Data/hora: 08/06/2024 06:34:52

Biblioteca(s): | Embrapa Amazônia Oriental.
Tipo da produção científica: | Artigo em Periódico Indexado
Circulação/Nível: | A - 1
Data corrente: | 07/01/2020
Data da última atualização: | 04/06/2020
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 &#8728;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.
Thesagro: | Açaí; Clima; Euterpe Oleracea; Produção.
Thesaurus Nal: | Crop models.
Categoria do assunto: | P Recursos Naturais, Ciências Ambientais e da Terra
Registro original: | Embrapa Amazônia Oriental (CPATU)
Exemplares: | CPATU - (56232-1) - UPC - AP - DD -  -  -  - DIS