Title:	Predicting soybean grain yield using aerial drone images.
Authors:	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.
Affiliation:	ADERSON SOARES DE ANDRADE JUNIOR, CPAMN; SILVESTRE P. DA SILVA, UFPI; INGRID S. SETUBAL, UFPI; HENRIQUE ANTUNES DE SOUZA, CPAMN; PAULO FERNANDO DE MELO JORGE VIEIRA, CPAMN; RAPHAEL A. DAS C. N. CASARI, CNPAE.
Date Issued:	2022
Citation:	Revista Brasileira de Engenharia Agrícola e Ambiental, v. 26, n. 6, p. 466-476, 2022.
Description:	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).
Thesagro:	Glycine Max
Keywords:	Aeronave remotamente pilotada Índices de vegetação Autocorrelação
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CPAMN)