Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1161243
Título: Climate drivers affecting upland rice yield in the central region of Brazil.
Autoria: HEINEMANN, A. B.
STONE, L. F.
SILVA, G. C. C.
MATTA, D. H. da
JUSTINO, L. F.
SILVA, S. C. da
Afiliação: ALEXANDRE BRYAN HEINEMANN, CNPAF; LUIS FERNANDO STONE, CNPAF; GUILHERME CUSTODIO CANDIDO SILVA, UNIVERSIDADE FEDERAL DE GOIÁS; DAVID HENRIQUES DA MATTA, UNIVERSIDADE FEDERAL DE GOIÁS; LUDMILLA FERREIRA JUSTINO, UNIVERSIDADE FEDERAL DE GOIÁS; SILVANDO CARLOS DA SILVA, CNPAF.
Ano de publicação: 2024
Referência: Pesquisa Agropecuária Tropical, v. 54, e77222, 2024.
Conteúdo: The upland rice production is primarily concentrated in a vast area of central Brazil. Given the region’s environmental variability, the performance of rice cultivars can differ significantly. This study aimed to identify the key climate factors influencing the upland rice yield in the central region of Brazil, encompassing four states: Goiás, Mato Grosso, Tocantins and Rondônia. A dataset comprising 177 trials involving commonly cultivated and well-adapted upland rice varieties, derived from the Embrapa’s rice breeding dataset, was analyzed. These trials were conducted in randomized blocks, with three replications, from 1996 to 2018. The generalized additive model approach was employed to adjust the non-linear relationships between environmental factors and grain yield, revealing four climatic variables: maximum air temperature throughout the growth cycle, minimum air temperature at panicle initiation, degree-days from emergence to panicle initiation and degree-days throughout the growth cycle. An increase in the maximum air temperature and degree-days throughout the growth cycle tend to decrease rice yield, while an increase in the minimum air temperature at the panicle initiation and degree-days from emergence to panicle initiation tend to increase it.
Thesagro: Arroz
Oryza Sativa
Risco Climático
Clima
NAL Thesaurus: Rice
Prediction
Climate
Palavras-chave: Modelo aditivo generalizado
Previsão ambiental
Enviromics prediction
ISSN: 1983-4063
Digital Object Identifier: https://doi.org/10.1590/1983-40632024v5477222
Tipo do material: Artigo de periódico
Acesso: openAccess
Aparece nas coleções:Artigo em periódico indexado (CNPAF)

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