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Registro Completo |
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
19/02/2024 |
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Data da última atualização: |
19/02/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
CASTRO, G. D. M. de; VILELA, E. F.; FARIA, A. L. R. de; SILVA, R. A.; FERREIRA, W. P. M. |
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Afiliação: |
GABRIEL DUMBÁ MONTEIRO DE CASTRO, UNIVERSIDADE FEDERAL DE VIÇOSA; EMERSON FERREIRA VILELA, EMPRESA DE PESQUISA AGROPECUÁRIA DE MINAS GERAIS; ANA LUÍSA RIBEIRO DE FARIA, UNIVERSIDADE FEDERAL DE VIÇOSA; ROGÉRIO ANTÔNIO SILVA, EMPRESA DE PESQUISA AGROPECUÁRIA DE MINAS GERAIS; WILLIAMS PINTO MARQUES FERREIRA, CNPCa. |
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Título: |
New vegetation index for monitoring coffee rust using sentinel-2 multispectral imagery. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Coffee Science, v. 18, e182170, 2023. |
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DOI: |
https://doi.org/10.25186/.v18i.2170 |
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Idioma: |
Português |
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Conteúdo: |
Coffee Rust (Hemileia vastatrix) is considered the primary coffee disease in the world. The pathogenic fungus can find favorable environmental conditions in different countries, constantly threatening coffee producers. The previous detection of the incidence of coffee rust in a region is crucial because it provides an overview of the disease’s progress aiding in coffee plantations management. The objective of this work was the development of a vegetation index for remote monitoring of coffee rust infestation. Using satellite images from the MSI/Sentinel-2 collection, the Machine Learning classifier algorithm - Random Forest, and the cloud processing platform - Google Earth Engine, the most sensitives bands in coffee rust detection were determined, namely B4 (Red), B7 (Red Edge 3) and B8A (Red Edge 4). Thus, the Triangular Vegetation Index method was used to create a new vegetative index for remote detection of coffee rust infestation on a regional scale, named Coffee Rust Detection Index (CRDI). A linear regression model was created to estimate rust infestation based on the performance of the new index. The model presented a coefficient of determination (R²) of 62.5%, and a root mean square error (RMSE) of 0.107. In addition, a comparison analysis of the new index with eight other vegetative indices commonly used in the literature was carried out. The CRDI obtained the best performance in coffee rust detection among the others. This study shows that the new index CRDI has the robustness and general capacity to be used in monitoring coffee rust infestation on a regional scale. MenosCoffee Rust (Hemileia vastatrix) is considered the primary coffee disease in the world. The pathogenic fungus can find favorable environmental conditions in different countries, constantly threatening coffee producers. The previous detection of the incidence of coffee rust in a region is crucial because it provides an overview of the disease’s progress aiding in coffee plantations management. The objective of this work was the development of a vegetation index for remote monitoring of coffee rust infestation. Using satellite images from the MSI/Sentinel-2 collection, the Machine Learning classifier algorithm - Random Forest, and the cloud processing platform - Google Earth Engine, the most sensitives bands in coffee rust detection were determined, namely B4 (Red), B7 (Red Edge 3) and B8A (Red Edge 4). Thus, the Triangular Vegetation Index method was used to create a new vegetative index for remote detection of coffee rust infestation on a regional scale, named Coffee Rust Detection Index (CRDI). A linear regression model was created to estimate rust infestation based on the performance of the new index. The model presented a coefficient of determination (R²) of 62.5%, and a root mean square error (RMSE) of 0.107. In addition, a comparison analysis of the new index with eight other vegetative indices commonly used in the literature was carried out. The CRDI obtained the best performance in coffee rust detection among the others. This study shows that the new index CRDI has th... Mostrar Tudo |
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Thesagro: |
Hemileia Vastatrix. |
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Thesaurus Nal: |
Control methods; Disease control; Vegetation index. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/doc/1162117/1/New-vegetation-index.pdf
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Marc: |
LEADER 02300naa a2200229 a 4500
001 2162117
005 2024-02-19
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.25186/.v18i.2170$2DOI
100 1 $aCASTRO, G. D. M. de
245 $aNew vegetation index for monitoring coffee rust using sentinel-2 multispectral imagery.$h[electronic resource]
260 $c2023
520 $aCoffee Rust (Hemileia vastatrix) is considered the primary coffee disease in the world. The pathogenic fungus can find favorable environmental conditions in different countries, constantly threatening coffee producers. The previous detection of the incidence of coffee rust in a region is crucial because it provides an overview of the disease’s progress aiding in coffee plantations management. The objective of this work was the development of a vegetation index for remote monitoring of coffee rust infestation. Using satellite images from the MSI/Sentinel-2 collection, the Machine Learning classifier algorithm - Random Forest, and the cloud processing platform - Google Earth Engine, the most sensitives bands in coffee rust detection were determined, namely B4 (Red), B7 (Red Edge 3) and B8A (Red Edge 4). Thus, the Triangular Vegetation Index method was used to create a new vegetative index for remote detection of coffee rust infestation on a regional scale, named Coffee Rust Detection Index (CRDI). A linear regression model was created to estimate rust infestation based on the performance of the new index. The model presented a coefficient of determination (R²) of 62.5%, and a root mean square error (RMSE) of 0.107. In addition, a comparison analysis of the new index with eight other vegetative indices commonly used in the literature was carried out. The CRDI obtained the best performance in coffee rust detection among the others. This study shows that the new index CRDI has the robustness and general capacity to be used in monitoring coffee rust infestation on a regional scale.
650 $aControl methods
650 $aDisease control
650 $aVegetation index
650 $aHemileia Vastatrix
700 1 $aVILELA, E. F.
700 1 $aFARIA, A. L. R. de
700 1 $aSILVA, R. A.
700 1 $aFERREIRA, W. P. M.
773 $tCoffee Science$gv. 18, e182170, 2023.
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Registro original: |
Embrapa Café (CNPCa) |
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| Registros recuperados : 91 | |
| 9. |  | FARIA, A. J.; HATTORI, S.; OMETTO, J. C.; BUZATO, O.; VILLA NOVA, N. A. Balanco de energia em floresta artificial (Pinus elliottii var. elliottii). In: SEMINARIO SOBRE ATUALIDADES E PERSPECTIVAS FLORESTAIS: A Influencia das Florestas no Manejo de Bacias Hidrograficas, 11., 1985, Curitiba. Anais... Curitiba: EMBRAPA-CNPF, 1985. p.23-31. (EMBRAPA-CNPF. Documentos, 16)| Biblioteca(s): Embrapa Florestas. |
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| 12. | | PALUDO, A.; ANDRADE, D. G. A. de; FARIA, A.; LIMA, H. C. de; DUBOC, E. Conservação pós-colheita e caracterização de mudanças físicas, físico-químicas e sensoriais o Figo da Índia (Opintia ficus-indica) cultivado nos cerrados do Brasil Central. In: ENCONTRO DE JOVENS TALENTOS DA EMBRAPA CERRADOS, 3., 2007, Planaltina, DF. Resumos apresentados. Planaltina, DF: Embrapa Cerrados, 2007. p. 33. (Embrapa Cerrados. Documentos, 176).| Tipo: Resumo em Anais de Congresso | Circulação/Nível: -- - -- |
| Biblioteca(s): Embrapa Cerrados. |
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| 16. | | FARIA, A. F. de; HASEGAWA, P. N.; CHAGAS, E.; PIO, R.; PURGATTO, E.; MERCADANTE, A. Z. Cultivar influence on carotenoid composition of loquats from Brazil. Journal of food composition and analysis, v. 22, n. 3, p. 196-203, 2009.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Roraima. |
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| 19. | | FARIA, C. M. B. de; SOARES, J. M.; COSTA, N. D.; FARIA, A. F. Efeito de adubos verdes associados a correções do solo no melão irrigado. In: REUNIÃO BRASILEIRA DE FERTILIDADE DO SOLO E NUTRIÇÃO DE PLANTAS, 25.; REUNIÃO BRASILEIRA SOBRE MICORRIZAS, 9.; SIMPÓSIO BRASILEIRO DE MICROBIOLOGIA DO SOLO, 7.; REUNIÃO BRASILEIRA DE BIOLOGIA DO SOLO, 4., 2002, Rio de Janeiro. Resumos... Rio de Janeiro: SBCS; SBM; UFRRJ; Embrapa Agrobiologia; Embrapa Solos, 2002. p. 121. 1 CD-ROM.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Semiárido. |
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| 20. | | MALAGUTTI, A. R.; FARIA, A. G. V.; GARBIN, J. R.; RIBEIRO, C. Development of TiO2 thin films prepared by the polymeric precursor method applied to photocatalytic degradation of rhodamine B In: ENCONTRO DA SOCIEDADE BRASILEIRA DE PESQUISA EM MATERIAIS - SBPMat, 7., 2008, Guarujá; BRAZILIAN MRS MEETING, 7., 2008, Guarujá. Abstracts... Rio de Janeiro: SBPMat, 2008. não paginado. 1CD-ROM.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Instrumentação. |
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| Registros recuperados : 91 | |
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