Predicting soybean grain yield using aerial drone images

Autor:	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.
Přispěvatelé:	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.
Jazyk:	portugalština
Rok vydání:	2022
Předmět:	Aeronave remotamente pilotada Glycine Max Índices de vegetação Autocorrelação
Zdroj:	Repositório Institucional da EMBRAPA (Repository Open Access to Scientific Information from EMBRAPA-Alice) Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA
Popis:	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). Made available in DSpace on 2022-05-19T20:13:42Z (GMT). No. of bitstreams: 1 PredictingSoybeanGrainYieldRBEAA26.2022.pdf: 3995692 bytes, checksum: 90ca4d00d4bcf55e099c095ffb6a9a24 (MD5) Previous issue date: 2022
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=od______3056::6f063afbd32c2ca663f3879d71a2d1b1 http://www.alice.cnptia.embrapa.br/alice/handle/doc/1143266 Zobrazit plný text záznamu