G. Chehab

Predicting harvest productivity from field operations data: a random forest approach for the brazilian cerrado

Accurate pre-harvest yield prediction enables smarter logistics, targeted agronomic interventions, and evidence-based farm management. Most machine learning (ML) yield models rely on census-level statistics or satellite remote sensing; per-field, per-operation management records remain largely not analyzed as a predict...