Integrating Agronomy and Machine Learning to Analyze Yield Gap Magnitudes and Causes from Field to Global Levels.

Fernando Aramburu Merlos, Research Assistant Professor, Department of Agronomy and Horticulture, University of Nebraska Lincoln Author
05/25/2024 Added
1 Plays


Identifying untapped opportunities for crop production increase is crucial to guide food security interventions. In this presentation, Fernando will show how agronomic knowledge, big data, and machine learning can be integrated to map yield potentials at high resolution and identify agronomic practices that promptly deliver large on-farm yield gains.

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