|
|
Registro Completo |
Biblioteca(s): |
Embrapa Unidades Centrais. |
Data corrente: |
03/04/2017 |
Data da última atualização: |
16/05/2017 |
Autoria: |
GUSSO, A.; ARVOR, D.; DUCATI, J. R. |
Afiliação: |
ANIBAL GUSSO, UFRGS; DAMIEN ARVOR, CNRS; JORGE RICARDO DUCATI, UFRGS. |
Título: |
Model for soybean production forecast based on prevailing physical conditions. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 52, n. 2, p. 95-103, fev. 2017. |
Idioma: |
Inglês |
Notas: |
Título em português: Modelo para previsão da produção de soja baseado em condições físicas predominantes. |
Conteúdo: |
The objective of this work was to evaluate the reliability of the physiological meaning of the enhanced vegetation index (EVI) data for the development of a remote sensing-based procedure to estimate soybean production prior to crop harvest. Time-series data from the moderate resolution imaging spectroradiometer (Modis) were applied to investigate the relationship between local yield fluctuations of soybean and the prevailing physically-driven conditions in the state of Mato Grosso, located in the south of the Brazilian Amazon. The developed methodology was based on the coupled model (CM). The CM provides production estimates for early January, using images from the maximum crop development period. Production estimates were validated at three different spatial scales: state, municipality, and local. At the state and municipality levels, the results obtained from the CM were compared with official agricultural statistics from Instituto Brasileiro de Geografia e Estatística and Companhia Nacional de Abastecimento, from 2001 to 2011. The coefficients of determination ranged from 0.91 to 0.98, with overall result of R2=0.96 (p?0.01), indicating that the model adheres to official statistics. At the local level, spatially distributed data were compared with production data from 422 crop fields. The coefficient of determination (R2=0.87) confirmed the reliability of the EVI for its applicability on remote sensing-based models for soybean production forecast. |
Thesagro: |
Agricultura; Satélite; Sensoriamento remoto. |
Thesaurus Nal: |
Moderate resolution imaging spectroradiometer; Remote sensing; Satellites. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/158533/1/Model-for-soybean-production.pdf
|
Marc: |
LEADER 02255naa a2200229 a 4500 001 2068041 005 2017-05-16 008 2017 bl uuuu u00u1 u #d 100 1 $aGUSSO, A. 245 $aModel for soybean production forecast based on prevailing physical conditions. 260 $c2017 500 $aTítulo em português: Modelo para previsão da produção de soja baseado em condições físicas predominantes. 520 $aThe objective of this work was to evaluate the reliability of the physiological meaning of the enhanced vegetation index (EVI) data for the development of a remote sensing-based procedure to estimate soybean production prior to crop harvest. Time-series data from the moderate resolution imaging spectroradiometer (Modis) were applied to investigate the relationship between local yield fluctuations of soybean and the prevailing physically-driven conditions in the state of Mato Grosso, located in the south of the Brazilian Amazon. The developed methodology was based on the coupled model (CM). The CM provides production estimates for early January, using images from the maximum crop development period. Production estimates were validated at three different spatial scales: state, municipality, and local. At the state and municipality levels, the results obtained from the CM were compared with official agricultural statistics from Instituto Brasileiro de Geografia e Estatística and Companhia Nacional de Abastecimento, from 2001 to 2011. The coefficients of determination ranged from 0.91 to 0.98, with overall result of R2=0.96 (p?0.01), indicating that the model adheres to official statistics. At the local level, spatially distributed data were compared with production data from 422 crop fields. The coefficient of determination (R2=0.87) confirmed the reliability of the EVI for its applicability on remote sensing-based models for soybean production forecast. 650 $aModerate resolution imaging spectroradiometer 650 $aRemote sensing 650 $aSatellites 650 $aAgricultura 650 $aSatélite 650 $aSensoriamento remoto 700 1 $aARVOR, D. 700 1 $aDUCATI, J. R. 773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 52, n. 2, p. 95-103, fev. 2017.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
| Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Gado de Leite; Embrapa Milho e Sorgo. |
Data corrente: |
23/09/2020 |
Data da última atualização: |
30/12/2020 |
Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
Autoria: |
KARAM, D.; BRIGHENTI, A. M. |
Afiliação: |
DECIO KARAM, CNPMS; ALEXANDRE MAGNO B DOS SANTOS, CNPGL. |
Título: |
Identificação e controle de plantas daninhas. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
In: ALFAFA: do cultivo aos múltiplos usos. Brasília, DF: Ministério da Agricultura, Pecuária e Abastecimento, 2020. |
Páginas: |
p. 98-104. |
Idioma: |
Português |
Palavras-Chave: |
Planta daninha. |
Thesagro: |
Controle Químico; Erva Daninha; Forragem; Herbicida; Planta Forrageira. |
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
Marc: |
LEADER 00631naa a2200205 a 4500 001 2125081 005 2020-12-30 008 2020 bl uuuu u00u1 u #d 100 1 $aKARAM, D. 245 $aIdentificação e controle de plantas daninhas.$h[electronic resource] 260 $c2020 300 $ap. 98-104. 650 $aControle Químico 650 $aErva Daninha 650 $aForragem 650 $aHerbicida 650 $aPlanta Forrageira 653 $aPlanta daninha 700 1 $aBRIGHENTI, A. M. 773 $tIn: ALFAFA: do cultivo aos múltiplos usos. Brasília, DF: Ministério da Agricultura, Pecuária e Abastecimento, 2020.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Milho e Sorgo (CNPMS) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Expressão de busca inválida. Verifique!!! |
|
|