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Biblioteca(s): |
Embrapa Florestas. |
Data corrente: |
02/06/2014 |
Data da última atualização: |
02/06/2014 |
Autoria: |
CORTE, A. P. D.; SANQUETTA, C. R.; FIGUEIREDO FILHO, A.; PEREIRA, T. K.; BEHLING, A. |
Título: |
Desempenho de métodos e processos de amostragem para avaliação de diversidade em Floresta Ombrófila Mista. |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
Floresta, Curitiba, v. 43, n. 4, p. 579-591, out./dez. 2013. |
Idioma: |
Português |
Palavras-Chave: |
Collector curve; Curva do coletor; Margalef; Shannon; Simpson. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00646naa a2200217 a 4500 001 1987472 005 2014-06-02 008 2013 bl uuuu u00u1 u #d 100 1 $aCORTE, A. P. D. 245 $aDesempenho de métodos e processos de amostragem para avaliação de diversidade em Floresta Ombrófila Mista. 260 $c2013 653 $aCollector curve 653 $aCurva do coletor 653 $aMargalef 653 $aShannon 653 $aSimpson 700 1 $aSANQUETTA, C. R. 700 1 $aFIGUEIREDO FILHO, A. 700 1 $aPEREIRA, T. K. 700 1 $aBEHLING, A. 773 $tFloresta, Curitiba$gv. 43, n. 4, p. 579-591, out./dez. 2013.
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Embrapa Florestas (CNPF) |
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Registro Completo
Biblioteca(s): |
Embrapa Amazônia Oriental. |
Data corrente: |
07/01/2020 |
Data da última atualização: |
04/06/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
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. |
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. |
Título: |
Agrometeorological models to forecast açaí (Euterpe oleracea Mart.) yield in the Eastern Amazon. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Journal of the Science of Food and Agriculture, v. 100, n. 4, p. 1558-1569, Mar. 2020. |
DOI: |
10.1002/jsfa.10164 |
Idioma: |
Inglês |
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 |
Thesagro: |
Açaí; Clima; Euterpe Oleracea; Produção. |
Thesaurus NAL: |
Crop models. |
Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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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