Machine learning algorithms for soybean yield forecasting in the Brazilian Cerrado.

Valter Barbosa Dos SantosAline Moreno Ferreira Dos SantosJose Reinaldo da Silva Cabral de MoraesIgor Cristian de Oliveira VieiraGlauco de Souza Rolim

Published in: Journal of the science of food and agriculture (2021)

All models had acceptable precision, accuracy, and trend indices, which makes it possible to use all algorithms to be applied in the prediction of soybean crop yield, observing the particularities of the region to be studied, in addition to being a useful tool for agricultural planning and decision-making in soy producing regions such as the Brazilian Cerrado. This article is protected by copyright. All rights reserved.

Keyphrases

machine learning
climate change
artificial intelligence
big data
deep learning
risk assessment
heavy metals
water quality