Title:	Assessment of maize hybrid water status using aerial images from an unmanned aerial vehicle.
Authors:	LOPES, A. da S. ANDRADE JUNIOR, A. S. de BASTOS, E. A. SOUSA, C. A. F. de CASARI, R. A. das C. N. MOURA, M. S. B. de
Affiliation:	ALZENEIDE DA S. LOPES, UNIVERSIDADE FEDERAL DO PIAUÍ; ADERSON SOARES DE ANDRADE JUNIOR, CPAMN; EDSON ALVES BASTOS, CPAMN; CARLOS ANTONIO FERREIRA DE SOUSA, CPAMN; RAPHAEL A. DAS C. N. CASARI, EMBRAPA AGROENERGIA; MAGNA SOELMA BESERRA DE MOURA, CPATSA.
Date Issued:	2024
Citation:	Revista Caatinga, v. 37, e11701, 2024.
Description:	The objective of this work was to evaluate the potential of vegetation indices (VIs), obtained using aerial images from an unmanned aerial vehicle (UAV), for assessing water status of maize hybrids subjected to different water regimes under the soil and climate conditions of Teresina, Piauí, Brazil. Evaluations were carried out considering the application of five water regimes (WR) based on the crop evapotranspiration (ETc) (40%, 60%, 80%, 100%, and 120% of ETc) for three maize hybrids: BRS 3046 (conventional triple hybrid), BRS 2022 (conventional double hybrid), Status VIP3 (transgenic simple hybrid). A randomized block experimental design with four replications was used, in a 5×3 split-plot arrangement, consisting of WRs in the plots and maize hybrids in the subplots. A UAV was used for acquiring multispectral images. Eighteen VIs were evaluated and correlated with stomatal conductance (gs), leaf relative water content (RWC), and grain yield (GY). The VIs TCARI -RE and NDVI presented correlation with gs, whereas MNGRD and GCI presented correlation with RWC; therefore, they were considered promising for assessing the water status of maize plants. NDVI and WDRVI presented correlations with GY. Maps of NDVI, MNGRV, and WDRVI showed spatial correlation with gs, RWC, and GY measurements, respectively, in response to the applied WRs, denoting potential for assessing the water status of maize plants using aerial images from UAV.
Thesagro:	Variedade Sensoriamento Remoto Milho Índice de Seleção Vegetação Clima
NAL Thesaurus:	Remote sensing Water stress Vegetation index
Keywords:	Drone Cultivar Estresse hídrico Índice de vegetação
ISSN:	1983-2125
DOI:	http://dx.doi.org/10.1590/1983-21252024v3711701rc
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CPATSA)