Coffee crop yield estimate using an agrometeorological‑spectral model
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Pesquisa Agropecuária Brasileira (Online) |
Texto Completo: | https://seer.sct.embrapa.br/index.php/pab/article/view/8623 |
Resumo: | The objective of this work was to evaluate an agrometeorological-spectral model to estimate coffee crop yield. Images from the MODIS sensor and meteorological data from the ETA regional weather forecast model were used to provide input variables to the agrometeorological-spectral model, in the South-Southeast region of Minas Gerais State, Brazil, for crop years 2003/2004 to 2007/2008. The input spectral variable of the spectral-agrometeorological model, the leaf area index (LAI), used in the determination of the maximum yield, was estimated with the normalized-difference vegetation index (NDVI) obtained from MODIS images. Other input variables for the model were: meteorological data generated by the ETA model and the soil available water capacity. Comparing 0.4; 3.0; 5.3; 1.5 and 8.5% for crop years 2003/2004, 2004/2005, 2005/2006, 2006/2007 and 2007/2008, respectively. The agrometeorological-spectral model, based on Doorenbos & Kassan model, was as efficient as the IBGE official model to estimate the coffee crop yield. Furthermore, it was possible to present the spatial variation of coffee crop yield loss and to predict 80% of final yield by the first fortight of February before the harvest. |
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Coffee crop yield estimate using an agrometeorological‑spectral modelEstimativa da produtividade de café com base em um modelo agrometeorológico-espectralCoffea; agricultural statistics; leaf area index; modeling; remote sensingCoffea; estatísticas agrícolas; índice de área foliar; modelagem; sensoriamento remoto The objective of this work was to evaluate an agrometeorological-spectral model to estimate coffee crop yield. Images from the MODIS sensor and meteorological data from the ETA regional weather forecast model were used to provide input variables to the agrometeorological-spectral model, in the South-Southeast region of Minas Gerais State, Brazil, for crop years 2003/2004 to 2007/2008. The input spectral variable of the spectral-agrometeorological model, the leaf area index (LAI), used in the determination of the maximum yield, was estimated with the normalized-difference vegetation index (NDVI) obtained from MODIS images. Other input variables for the model were: meteorological data generated by the ETA model and the soil available water capacity. Comparing 0.4; 3.0; 5.3; 1.5 and 8.5% for crop years 2003/2004, 2004/2005, 2005/2006, 2006/2007 and 2007/2008, respectively. The agrometeorological-spectral model, based on Doorenbos & Kassan model, was as efficient as the IBGE official model to estimate the coffee crop yield. Furthermore, it was possible to present the spatial variation of coffee crop yield loss and to predict 80% of final yield by the first fortight of February before the harvest.O objetivo deste trabalho foi avaliar um modelo agrometeorológico-espectral, para estimar a produtividade de cafezais. Utilizaram-se imagens do sensor MODIS e dados agrometeorológicos do modelo regional de previsão do tempo (ETA), para fornecer as variáveis de entrada para o modelo agrometeorológico-espectral da mesorregião geográfica sul/sudoeste do estado de Minas Gerais nos anos-agrícolas de 2003/2004 a 2007/2008. A variável espectral de entrada do modelo agrometeorológico-espectral, índice de área foliar (IAF), usada no cálculo da produtividade máxima, foi estimada com o índice de vegetação por diferença normalizada (NDVI), obtido de imagens MODIS. Outras variáveis de entrada no modelo foram: dados meteorológicos gerados pelo modelo ETA e a capacidade de água disponível no solo. Ao comparar a produtividade média estimada pelo modelo com a fornecida oficialmente pelo IBGE, as diferenças relativas obtidas em escala regional foram de: 0,4, 3,0, 5,3, 1,5 e 8,5% para os anos agrícolas 2003/2004, 2004/2005, 2005/2006, 2006/2007 e 2007/2008, respectivamente. O modelo agrometeorólogico-espectral, que tem como base o modelo de Doorenbos & Kassan, foi tão eficaz para estimar a produtividade dos cafezais quanto o modelo oficial do IBGE. Além disso, foi possível espacializar a quebra de produtividade e prever 80% da produtividade final na primeira quinzena de fevereiro, antes do início da colheita.Pesquisa Agropecuaria BrasileiraPesquisa Agropecuária BrasileiraCNPqRosa, Viviane Gomes Cardoso daMoreira, Mauricio AlvesRudorff, Bernardo Friedrich TheodorAdami, Marcos2011-02-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.sct.embrapa.br/index.php/pab/article/view/8623Pesquisa Agropecuaria Brasileira; v.45, n.12, dez. 2010; 1478-14-88Pesquisa Agropecuária Brasileira; v.45, n.12, dez. 2010; 1478-14-881678-39210100-104xreponame:Pesquisa Agropecuária Brasileira (Online)instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa)instacron:EMBRAPAporhttps://seer.sct.embrapa.br/index.php/pab/article/view/8623/6170https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/8623/4355https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/8623/5066info:eu-repo/semantics/openAccess2014-11-17T16:02:52Zoai:ojs.seer.sct.embrapa.br:article/8623Revistahttp://seer.sct.embrapa.br/index.php/pabPRIhttps://old.scielo.br/oai/scielo-oai.phppab@sct.embrapa.br || sct.pab@embrapa.br1678-39210100-204Xopendoar:2014-11-17T16:02:52Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa)false |
dc.title.none.fl_str_mv |
Coffee crop yield estimate using an agrometeorological‑spectral model Estimativa da produtividade de café com base em um modelo agrometeorológico-espectral |
title |
Coffee crop yield estimate using an agrometeorological‑spectral model |
spellingShingle |
Coffee crop yield estimate using an agrometeorological‑spectral model Rosa, Viviane Gomes Cardoso da Coffea; agricultural statistics; leaf area index; modeling; remote sensing Coffea; estatísticas agrícolas; índice de área foliar; modelagem; sensoriamento remoto |
title_short |
Coffee crop yield estimate using an agrometeorological‑spectral model |
title_full |
Coffee crop yield estimate using an agrometeorological‑spectral model |
title_fullStr |
Coffee crop yield estimate using an agrometeorological‑spectral model |
title_full_unstemmed |
Coffee crop yield estimate using an agrometeorological‑spectral model |
title_sort |
Coffee crop yield estimate using an agrometeorological‑spectral model |
author |
Rosa, Viviane Gomes Cardoso da |
author_facet |
Rosa, Viviane Gomes Cardoso da Moreira, Mauricio Alves Rudorff, Bernardo Friedrich Theodor Adami, Marcos |
author_role |
author |
author2 |
Moreira, Mauricio Alves Rudorff, Bernardo Friedrich Theodor Adami, Marcos |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
CNPq |
dc.contributor.author.fl_str_mv |
Rosa, Viviane Gomes Cardoso da Moreira, Mauricio Alves Rudorff, Bernardo Friedrich Theodor Adami, Marcos |
dc.subject.por.fl_str_mv |
Coffea; agricultural statistics; leaf area index; modeling; remote sensing Coffea; estatísticas agrícolas; índice de área foliar; modelagem; sensoriamento remoto |
topic |
Coffea; agricultural statistics; leaf area index; modeling; remote sensing Coffea; estatísticas agrícolas; índice de área foliar; modelagem; sensoriamento remoto |
description |
The objective of this work was to evaluate an agrometeorological-spectral model to estimate coffee crop yield. Images from the MODIS sensor and meteorological data from the ETA regional weather forecast model were used to provide input variables to the agrometeorological-spectral model, in the South-Southeast region of Minas Gerais State, Brazil, for crop years 2003/2004 to 2007/2008. The input spectral variable of the spectral-agrometeorological model, the leaf area index (LAI), used in the determination of the maximum yield, was estimated with the normalized-difference vegetation index (NDVI) obtained from MODIS images. Other input variables for the model were: meteorological data generated by the ETA model and the soil available water capacity. Comparing 0.4; 3.0; 5.3; 1.5 and 8.5% for crop years 2003/2004, 2004/2005, 2005/2006, 2006/2007 and 2007/2008, respectively. The agrometeorological-spectral model, based on Doorenbos & Kassan model, was as efficient as the IBGE official model to estimate the coffee crop yield. Furthermore, it was possible to present the spatial variation of coffee crop yield loss and to predict 80% of final yield by the first fortight of February before the harvest. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-02-03 |
dc.type.none.fl_str_mv |
|
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/8623 |
url |
https://seer.sct.embrapa.br/index.php/pab/article/view/8623 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://seer.sct.embrapa.br/index.php/pab/article/view/8623/6170 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/8623/4355 https://seer.sct.embrapa.br/index.php/pab/article/downloadSuppFile/8623/5066 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
publisher.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira Pesquisa Agropecuária Brasileira |
dc.source.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira; v.45, n.12, dez. 2010; 1478-14-88 Pesquisa Agropecuária Brasileira; v.45, n.12, dez. 2010; 1478-14-88 1678-3921 0100-104x reponame:Pesquisa Agropecuária Brasileira (Online) instname:Empresa Brasileira de Pesquisa Agropecuária (Embrapa) instacron:EMBRAPA |
instname_str |
Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
instacron_str |
EMBRAPA |
institution |
EMBRAPA |
reponame_str |
Pesquisa Agropecuária Brasileira (Online) |
collection |
Pesquisa Agropecuária Brasileira (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Brasileira (Online) - Empresa Brasileira de Pesquisa Agropecuária (Embrapa) |
repository.mail.fl_str_mv |
pab@sct.embrapa.br || sct.pab@embrapa.br |
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1793416693847949312 |