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Article Abstract
Identifying untapped opportunities for crop production improvement in current cropland is crucial to guide food availability interventions. Here we integrated an agronomically robust bottom-up approach with machine learning to generate global maps of yield potential of high resolution (ca. 1 km at the Equator) and accuracy for maize, wheat and rice. These maps serve as a robust reference to benchmark farmers' yields in the context of current cropping systems and water regimes and can help to identify areas with large room to increase crop yields.
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