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 | Acesso ao texto completo restrito à biblioteca da Embrapa Arroz e Feijão. Para informações adicionais entre em contato com cnpaf.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
25/10/2023 |
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Data da última atualização: |
25/10/2023 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
COSTA-NETO, G.; MATTA, D. H. da; FERNANDES, I. K.; STONE, L. F.; HEINEMANN, A. B. |
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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. |
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Título: |
Environmental clusters defining breeding zones for tropical irrigated rice in Brazil. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Agronomy Journal, 2023. |
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ISSN: |
1435-0645 |
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DOI: |
https://doi.org/10.1002/agj2.21481 |
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Idioma: |
Inglês |
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Notas: |
Early view. |
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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 |
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Thesagro: |
Arroz Irrigado; Genótipo; Meio Ambiente; Melhoramento Genético Vegetal; Oryza Sativa; Sistema de Produção. |
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Thesaurus Nal: |
Breeding; Climate models; Environmental factors; Genotype; Genotype-environment interaction; Rice; Tropical agriculture. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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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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Biblioteca |
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Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
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| Acesso ao texto completo restrito à biblioteca da Embrapa Gado de Leite. Para informações adicionais entre em contato com cnpgl.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
15/01/2020 |
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Data da última atualização: |
27/06/2023 |
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Tipo da produção científica: |
Capítulo em Livro Técnico-Científico |
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Autoria: |
SANTANA, D. P.; NOCE, M. A.; BORGHI, E.; ALVARENGA, R. C.; GONTIJO NETO, M. M.; MULLER, M. D.; MARTINS, C. E.; BERNARDO, W. F.; VIANA, M. C. M.; PIRES, J. A. DE A.; CALSAVARA, L. H. F.; MELLO, B. L. B. DE; COSTA, F. A. DE S.; OLIVEIRA, C. S. S. E. |
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Afiliação: |
DERLI PRUDENTE SANTANA, CNPMS; MARCO AURELIO NOCE, CNPMS; EMERSON BORGHI, CNPMS; RAMON COSTA ALVARENGA, CNPMS; MIGUEL MARQUES GONTIJO NETO, CNPMS; MARCELO DIAS MULLER, CNPGL; CARLOS EUGENIO MARTINS, CNPGL; WILLIAM FERNANDES BERNARDO, CNPGL; Maria Celuta Machado Viana, EPAMIG; José Alberto de Ávila Pires, EMATER-MG; Leonardo Henrique Ferreira Calsavara, EMATER-MG; Bernardo Lima Bento de Mello, INCAPER; Fernando Antônio de Souza Costa, MAPA; Caio Sérgio Santos e Oliveira, SENAR-MG. |
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Título: |
Sistemas iLPF e transferência de tecnologia nos estados de Minas Gerais, Espírito Santo e Rio de Janeiro. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
In: SKORUPA, L. A.; MANZATTO, C. V. (ed.). Sistemas de integração lavoura-pecuária-floresta no Brasil: estratégias regionais de transferência de tecnologia, avaliação da adoção e de impactos. Brasília: DF, Embrapa, 2019. |
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Páginas: |
p. 192-233. |
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Idioma: |
Português |
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Conteúdo: |
As informações contidas neste capítulo mostram a evolução dos sistemas ILPF nos Estados de MG, RJ e ES, e como são delineadas as estratégias de transferência de tecnologia empregadas pelas instituições de ensino, pesquisa e extensão que permitem alavancar as atividades agrícolas e pecuárias em cada região. |
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Palavras-Chave: |
Arranjos de cultivos; Cultivo consorciado; Pastagens degradadas. |
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Categoria do assunto: |
A Sistemas de Cultivo |
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Marc: |
LEADER 01449nam a2200313 a 4500
001 2118825
005 2023-06-27
008 2019 bl uuuu 00u1 u #d
100 1 $aSANTANA, D. P.
245 $aSistemas iLPF e transferência de tecnologia nos estados de Minas Gerais, Espírito Santo e Rio de Janeiro.$h[electronic resource]
260 $aIn: SKORUPA, L. A.; MANZATTO, C. V. (ed.). Sistemas de integração lavoura-pecuária-floresta no Brasil: estratégias regionais de transferência de tecnologia, avaliação da adoção e de impactos. Brasília: DF, Embrapa$c2019
300 $ap. 192-233.
520 $aAs informações contidas neste capítulo mostram a evolução dos sistemas ILPF nos Estados de MG, RJ e ES, e como são delineadas as estratégias de transferência de tecnologia empregadas pelas instituições de ensino, pesquisa e extensão que permitem alavancar as atividades agrícolas e pecuárias em cada região.
653 $aArranjos de cultivos
653 $aCultivo consorciado
653 $aPastagens degradadas
700 1 $aNOCE, M. A.
700 1 $aBORGHI, E.
700 1 $aALVARENGA, R. C.
700 1 $aGONTIJO NETO, M. M.
700 1 $aMULLER, M. D.
700 1 $aMARTINS, C. E.
700 1 $aBERNARDO, W. F.
700 1 $aVIANA, M. C. M.
700 1 $aPIRES, J. A. DE A.
700 1 $aCALSAVARA, L. H. F.
700 1 $aMELLO, B. L. B. DE
700 1 $aCOSTA, F. A. DE S.
700 1 $aOLIVEIRA, C. S. S. E
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Embrapa Gado de Leite (CNPGL) |
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