Taking Maize Agronomy to Scale in Africa (TAMASA) is a 4-year project (November 2014-October 2018) seeking to improve productivity and profitability for small-scale maize farmers in Ethiopia, Tanzania and Nigeria.

The overall purpose of TAMASA is to use innovative approaches to transform agronomy that:

  • Use available geospatial and other data and analytics to map maize areas, soil constraints, and actual and yields at different scale
  • Work with service providers (i.e. input suppliers, government and private research and extension services, agro-dealers, and others) to identify and co-develop systems and applications that transform this data and information to useable products that support their businesses or programs to reach clients more effectively
  • Build capacity in national programs to support and sustain these approaches

News & Updates feed

  • Digitalizing African Agriculture: Paving the way to Africa’s Progress Through Transforming the Agriculture Sector

    AGRF2019 discussed digital transformation as key driver of sustainable food systems in Africa By Simret Yasabu and Jerome Bossuet This year’s African Green Revolution Forum (AGRF), which took place from September 3-6, 2019 in Accra, Ghana, focused on the potential of digital agriculture to transform the African agriculture through innovations such as precision agriculture ...

  • Innovation, partnerships and knowledge for African farmers meet at AGRF 2018

    KIGALI, Rwanda (CIMMYT) — The African Green Revolution Forum (AGRF) is the place to be for organizations interested in Africa’s agricultural development. Research institutions, development agencies, funders, farmers’ organizations, large agribusinesses and green start-ups came together for the latest edition of this event in Kigali, Rwanda, on September 4-8. Organized ...

  • Are advisory apps a solution for collecting Big Data?

    Big Data is transforming the way scientists conduct agricultural research and helping smallholder farmers receive useful information in real time. Experts and partners of the CGIAR Platform for Big Data in Agriculture are meeting on October 3-5, 2018, in Nairobi, Kenya, to share their views on how to harness this ...


    The current R&D landscape, particularly in agronomy, is characterized by blanket recommendations, poor availability, and limited use of spatial data. There are few options for rapid and cost-effective data collection, the result being that agronomy remains experiential, rather than predictive, and that site-specific knowledge cannot be shared or easily scaled ...

  • How the data revolution could help design better agronomic investments?

    A spatial ex ante framework for guiding agronomic investments in sub-Saharan Africa, Sebastian Palmas and Jordan Chamberlin, CIMMYT Kenya Brown Bag, 4 March 2019.

  • Looking for a needle in a haystack: The trials and tribulations of spatial sampling frames

    Collecting and using large amounts of geo-referenced data, all part of so-called ‘big data’, is all the rage these days.  In TAMASA we have a spatial sampling frame for collecting household and farmer yield data, which on a map looks very neat and tidy, and eminently ‘doable’.  For example, in ...