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Registro Completo |
Biblioteca(s): |
Embrapa Arroz e Feijão. |
Data corrente: |
25/10/2023 |
Data da última atualização: |
25/10/2023 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
COSTA-NETO, G.; MATTA, D. H. da; FERNANDES, I. K.; STONE, L. F.; HEINEMANN, A. B. |
Afiliação: |
GERMANO COSTA-NETO, CORNELL UNIVERSITY, Ithaca-NY; DAVID HENRIQUES DA MATTA, UNIVERSIDADE FEDERAL DE GOIÁS; IGOR KUIVJOGI FERNANDES, UNIVERSIDADE FEDERAL DE GOIÁS; LUIS FERNANDO STONE, CNPAF; ALEXANDRE BRYAN HEINEMANN, CNPAF. |
Título: |
Environmental clusters defining breeding zones for tropical irrigated rice in Brazil. |
Ano de publicação: |
2023 |
Fonte/Imprenta: |
Agronomy Journal, 2023. |
ISSN: |
1435-0645 |
DOI: |
https://doi.org/10.1002/agj2.21481 |
Idioma: |
Inglês |
Notas: |
Early view. |
Conteúdo: |
Geographic and seasonal effects are important in driving selection decisions in rice breeding research. Adopting new strategies for characterizing environmental?phenotype associations is critical to understanding these effects, and the outcomes of their study could reflect the benefits of developing locally adapted cultivars. This study aimed to characterize Brazil's tropical irrigated rice (IR) environment, Latin America's largest rice production system. We integrated unsupervised (K-means clustering) and supervised (decision tree classifier) algorithms to identify environmental clusters (EC) based on historical yield data. The data set included 31 locations and 471 genotypes from 1982 to 2017. We used environmental features (EF), such as weather and geography, as input variables for our analysis, assuming the model as EC ∼ f (EF). Results indicate that the tropical IR production region can be divided into four primary breeding zones, with temperature emerging as a significant factor in the study area. After employing a linear mixed model analysis, we observed that the current relationship between genetics (G), environmental variation (E), and their interaction (G×E) in Brazil's tropical IR has a 1:6:2 ratio. However, when introducing our data-driven model based on EC, we reduced this ratio to 1:5:1. Therefore, the selection for local adaptability across a large region became more reliable. Our approach successfully identified EC in Brazil's tropical production region of IR, providing valuable insights for defining breeding zones and identifying more productive and stable seed production fields. MenosGeographic and seasonal effects are important in driving selection decisions in rice breeding research. Adopting new strategies for characterizing environmental?phenotype associations is critical to understanding these effects, and the outcomes of their study could reflect the benefits of developing locally adapted cultivars. This study aimed to characterize Brazil's tropical irrigated rice (IR) environment, Latin America's largest rice production system. We integrated unsupervised (K-means clustering) and supervised (decision tree classifier) algorithms to identify environmental clusters (EC) based on historical yield data. The data set included 31 locations and 471 genotypes from 1982 to 2017. We used environmental features (EF), such as weather and geography, as input variables for our analysis, assuming the model as EC ∼ f (EF). Results indicate that the tropical IR production region can be divided into four primary breeding zones, with temperature emerging as a significant factor in the study area. After employing a linear mixed model analysis, we observed that the current relationship between genetics (G), environmental variation (E), and their interaction (G×E) in Brazil's tropical IR has a 1:6:2 ratio. However, when introducing our data-driven model based on EC, we reduced this ratio to 1:5:1. Therefore, the selection for local adaptability across a large region became more reliable. Our approach successfully identified EC in Brazil's tropical production region... Mostrar Tudo |
Thesagro: |
Arroz Irrigado; Genótipo; Meio Ambiente; Melhoramento Genético Vegetal; Oryza Sativa; Sistema de Produção. |
Thesaurus Nal: |
Breeding; Climate models; Environmental factors; Genotype; Genotype-environment interaction; Rice; Tropical agriculture. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
Marc: |
LEADER 02650naa a2200361 a 4500 001 2157493 005 2023-10-25 008 2023 bl uuuu u00u1 u #d 022 $a1435-0645 024 7 $ahttps://doi.org/10.1002/agj2.21481$2DOI 100 1 $aCOSTA-NETO, G. 245 $aEnvironmental clusters defining breeding zones for tropical irrigated rice in Brazil.$h[electronic resource] 260 $c2023 500 $aEarly view. 520 $aGeographic and seasonal effects are important in driving selection decisions in rice breeding research. Adopting new strategies for characterizing environmental?phenotype associations is critical to understanding these effects, and the outcomes of their study could reflect the benefits of developing locally adapted cultivars. This study aimed to characterize Brazil's tropical irrigated rice (IR) environment, Latin America's largest rice production system. We integrated unsupervised (K-means clustering) and supervised (decision tree classifier) algorithms to identify environmental clusters (EC) based on historical yield data. The data set included 31 locations and 471 genotypes from 1982 to 2017. We used environmental features (EF), such as weather and geography, as input variables for our analysis, assuming the model as EC ∼ f (EF). Results indicate that the tropical IR production region can be divided into four primary breeding zones, with temperature emerging as a significant factor in the study area. After employing a linear mixed model analysis, we observed that the current relationship between genetics (G), environmental variation (E), and their interaction (G×E) in Brazil's tropical IR has a 1:6:2 ratio. However, when introducing our data-driven model based on EC, we reduced this ratio to 1:5:1. Therefore, the selection for local adaptability across a large region became more reliable. Our approach successfully identified EC in Brazil's tropical production region of IR, providing valuable insights for defining breeding zones and identifying more productive and stable seed production fields. 650 $aBreeding 650 $aClimate models 650 $aEnvironmental factors 650 $aGenotype 650 $aGenotype-environment interaction 650 $aRice 650 $aTropical agriculture 650 $aArroz Irrigado 650 $aGenótipo 650 $aMeio Ambiente 650 $aMelhoramento Genético Vegetal 650 $aOryza Sativa 650 $aSistema de Produção 700 1 $aMATTA, D. H. da 700 1 $aFERNANDES, I. K. 700 1 $aSTONE, L. F. 700 1 $aHEINEMANN, A. B. 773 $tAgronomy Journal, 2023.
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Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
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Registros recuperados : 323 | |
101. | | HEINEMANN, A. B.; FRIZZONE, J. A.; PINTO, J. M.; FEITOSA FILHO, J. C. Influência da altura do emissor na uniformidade de distribuição da água de um sistema pivô central. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 33, n. 9, p. 1487-91, set. 1998. Título em inglês: Influence of sprinkler height on the uniformity of water distribution of a central pivot system.Biblioteca(s): Embrapa Unidades Centrais. |
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103. | | SANTOS, A. B. dos; STONE, L. F.; HEINEMANN, A. B.; SANTOS, T. P. B. Índices fisiológicos do arroz irrigado afetados pela inundação e fertilização nitrogenada. Revista Ceres, Viçosa, MG, v. 64, n. 2, p. 122-131, mar./abr. 2017.Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
Biblioteca(s): Embrapa Arroz e Feijão. |
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107. | | ANTOLIN, L. A. S.; COSTA NETO, G. M. F.; BORGES, M. G.; HEINEMANN, A. B. Irrigation efficiency simulation for common bean during dry season, in the municipality of Goiânia, Goiás. In: INOVAGRI INTERNATIONAL MEETING, 3., 2015, Fortaleza. Anais... Fortaleza: INI, 2015.Tipo: Artigo em Anais de Congresso |
Biblioteca(s): Embrapa Arroz e Feijão. |
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108. | | SANTOS, E. do N.; LUZ, W. G. da; SILVA, S. C. da; HEINEMANN, A. B. Lâmina de água para o feijoeiro em Cristalina, GO. In: SEMINÁRIO JOVENS TALENTOS, 11., 2017, Santo Antônio de Goiás. Coletânea dos resumos apresentados. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2017. p. 51. (Embrapa Arroz e Feijão. Documentos, 316).Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Arroz e Feijão. |
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111. | | VAN OORT, P. A. J.; ZHANG, T.; VRIES, M. E. de; HEINEMANN, A. B.; MEINKE, H. Correlation between temperature and phenology prediction error in rice (Oryza sativa L.). Agricultural and Forest Meteorology, Amsterdam, v. 151, n. 12, p. 1545-1555, Dec. 2011.Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
Biblioteca(s): Embrapa Arroz e Feijão. |
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Registros recuperados : 323 | |
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Nenhum registro encontrado para a expressão de busca informada. |
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