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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
03/01/2024 |
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Data da última atualização: |
03/01/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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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. |
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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. |
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Título: |
Use of RPA images in the mapping of the chlorophyll index of coffee plants. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Sustainability , v. 14, n. 20, 13118, 2022. |
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Páginas: |
16 p. |
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DOI: |
https://doi.org/10.3390/su142013118 |
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Idioma: |
Inglês |
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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. MenosCoffee 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 o... Mostrar Tudo |
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Thesagro: |
Coffea Arábica. |
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Thesaurus Nal: |
Chlorophyll; Radiation hybrid mapping. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1160422/1/Use-of-RPA-Images-in-the-Mapping.pdf
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Marc: |
LEADER 03032naa a2200241 a 4500
001 2160422
005 2024-01-03
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/su142013118$2DOI
100 1 $aSANTOS, L. M. dos
245 $aUse of RPA images in the mapping of the chlorophyll index of coffee plants.$h[electronic resource]
260 $c2022
300 $a16 p.
520 $aCoffee 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.
650 $aChlorophyll
650 $aRadiation hybrid mapping
650 $aCoffea Arábica
700 1 $aFERRAZ, G. A. e S.
700 1 $aCARVALHO, M. A. de F.
700 1 $aTEODORO, S. A.
700 1 $aCAMPOS, A. A. V.
700 1 $aMENICUCCI NETO, P.
773 $tSustainability$gv. 14, n. 20, 13118, 2022.
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Registro original: |
Embrapa Café (CNPCa) |
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Biblioteca |
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Origem |
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Registro |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
07/12/2020 |
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Data da última atualização: |
10/12/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
ALVES, G. F.; VICTORIA, D. de C. |
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Afiliação: |
GABRIEL FRANCIOLI ALVES, Bolsista CNPq (PIBIC), Unicamp; DANIEL DE CASTRO VICTORIA, CNPTIA. |
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Título: |
Avaliação da precipitação estimada pelo GPM Late Run para estações meteorológicas no Brasil. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
In: CONGRESSO INTERINSTITUCIONAL DE INICIAÇÃO CIENTÍFICA, 14., 2020. Anais... Campinas: Embrapa Informática Agropecuária, 2020. |
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Páginas: |
p. 1-8. |
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ISBN: |
978-65-88414-00-2 |
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Idioma: |
Português |
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Notas: |
Evento online. CIIC 2020. Nº 20604. |
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Conteúdo: |
RESUMO - O produto GPM IMERG (Global Precipitation Measurement) fornece dados de precipitação a cada 30 minutos, com 10 quilômetros de resolução espacial, para grande parte do globo. Esse é gerado a partir de dados coletados por uma constelação de satélites e apresenta três versões denominadas Early, Late e Final Run, com latência³ de 4 horas, 12 horas e 3,5 meses, respectivamente. Diversos trabalhos avaliam a qualidade do produto GPM porém, a maioria avalia o produto final (Final Run), o qual não é disponibilizado em tempo hábil para utilização no monitoramento agrometeorológico. Dessa forma, é preciso avaliar se o produto GPM IMERG Late Run representa de forma fiel a precipitação ocorrida no Brasil. A partir dos dados analisados, é possível visualizar que quando trabalhamos com escalas temporais mais agregadas os resultados melhoram, ou seja, as estimativas de chuvas decendiais e mensais são melhores que as estimativas diárias e isso é visível em todo o território brasileiro, exceto para algumas estações do litoral nordestino. Dessa forma, concluímos que é possível utilizar o produto GPM IMERG Late Run como base para o sistema de monitoramento. |
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Palavras-Chave: |
Global Precipitation Measurement; Meteorological monitoring; Monitoramento meteorológico; Precipitação; Precipitation. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/218833/1/RE20604-CIIC-2020.pdf
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Marc: |
LEADER 01997nam a2200217 a 4500
001 2127729
005 2020-12-10
008 2020 bl uuuu u00u1 u #d
020 $a978-65-88414-00-2
100 1 $aALVES, G. F.
245 $aAvaliação da precipitação estimada pelo GPM Late Run para estações meteorológicas no Brasil.$h[electronic resource]
260 $aIn: CONGRESSO INTERINSTITUCIONAL DE INICIAÇÃO CIENTÍFICA, 14., 2020. Anais... Campinas: Embrapa Informática Agropecuária$c2020
300 $ap. 1-8.
500 $aEvento online. CIIC 2020. Nº 20604.
520 $aRESUMO - O produto GPM IMERG (Global Precipitation Measurement) fornece dados de precipitação a cada 30 minutos, com 10 quilômetros de resolução espacial, para grande parte do globo. Esse é gerado a partir de dados coletados por uma constelação de satélites e apresenta três versões denominadas Early, Late e Final Run, com latência³ de 4 horas, 12 horas e 3,5 meses, respectivamente. Diversos trabalhos avaliam a qualidade do produto GPM porém, a maioria avalia o produto final (Final Run), o qual não é disponibilizado em tempo hábil para utilização no monitoramento agrometeorológico. Dessa forma, é preciso avaliar se o produto GPM IMERG Late Run representa de forma fiel a precipitação ocorrida no Brasil. A partir dos dados analisados, é possível visualizar que quando trabalhamos com escalas temporais mais agregadas os resultados melhoram, ou seja, as estimativas de chuvas decendiais e mensais são melhores que as estimativas diárias e isso é visível em todo o território brasileiro, exceto para algumas estações do litoral nordestino. Dessa forma, concluímos que é possível utilizar o produto GPM IMERG Late Run como base para o sistema de monitoramento.
653 $aGlobal Precipitation Measurement
653 $aMeteorological monitoring
653 $aMonitoramento meteorológico
653 $aPrecipitação
653 $aPrecipitation
700 1 $aVICTORIA, D. de C.
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Embrapa Agricultura Digital (CNPTIA) |
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