tool facilitates the recording of household and agronomic data for maize produciong households in Ghana. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Household questionnaire Adami Tulu, Ethiopia 2016 
Description This research tool facilitates the recording of household and agronomic data for maize produciong households in Ghana. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Household questionnaire Bako Tibe, Ethiopia 2016 
Description This research tool facilitates the recording of household and agronomic data for maize produciong households in Ethiopia. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact N/A 
 
Title Household questionnaire Ghana, Nkoranza minor season 2016 
Description This research tool facilitates the recording of household and agronomic data for maize produciong households in Ghana. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Household questionnaire Nkoranza, Ghana major season 2016 
Description This research tool facilitates the recording of household and agronomic data for maize produciong households in Ghana. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Village Questionnaire Ethiopia 
Description This tool facilitates the recording on facilities, inititatives and commodity prices in a village in Ethiopia 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Village Questionnaire Ghana 
Description This tool facilitates the recording on facilities, inititatives and commodity prices in a village in Ghana. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact NA 
 
Title Yield Gap Note 
Description This method provides an integrate dframework that is aimed to disentangle agronomic and economic yield gaps. 
Type Of Material Improvements to research infrastructure 
Provided To Others? No  
Impact In the course of creating the framework, collaboration between agronomic and economic research has been intensified. Preliminary results show that some agronomic yield gaps will never be bridged due to economic circumstances, which emphasizes the need for an integrated approach. 
 
Title Demonstration experiment Adami Tulu, Ethiopia 2016 
Description Demonstration experiment Adami Tulu, Ethiopia 2016 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The demonstration experiment led to farmer awareness on several Agricultural practices. 
 
Title Demonstration experiment Bako Tibe, Ethiopia 2016 
Description Demonstration experiment Bako Tibe, Ethiopia 2016 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The demonstration experiment led to farmer awareness on several Agricultural practices. 
 
Title Demonstration experiment Savelugu, Ghana 2017 
Description Demonstration experiment Savelugu, Ghana 2017 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The demonstration experiment led to farmer awareness on several Agricultural practices. 
 
Title Demonstration experiment dataset Ghana Nkoranza 2016 
Description Demonstration experiment dataset Ghana Savelugu 2016 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The demonstration experiment led to farmer awareness on several Agricultural practices. 
 
Title Demonstration experiment dataset Ghana Savelugu 2016 
Description Demonstration experiment dataset Savelugu 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact N/A 
 
Title Demonstration experiment dataset Nkoranza, Ghana 2017 
Description Demonstration experiment dataset Nkoranza, Ghana 2017 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact The demonstration experiment led to farmer awareness on several Agricultural practices. 
 
Title Demonstration experiments Ethiopia 2017 
Description Demonstrations have been performed on-farm in Bako Tibe and Adami Tulu, analyzing influence of variety, planting density, fertilizer management and tied ridges on maize yield. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
Impact Data are analyzed and will be published in a peer-reviewed paper. Farmer field days have been held to discuss the different treatments. Some of the farmers adapted their practices after having observed the demonstrations. In on-going projects, additional experiments will be performed in the same villages. 
 
Title Household dataset Ethiopia 2015 
Description Household survey in Ethiopia with 80 farmers. 40 in Bako Tibe and 40 in Adami Tulu. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact N/A 
 
Title Household dataset Ethiopia 2016 
Description Household survey among 80 farmers in Ethiopia, 40 in Adami Tulu and 40 in Bako Tibe. 
Type Of Material Database/Collection of data 
Year Produced 2016 
Provided To Others? No  
Impact N/A 
 
Title Household dataset Ghana 
Description Dataset with 90 household observations in two areas in Ghana. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact NA 
 
Title Household dataset Ghana major season Nkoranza 2016 
Description Household dataset Ghana minor season Nkoranza 2016 of 45 households. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact N/A 
 
Title Household dataset Ghana minor season Nkoranza 2016 
Description Household survey conducted at 45 households in Nkoranza, Ghana during the minor season in 2016 on plot level characteristics 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact N/A 
 
Title Soil sample data set Ghana 
Description Collection of soil samples from maizefields from 90 households in Ghana 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact More precise estimation of soil quality 
 
Title Soil sample report generator 
Description This model supports the generation of multiple soil sample reports at once. 
Type Of Material Data handling & control 
Year Produced 2016 
Provided To Others? Yes  
Impact The process of feeding back soil sample reports to individual farmers is improved. 
URL https://www.researchgate.net/publication/293816753_Soil_sample_report_generator_using_R_facilitating...
 
Title VSA in ODK 
Description This model and database processes and records results from FAO's Visual Soil Assessment together with images and geo-locations. 
Type Of Material Data handling & control 
Year Produced 2016 
Provided To Others? Yes  
Impact Availability of geo-locations of soil sampling helped to improve the soil sampling strategy of field workers. Processed data was stored safely directly after the field work was finished. 
URL https://www.researchgate.net/publication/293649999_FAO%27s_Visual_Soil_Assessment_in_ODK_Using_table...
 
Title Village dataset 
Description Dataset of 6 villages on facilities, innovation groups and commodity prices in maize producing villages. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact NA 
 
Title Yield sample dataset Ghana 
Description Actual maize yield data from fields of 90 households in Ghana. 
Type Of Material Database/Collection of data 
Provided To Others? No  
Impact More precise estimations of yields. 
 
Description Crop Nutrient Gaps 
Organisation International Centre for Maize and Wheat Improvement (CIMMYT)
Country Mexico 
Sector Charity/Non Profit 
PI Contribution PPS-WUR is leading the Crop Nutrient Gaps project. The project assess nutrient gaps related to yield gaps in Ethiopia, Tanzania and Kenya. Especially for Ethiopia, there was a strong collaboration between IMAGINE and Crop Nutrient Gaps. Kindie Tesfaye from CIMMYT was also involved in both projects.
Collaborator Contribution Partners provided insights which helped us to improve the assessments in IMAGINE.
Impact Outputs of the Crop Nutrient Gaps project are listed on the website, and published on www.yieldgap.org.
Start Year 2016
 
Description Crop Nutrient Gaps 
Organisation University of Nebraska–Lincoln
Country United States 
Sector Academic/University 
PI Contribution PPS-WUR is leading the Crop Nutrient Gaps project. The project assess nutrient gaps related to yield gaps in Ethiopia, Tanzania and Kenya. Especially for Ethiopia, there was a strong collaboration between IMAGINE and Crop Nutrient Gaps. Kindie Tesfaye from CIMMYT was also involved in both projects.
Collaborator Contribution Partners provided insights which helped us to improve the assessments in IMAGINE.
Impact Outputs of the Crop Nutrient Gaps project are listed on the website, and published on www.yieldgap.org.
Start Year 2016
 
Description Crop Nutrient Gaps 
Organisation Yara (UK) Ltd
Country United Kingdom 
Sector Private 
PI Contribution PPS-WUR is leading the Crop Nutrient Gaps project. The project assess nutrient gaps related to yield gaps in Ethiopia, Tanzania and Kenya. Especially for Ethiopia, there was a strong collaboration between IMAGINE and Crop Nutrient Gaps. Kindie Tesfaye from CIMMYT was also involved in both projects.
Collaborator Contribution Partners provided insights which helped us to improve the assessments in IMAGINE.
Impact Outputs of the Crop Nutrient Gaps project are listed on the website, and published on www.yieldgap.org.
Start Year 2016
 
Description ISRIC soil samples 
Organisation The Global Health Network
Department International Severe Acute Respiratory Infection Consortium (ISARIC)
Country United Kingdom 
Sector Charity/Non Profit 
PI Contribution Sharing of soil sample results.
Collaborator Contribution Giving feedback on soil sampling strategy
Impact No outputs yet
Start Year 2015
 
Description SIMLESA data 
Organisation International Centre for Maize and Wheat Improvement (CIMMYT)
Country Mexico 
Sector Charity/Non Profit 
PI Contribution We aim to help with data analysis of interesting datasets on maize production in Ethiopia.
Collaborator Contribution Co-authoring scientific articles.
Impact Not applicable yet
Start Year 2015
 
Description TAMASA (Taking Maize Agronomy to Scale in Africa ) 
Organisation International Centre for Maize and Wheat Improvement (CIMMYT)
Country Mexico 
Sector Charity/Non Profit 
PI Contribution TAMASA asked us to host 2 sandwich PhD students, focussing on Ethiopia. Their work will be aligned with IMAGINE
Collaborator Contribution Household surveys of IMAGINE and TAMASA will be aligned, to make most out of both.
Impact Aligned Household surveys. PhD theses will produced, and peer-reviewed articles. Capacity building by delivering two doctors.
Start Year 2015