Taking Maize Agronomy to Scale in Africa (TAMASA) is a four-year project funded by the Bill and Melinda Gates Foundation, seeking to improve productivity and profitability for small-scale maize farmers in Ethiopia, Tanzania and Nigeria. The project will run from November 2014 through October 2018.
Within each country, TAMASA’s activities are structured within a nested impact geography, consisting of four stratification levels:
- Maize area: defined as where maize is grown using the AfSIS crop mask, SPAM and national production statistics
- Maize-based systems: defined as areas within the maize area where >50% of the crop in more than half the seasons is maize
- Area of Interest (AOI): defined using intensification criteria of areas within maize-based systems where population density >25 km2and that are <4 hours travel time to an urban market.
- Focal areas (FA): defined as areas within the AOI where TAMASA and its primary partners will conduct research and deliver outputs and impact.
TAMASA’s activities are organized into seven sets of activities, called Workstreams, and are outlined below:
Workstream 1 addresses core data gaps. There are several components of this work:
- Collect georeferenced data on plot-level soil characteristics, agronomic management, and maize yields, supplemented by farm-level data on resources, management decisions and production outcomes. Much of these data will be collected on panel observations, i.e. repeated visits to the same plots in successive seasons over the duration of the project.
- Analyze the data collected, along with complementary data sources generated by other projects (e.g. LSMS-ISA data) to characterize management, input use and yields over time and space.
- To collect data within a centrally managed repository which is accessible by project researchers as well as national partners.
- To evaluate alternative data collection methods (e.g. mobile-camera-based yield estimates over crop cuts; UAV-based yield estimates), and promote such methods if/where they are cost-effective.
Workstreams 2 through 5 are focused on the development of decision-support tools.
Workstream 2 will establish a spatially-explicit framework for ex-ante analysis of alternative targeting of productive investment, e.g. where new fertilizer blends may be more profitable than existing blends.
Workstream 3 will establish working versions of a Nutrient Expert tool which will provide site-specific nutrient management advice to farmers. This work is done in collaboration with IPNI.
Workstream 4 will establish a tool for the selection of maize varieties most appropriate for particular geographic locations and specified trait requirements.
Workstream 5 consists of developing data to support the identification of opportunities for new fertilizer blends. This work is currently being done in Nigeria in collaboration with OCP.
Workstream 6 focuses on evaluating the actual and potential adoption and impact of the tools developed in Workstreams 2-5. Data collected under Workstream 1 (i.e. the agronomic panel survey) will be used to evaluate adoption via experimental methods. Within Workstream 6, there is also space for evaluating complementary agronomic and other interventions.
Workstream 7 consists of project management activities. Within this Workstream are included monitoring, evaluation and learning (ME&L) activities, communication, and collaborative management of training and research conducted by doctoral students who are sponsored by the project and who conduct their coursework at Wageningen University (Netherlands), Leuven University (Belgium) and Reading University (UK).