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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
07/01/2020 |
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Data da última atualização: |
04/06/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
MORAES, J. R. da S. C. de; ROLIM, G. de S.; MARTORANO, L. G.; APARECIDO, L. E. de O.; OLIVEIRA, M. do S. P. de; FARIAS NETO, J. T. de. |
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Afiliação: |
José Reinaldo da Silva Cabral de Moraes, UNESP; Glauco de Souza Rolim, UNESP; LUCIETA GUERREIRO MARTORANO, CPATU; Lucas Eduardo de Oliveira Aparecido, UNESP; MARIA DO SOCORRO P DE OLIVEIRA, CPATU; JOAO TOME DE FARIAS NETO, CPATU. |
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Título: |
Agrometeorological models to forecast açaí (Euterpe oleracea Mart.) yield in the Eastern Amazon. |
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Ano de publicação: |
2020 |
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Fonte/Imprenta: |
Journal of the Science of Food and Agriculture, v. 100, n. 4, p. 1558-1569, Mar. 2020. |
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DOI: |
10.1002/jsfa.10164 |
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Idioma: |
Inglês |
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Conteúdo: |
The increasing demand in Brazil and the world for products derived from the açaí palm (Euterpe oleracea Mart) has generated changes in its production process, principally due to the necessity of maintaining yield in situations of seasonality and climate fluctuation. The objective of this study was to estimate açaí fruit yield in irrigated system (IRRS) and rainfed system or unirrigated (RAINF) using agrometeorological models in response to climate conditions in the eastern Amazon. Modeling was done using multiple linear regression using the ?stepwise forward? method of variable selection. Monthly air temperature (T) values, solar radiation (SR), vapor pressure deficit (VPD), precipitation + irrigation (P+I), and potential evapotranspiration (PET) in six phenological phases were correlated with yield. The thermal necessity value was calculated through the sum of accumulated degree days (ADD) up to the formation of fruit bunch, as well as the time necessary for initial leaf development, using a base temperature of 10 ∘C. The most importantmeteorological variableswere T, SR, and VPD for IRRS, and for RAINFwater stress had the greatest effect. The accuracy of the agrometeorological models, usingmaximumvalues formean absolute percent error (MAPE),was 0.01 in the IRRS and 1.12 in the RAINF. Using thesemodels yieldwas predicted approximately 6 to 9 months before the harvest, in April,May,November, and December in the IRRS, and January,May, June, August, September, and November for the RAINF. MenosThe increasing demand in Brazil and the world for products derived from the açaí palm (Euterpe oleracea Mart) has generated changes in its production process, principally due to the necessity of maintaining yield in situations of seasonality and climate fluctuation. The objective of this study was to estimate açaí fruit yield in irrigated system (IRRS) and rainfed system or unirrigated (RAINF) using agrometeorological models in response to climate conditions in the eastern Amazon. Modeling was done using multiple linear regression using the ?stepwise forward? method of variable selection. Monthly air temperature (T) values, solar radiation (SR), vapor pressure deficit (VPD), precipitation + irrigation (P+I), and potential evapotranspiration (PET) in six phenological phases were correlated with yield. The thermal necessity value was calculated through the sum of accumulated degree days (ADD) up to the formation of fruit bunch, as well as the time necessary for initial leaf development, using a base temperature of 10 ∘C. The most importantmeteorological variableswere T, SR, and VPD for IRRS, and for RAINFwater stress had the greatest effect. The accuracy of the agrometeorological models, usingmaximumvalues formean absolute percent error (MAPE),was 0.01 in the IRRS and 1.12 in the RAINF. Using thesemodels yieldwas predicted approximately 6 to 9 months before the harvest, in April,May,November, and December in the IRRS, and January,May, June, August, September, and Novembe... Mostrar Tudo |
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Thesagro: |
Açaí; Clima; Euterpe Oleracea; Produção. |
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Thesaurus Nal: |
Crop models. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 02318naa a2200253 a 4500
001 2118319
005 2020-06-04
008 2020 bl uuuu u00u1 u #d
024 7 $a10.1002/jsfa.10164$2DOI
100 1 $aMORAES, J. R. da S. C. de
245 $aAgrometeorological models to forecast açaí (Euterpe oleracea Mart.) yield in the Eastern Amazon.$h[electronic resource]
260 $c2020
520 $aThe increasing demand in Brazil and the world for products derived from the açaí palm (Euterpe oleracea Mart) has generated changes in its production process, principally due to the necessity of maintaining yield in situations of seasonality and climate fluctuation. The objective of this study was to estimate açaí fruit yield in irrigated system (IRRS) and rainfed system or unirrigated (RAINF) using agrometeorological models in response to climate conditions in the eastern Amazon. Modeling was done using multiple linear regression using the ?stepwise forward? method of variable selection. Monthly air temperature (T) values, solar radiation (SR), vapor pressure deficit (VPD), precipitation + irrigation (P+I), and potential evapotranspiration (PET) in six phenological phases were correlated with yield. The thermal necessity value was calculated through the sum of accumulated degree days (ADD) up to the formation of fruit bunch, as well as the time necessary for initial leaf development, using a base temperature of 10 ∘C. The most importantmeteorological variableswere T, SR, and VPD for IRRS, and for RAINFwater stress had the greatest effect. The accuracy of the agrometeorological models, usingmaximumvalues formean absolute percent error (MAPE),was 0.01 in the IRRS and 1.12 in the RAINF. Using thesemodels yieldwas predicted approximately 6 to 9 months before the harvest, in April,May,November, and December in the IRRS, and January,May, June, August, September, and November for the RAINF.
650 $aCrop models
650 $aAçaí
650 $aClima
650 $aEuterpe Oleracea
650 $aProdução
700 1 $aROLIM, G. de S.
700 1 $aMARTORANO, L. G.
700 1 $aAPARECIDO, L. E. de O.
700 1 $aOLIVEIRA, M. do S. P. de
700 1 $aFARIAS NETO, J. T. de
773 $tJournal of the Science of Food and Agriculture$gv. 100, n. 4, p. 1558-1569, Mar. 2020.
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Embrapa Amazônia Oriental (CPATU) |
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Registro Completo
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Biblioteca(s): |
Embrapa Recursos Genéticos e Biotecnologia. |
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Data corrente: |
24/01/2013 |
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Data da última atualização: |
02/03/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
MAGARELLI, G.; SOUSA FILHO, I. A. de; LOPES, I. S. D.; SILVA, J. G. DA; SOUZA, J, R. DE; HOFFMANN, L. V.; CASTRO, C. S. P. de. |
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Afiliação: |
GABRIELLA MAGARELLI, CENARGEN; IDIO ALVES DE SOUSA FILHO; YNAYAN SÉPHORA DOURADO LOPES; JONATAS GOMES DA SILVA; JURANDIR RODRIGUES DE SOUZA; LUCIA VIEIRA HOFFMANN, CNPA; CLARISSA SILVA PIRES DE CASTRO, CENARGEN. |
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Título: |
Determinação de ácidos fenólicos totais em cultivares de algodão por voltametria de pulso diferencial e eletrodo de carbono vítreo. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
In: WORKSHOP DA REDE DE NANOTECNOLOGIA APLICADA AO AGRONEGÓCIO 2012, 6., 2012, Fortaleza. Anais... São Carlos: Embrapa Instrumentação; Fortaleza: Embrapa Agroindústria Tropical, 2012. |
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Páginas: |
p. 42-47 |
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Idioma: |
Português |
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Palavras-Chave: |
Ácido fenólico; Eletrodo de carbono; Voltametria. |
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Thesagro: |
Algodão. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00882nam a2200229 a 4500
001 1946323
005 2023-03-02
008 2012 bl uuuu u00u1 u #d
100 1 $aMAGARELLI, G.
245 $aDeterminação de ácidos fenólicos totais em cultivares de algodão por voltametria de pulso diferencial e eletrodo de carbono vítreo.$h[electronic resource]
260 $aIn: WORKSHOP DA REDE DE NANOTECNOLOGIA APLICADA AO AGRONEGÓCIO 2012, 6., 2012, Fortaleza. Anais... São Carlos: Embrapa Instrumentação; Fortaleza: Embrapa Agroindústria Tropical$c2012
300 $ap. 42-47
650 $aAlgodão
653 $aÁcido fenólico
653 $aEletrodo de carbono
653 $aVoltametria
700 1 $aSOUSA FILHO, I. A. de
700 1 $aLOPES, I. S. D.
700 1 $aSILVA, J. G. DA
700 1 $aSOUZA, J, R. DE
700 1 $aHOFFMANN, L. V.
700 1 $aCASTRO, C. S. P. de
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Embrapa Recursos Genéticos e Biotecnologia (CENARGEN) |
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