Wheat farmers in Ethiopia achieve up to 38% higher yields with machine-learning-based fertilizer recommendations
In Ethiopia, wheat farmers are boosting yields by up to 38% after researchers and partners validated machine-learning-based fertilizer recommendations across multiple regions, replacing blanket advice with site- and season-specific guidance that improves incomes and resilience.
- climate change
- Climate-Smart Agriculture
Wheat farmers in Ethiopia achieve up to 38% higher yields with machine-learning-based fertilizer recommendations
In Ethiopia, wheat farmers are boosting yields by up to 38% after researchers and partners validated machine-learning-based fertilizer recommendations across multiple regions, replacing blanket advice with site- and season-specific guidance that improves incomes and resilience.
For decades, Ethiopian farmers faced the same challenge: fertilizer recommendations that treated the country’s diverse landscapes as if they were all the same. These “blanket” prescriptions ignored differences in soils, climates, and cropping systems, often leading to disappointing harvests and wasted resources.
While well-intentioned, the one-size-fits-all approach widened yield gaps and left smallholders struggling to make farming both profitable and sustainable.
Yet, that story is now changing.