Case Study

Tailored, climate-informed and location-specific agro-advisory services in the highlands of Ethiopia increased smallholder farmers’ wheat grain yields and profitability

A location-specific, tailored, season-smart agro-advisory decision support tool (DST) in the Highlands of Ethiopia increased wheat yields of smallholder farmers by up to 25% with an average partial profitability of USD 600 per ha per season. The data-driven DST was developed by integrating over 25,000 crop responses to fertilizer application datasets and corresponding biophysical co-variants, using machine learning algorithms. Currently, the DST is being piloted across the highlands of Ethiopia. Documented here, as part of INIT EIA Excellence in Agronomy.