Development and validation of a model based on vegetation indices for the prediction of sugarcane yield.

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Author(s): VASCONCELOS, J. C. S.; SPERANZA, E. A.; ANTUNES, J. F. G.; BARBOSA, L. A. F.; CHRISTOFOLETTI, D.; SEVERINO, F. J.; CANÇADO, G. M. de A.

Summary: This 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.

Publication year: 2023

Types of publication: Journal article

Unit: Embrapa Digital Agriculture

Keywords: Agricultura digital, Cana de Açúcar, Digital agriculture, Distribuição gaussiana inversa, Inverse Gaussian distribution, Modelo preditivo, Models, RPAS, Remotely piloted aircraft systems, Saccharum Officinarum, Sugarcane, Vegetation index

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