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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão. |
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Data corrente: |
10/10/2025 |
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Data da última atualização: |
10/10/2025 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
HEINEMANN, A. B.; MATTA, D. H. da; STONE, L. F.; COSTA-NETO, G.; RESENDE, R. T.; GONÇALVES, P. A. de O.; JUSTINO, L. F. |
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Afiliação: |
ALEXANDRE BRYAN HEINEMANN, CNPAF; DAVID HENRIQUES DA MATTA, UNIVERSIDADE FEDERAL DE GOIÁS; LUIS FERNANDO STONE, CNPAF; GERMANO COSTA-NETO, CORNELL UNIVERSITY; RAFAEL T. RESENDE, UNIVERSIDADE FEDERAL DE GOIÁS; PAULO AUGUSTO DE O. GONÇALVES, CORNELL UNIVERSITY; LUDMILLA FERREIRA JUSTINO. |
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Título: |
Envirotyping-informed mixed models to study the climatic drivers and yield seasonal variation for common beans in Brazil. |
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Ano de publicação: |
2025 |
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Fonte/Imprenta: |
European Journal of Agronomy, v. 171, 127821, Oct. 2025. |
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Páginas: |
1-15 |
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DOI: |
https://doi.org/10.1016/j.eja.2025.127821 |
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Idioma: |
Português |
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Conteúdo: |
Common beans (Phaseolus vulgaris L.) is a staple food crop cultivated across various regions, seasons, and management systems in Brazil. To ensure production stability, it is essential to understand how climate factors affect cultivar development. This study aimed to determine the main edaphoclimatic drivers influencing the seasonal variation of common bean yield and their impact on genotype ranking across Brazil. Utilizing extensive databases, such as historical field trial records, allows for deeper insights into the impacts of environmental features on phenotypic variation, guiding plant breeders in addressing genotype-by-environment interactions that limit cultivar targeting and genetic progress. We applied an envirotyping-informed (EI) linear mixed-effects model (LMM) to assess climatic drivers and their effects on yield variation across diverse years, elite genotypes, and regions. Our findings identified distinct seasonal environmental types within each region. Air temperature emerged as a key factor, explaining 40 % to 80 % of the phenotypic variation in grain yield. The Midwest region, where the main breeding nursery is located, is primarily limited by temperature, while other regions, such as the Southeast, exhibit different factors affecting yield variations. The inclusion of EI-LMM enabled cultivar ranking based on genetic mean incremental predict value and the calculation of genotype relative importance using analysis of variance (ANOVA). These outcomes connect data from advanced breeding trials and inform decisions about cultivar development, considering regional environmental specificities and within-season variations. Future studies should incorporate genotype-by-environment-by-management interactions to better understand climate adaptation in common beans, bridging the gap between breeding efforts and farmer needs. MenosCommon beans (Phaseolus vulgaris L.) is a staple food crop cultivated across various regions, seasons, and management systems in Brazil. To ensure production stability, it is essential to understand how climate factors affect cultivar development. This study aimed to determine the main edaphoclimatic drivers influencing the seasonal variation of common bean yield and their impact on genotype ranking across Brazil. Utilizing extensive databases, such as historical field trial records, allows for deeper insights into the impacts of environmental features on phenotypic variation, guiding plant breeders in addressing genotype-by-environment interactions that limit cultivar targeting and genetic progress. We applied an envirotyping-informed (EI) linear mixed-effects model (LMM) to assess climatic drivers and their effects on yield variation across diverse years, elite genotypes, and regions. Our findings identified distinct seasonal environmental types within each region. Air temperature emerged as a key factor, explaining 40 % to 80 % of the phenotypic variation in grain yield. The Midwest region, where the main breeding nursery is located, is primarily limited by temperature, while other regions, such as the Southeast, exhibit different factors affecting yield variations. The inclusion of EI-LMM enabled cultivar ranking based on genetic mean incremental predict value and the calculation of genotype relative importance using analysis of variance (ANOVA). These outcomes connect d... Mostrar Tudo |
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Palavras-Chave: |
Fatores edafoclimáticos. |
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Thesagro: |
Feijão; Phaseolus Vulgaris; Produtividade. |
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Thesaurus Nal: |
Beans; Climatic factors. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
LEADER 02756naa a2200289 a 4500 001 2179597 005 2025-10-10 008 2025 bl uuuu u00u1 u #d 024 7 $ahttps://doi.org/10.1016/j.eja.2025.127821$2DOI 100 1 $aHEINEMANN, A. B. 245 $aEnvirotyping-informed mixed models to study the climatic drivers and yield seasonal variation for common beans in Brazil.$h[electronic resource] 260 $c2025 300 $a1-15 520 $aCommon beans (Phaseolus vulgaris L.) is a staple food crop cultivated across various regions, seasons, and management systems in Brazil. To ensure production stability, it is essential to understand how climate factors affect cultivar development. This study aimed to determine the main edaphoclimatic drivers influencing the seasonal variation of common bean yield and their impact on genotype ranking across Brazil. Utilizing extensive databases, such as historical field trial records, allows for deeper insights into the impacts of environmental features on phenotypic variation, guiding plant breeders in addressing genotype-by-environment interactions that limit cultivar targeting and genetic progress. We applied an envirotyping-informed (EI) linear mixed-effects model (LMM) to assess climatic drivers and their effects on yield variation across diverse years, elite genotypes, and regions. Our findings identified distinct seasonal environmental types within each region. Air temperature emerged as a key factor, explaining 40 % to 80 % of the phenotypic variation in grain yield. The Midwest region, where the main breeding nursery is located, is primarily limited by temperature, while other regions, such as the Southeast, exhibit different factors affecting yield variations. The inclusion of EI-LMM enabled cultivar ranking based on genetic mean incremental predict value and the calculation of genotype relative importance using analysis of variance (ANOVA). These outcomes connect data from advanced breeding trials and inform decisions about cultivar development, considering regional environmental specificities and within-season variations. Future studies should incorporate genotype-by-environment-by-management interactions to better understand climate adaptation in common beans, bridging the gap between breeding efforts and farmer needs. 650 $aBeans 650 $aClimatic factors 650 $aFeijão 650 $aPhaseolus Vulgaris 650 $aProdutividade 653 $aFatores edafoclimáticos 700 1 $aMATTA, D. H. da 700 1 $aSTONE, L. F. 700 1 $aCOSTA-NETO, G. 700 1 $aRESENDE, R. T. 700 1 $aGONÇALVES, P. A. de O. 700 1 $aJUSTINO, L. F. 773 $tEuropean Journal of Agronomy$gv. 171, 127821, Oct. 2025.
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Embrapa Arroz e Feijão (CNPAF) |
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| 1. |  | GINJA, C.; GAMA, L. T.; CORTÉS, O.; BURRIEL, I. M.; VEGA-PLA , J. L.; PENEDO, C.; SPONENBERG, P.; CAÑÓN, J.; SANZ, A.; EGITO, A. A. do; ALVAREZ, L. A.; GIOVAMBATTISTA, G.; AGHA, S.; ROGBERG-MUÑOZ, A.; LARA, M. A. C.; DELGADO, J. V.; MARTINEZ, A.; AFONSO, S.; AGUIRRE, L.; ARMSTRONG, E.; VALLEJO, M. E. C.; CANALES, A.; CASSAMÁ, B.; CONTRERAS, G; CORDEIRO, J. M. M.; DUNNER, S.; ELBELTAGY, A.; FIORAVANTI, M. C. S.; CARPIO, M. G.; GÓMEZ, M.; HERNÁNDEZ, A.; HERNANDEZ, D.; JULIANO, R. S.; LANDI, V.; MARQUES, J. R.; MARTÍNEZ, R. D.; MARTÍNEZ, O. R.; MELUCCI, L.; FLORES, B. M.; MÚJICA, F.; PARÉS I CASANOVA, P. M.; QUIROZ, J.; RODELLAR, C.; TJON, G.; ADEBAMBO, T.; UFFO, O.; VARGAS, J. C.; VILLALOBOS, A.; ZARAGOZA, P. The genetic ancestry of american creole cattle inferred from uniparental and autosomal genetic markers. Scientific Reports, v. 9, n. 11486, p. 1-16, 2019.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
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