From scattered agronomic data to smarter fertilizer management decisions: A new chapter for maize productivity in Kenya
CGIAR, the Alliance of Bioversity International and CIAT, IITA and KALRO launched a Kenya-wide initiative in 2025 to rescue and harmonize agronomic data, using AI to develop site-specific maize fertilizer recommendations that boost yields, efficiency and sustainability.
- Africa
- Digital innovation
- Maize
From scattered agronomic data to smarter fertilizer management decisions: A new chapter for maize productivity in Kenya
CGIAR, the Alliance of Bioversity International and CIAT, IITA and KALRO launched a Kenya-wide initiative in 2025 to rescue and harmonize agronomic data, using AI to develop site-specific maize fertilizer recommendations that boost yields, efficiency and sustainability.
In August 2025, a quiet but ambitious journey began, one poised to transform how farmers across Kenya can improve productivity through making some of the most critical decisions in fertilizer management. To bring this vision to life, CGIAR (through the Alliance of Bioversity International and CIAT and IITA) partnered with KALRO to move beyond “blanket” recommendations toward truly site-specific guidance, considering applying the right nutrients, at the right rate in the right time and place, for the right crop. At the heart of this effort was a simple but powerful idea: bring together decades of agronomic data and turn it into actionable insights.
What followed was a monumental effort that went far beyond simply compiling datasets. Agronomic trial data, often scattered across institutions, stored in different formats, archived in aging computers, tucked in forgotten folders, or at a risk of being lost when projects end or researchers retire.
Recovering this valuable scientific legacy required a true data rescue mission; contacting the retired scientists to retrieve datasets and clarify historical data entries, engaging project leaders to fill critical knowledge gaps, and reconstructing or georeferencing trial locations to restore their spatial context, For decades, this fragmented data landscape limited the ability to generate meaningful, largescale insights that could inform agricultural decision making. Through the combined efforts of agronomists, data scientists, statisticians, geospatial analysts, and ICT experts from KALRO and CGIAR, these datasets were cleaned, standardized, and harmonized into a unified, analysis-ready structure. The result was more than a technical achievement; it was the transformation of decades of disconnected research into a powerful foundation for innovation, evidence-based recommendations, and next-generation digital advisory tools.