Raphael B. A. Fernandes

Coupling Soil Testing Data with Machine Learning Algorithms to Predict Plant Responses to Phosphorus in Sub-Saharan Africa

A machine learning–based framework that integrates soil testing data, management practices, and climatic variables to improve estimates of plant responses to P fertilization is proposed and validated and Random forest presented a better predictive capacity for relative maize yield in response to P fertilization.