JULIO CEZAR SOUZA VASCONCELOS, FUNDAÇÃO DE APOIO A PESQUISA E AO DESENVOLVIMENTOEDUARDO ANTONIO SPERANZA, CNPTIAJOAO FRANCISCO GONCALVES ANTUNES, CNPTIALUIZ ANTONIO FALAGUASTA BARBOSA, CNPTIADANIEL CHRISTOFOLETTI, COOPERATIVA DOS PLANTADORES DE CANA DO ESTADO DE SÃO PAULOFRANCISCO JOSÉ SEVERINO, COOPERATIVA DOS PLANTADORES DE CANA DO ESTADO DE SÃO PAULOGERALDO MAGELA DE ALMEIDA CANCADO, CNPTIA.2026-07-07http://hdl.handle.net/123456789/456521This study aimed to develop a predictive model for sugarcane production based on data extracted from aerial imagery obtained from drones or satellites, allowing the precise tracking of plant development in the field.openAccessAgricultura digitalInverse Gaussian distributionModelo preditivoDistribuição gaussiana inversaRemotely piloted aircraft systemsRPASDigital agricultureSaccharum OfficinarumCana de AçúcarSugarcaneModelsVegetation indexDevelopment and validation of a model based on vegetation indices for the prediction of sugarcane yield.Artigo de periódico