Site-specific fertilizer recommendation using data driven machine learning enhanced wheat productivity and resource use efficiency - Liben, Feyera; Abera, Wuletawu; Chernet, Meklit Tariku; Ebrahim, Mohammed; Tilaye, Amsalu; Erkossa, Teklu; Degefie, Tibebe Degefie; Mponela, Powell; Kihara, Job; Tamene, Lulseged D. (Elsevier, 2024)
Context Fertilizer use efficiency and profitability are very low due to blanket fertilizer recommendations in sub-Saharan Africa. It is crucial to establish tailored recommendations that account for local conditions. Countries like Ethiopia are moving towards adopting site-specific fertilizer recommendations (SSFR) that are developed using machine learning (ML) and designed to enhance yields, profitability, and environmental benefits.