Predicting soybean grain yield using aerial drone images.

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Author(s): ANDRADE JUNIOR, A. S. de; SILVA, S. P. da; SETUBAL, I. S.; SOUZA, H. A. de; VIEIRA, P. F. de M. J.; CASARI, R. A. das C. N.

Summary: This study aimed to evaluate the ability of vegetation indices (VIs) obtained from unmanned aerial vehicle (UAV) images to estimate soybean grain yield under soil and climate conditions in the Teresina microregion, Piaui state (PI), Brazil. Soybean cv. BRS-8980 was evaluated in stage R5 and submitted to two water regimes (WR) (100 and 50% of crop evapotranspiration - ETc) and two N levels (with and without N supplementation).

Publication year: 2022

Types of publication: Journal article

Unit: Embrapa Mid-North

Keywords: Aeronave remotamente pilotada, Autocorrelação, Glycine Max, Índices de vegetação

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