Data/hora: 06/06/2024 23:42:05

Biblioteca(s): 	Embrapa Café.	
Data corrente: 	03/01/2024	
Data da última atualização: 	03/01/2024	
Autoria: 	SANTOS, L. M. dos; FERRAZ, G. A. e S.; CARVALHO, M. A. de F.; TEODORO, S. A.; CAMPOS, A. A. V.; MENICUCCI NETO, P.	
Afiliação: 	LUANA MENDES DOS SANTOS, - UNIVERSIDADE FEDERAL DE LAVRAS; GABRIEL ARAÚJO E SILVA FERRAZ, UNIVERSIDADE FEDERAL DE LAVRAS; MILENE ALVES DE FIGUEIREDO CARVALHO, CNPCa; SABRINA APARECIDA TEODORO, UNIVERSIDADE FEDERAL DE LAVRAS; ALISSON ANDRÉ VICENTE CAMPOS, UNIVERSIDADE FEDERAL DE LAVRAS; PEDRO MENICUCCI NETO, UNIVERSIDADE FEDERAL DE LAVRAS.	
Título: 	Use of RPA images in the mapping of the chlorophyll index of coffee plants.	
Ano de publicação: 	2022	
Fonte/Imprenta: 	Sustainability , v. 14, n. 20, 13118, 2022.	
Páginas: 	16 p.	
DOI: 	https://doi.org/10.3390/su142013118	
Idioma: 	Inglês	
Conteúdo: 	Coffee trading is an important source of income for the Brazilian commercial balance. Chlorophyll (Chl) are pigments responsible for converting radiation into energy; these pigments are closely related to the photosynthetic efficiency of plants, and the evaluation of the nutritional status of the coffee tree. The inversion method can be used for estimating the canopy chlorophyll content (Chl(canopy)) using the leaf chlorophyll content (Chl(leaf)) and the leaf area index (LAI). The application of vegetation indices (VIs) in high spatial resolution images obtained from remotely piloted aircraft (RPA) can assist in the characterization of Chl(canopy) in addition to providing vital and fast information for monitoring crops and aiding decision-making. This study aimed to identify which VIs adequately explain the Chl and evaluate the relationships between the VIs obtained from remotely piloted aircraft (RPA) images and the Chl(leaf) and Chl(canopy) in coffee plants during the wet and dry seasons. The experiment was conducted on a Coffea arabica L. plantation in Lavras, Minas Gerais, Brazil. Images were collected on 26 November 2019 (wet), 11 August 2020 (dry), and 26 August 2021 (dry) by a multispectral camera embedded in a quadcopter. Plant height (H), crow diameter (D), and Chl(leaf) (a, b and total) data were collected in the field by a metre ruler (H and D) and sensor (Chl(leaf)). The LAI was calculated based on H and D. The Chl(canopy) (a, b, and total) was calculated based on Chl(leaf) and LAI. The image processing was performed in Pix4D software, and postprocessing and calculation of the 21 VIs were performed in QGIS. Statistical analyses (descriptive, statistical tests, Pearson correlation, residuals calculation, and linear regression) were performed using the software R. The VIs from the RPA that best correlates to Chl(canopy) in the wet season were the Modified Chlorophyll Absorption Ratio Index 2 (MCARI2(RPA)), Modified Simple Ratio (MSRRPA) and Simple Ratio (SRRPA). These VIs had high sensitivity and, therefore, were more affected by chlorophyll variability. For the two dry season studied days, there were no patterns in the relationships between Chl(leaf), Chl(canopy), and the VIs. It was possible to use the Chl inversion method for the coffee during the wet season.	
Thesagro: 	Coffea Arábica.	
Thesaurus Nal: 	Chlorophyll; Radiation hybrid mapping.	
Categoria do assunto: 	--	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1160422/1/Use-of-RPA-Images-in-the-Mapping.pdf	
Registro original: 	Embrapa Café (CNPCa)	
Exemplares: 	CNPCa - (1749-1) - UPC - AP - DD -  -  -  - DIS