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| Registros recuperados : 165 | |
| 33. |  | SAMAPAIO, G. V.; CARVALHO, H. W. L. de; DOURADO, V. V.; CARVALHO, B. C. L. de; SANTOS, M. X. dos. Comportamento de cultivares de milho no Planalto de Vitoria da Conquista no ano agricola de 2000/2001. In: CONGRESSO NACIONAL DE MILHO E SORGO, 24., 2002, Florianópolis, SC. Meio ambiente e a nova agenda para o agronegócio de milho e sorgo: [resumos expandidos]. Sete Lagoas: ABMS: Embrapa Milho e Sorgo; Florianópolis: Epagri, 2002. 1 CD-ROM.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| Registros recuperados : 165 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
20/01/2022 |
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Data da última atualização: |
20/01/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 2 |
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Autoria: |
EVANGELISTA, J. S. P. C.; PEIXOTO, M. A.; COELHO, I. F.; ALVES, R. S.; SILVA, F. F. e; RESENDE, M. D. V. de; SILVA, F. L. da; BHERING, L. L. |
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Afiliação: |
JENIFFER SANTANA PINTO COELHO EVANGELISTA, UFV; MARCO ANTÔNIO PEIXOTO, UFV; IGOR FERREIRA COELHO, UFV; RODRIGO SILVA ALVES, UFV; FABYANO FONSECA E SILVA, UFV; MARCOS DEON VILELA DE RESENDE, CNPCa; FELIPE LOPES DA SILVA, UFV; LEONARDO LOPES BHERING, UFV. |
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Título: |
Environmental stratification and genotype recommendation toward the soybean ideotype: a Bayesian approach. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Crop Breeding and Applied Biotechnology, v. 21, n. 1, e359721111, 2021. |
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DOI: |
https://doi.org/10.1590/1984-70332021v21n1a11 |
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Idioma: |
Inglês |
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Conteúdo: |
The genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation. Thus, the objectives of this study were: i) propose the Multi-Environment Index Based on Factor Analysis and Ideotype-Design/Markov Chain Monte Carlo (FAI/MCMC index), and ii) apply it for soybean genotypes recommendation. To this end, a data set with 30 soybean genotypes evaluated in 10 environments for grain yield trait was used. Variance components, genetic parameters and genetic values were estimated through MCMC algorithm. Environmental stratification was conducted by factor analyses and the selection of soybean genotypes was performed using the FAI/MCMC index. The results indicated the existence of genotypic variability and G×E interaction. The environments were grouped into three factors. The predicted genetic gains from indirect selection was 4.81%. Thus, our results suggest that the FAI/MCMC index can be successfully used in soybean breeding. |
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Thesagro: |
Genótipo; Glycine Soja; Soja. |
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Thesaurus NAL: |
Bayesian theory; Genotype; Seed stratification; Soybeans. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/230409/1/environmental-stratification-and-genotype.pdf
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Marc: |
LEADER 01935naa a2200301 a 4500
001 2139213
005 2022-01-20
008 2021 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1590/1984-70332021v21n1a11$2DOI
100 1 $aEVANGELISTA, J. S. P. C.
245 $aEnvironmental stratification and genotype recommendation toward the soybean ideotype$ba Bayesian approach.$h[electronic resource]
260 $c2021
520 $aThe genotype × environment (G×E) interaction plays an essential role in phenotypic expression and can lead to difficulties in genotypes recommendation. Thus, the objectives of this study were: i) propose the Multi-Environment Index Based on Factor Analysis and Ideotype-Design/Markov Chain Monte Carlo (FAI/MCMC index), and ii) apply it for soybean genotypes recommendation. To this end, a data set with 30 soybean genotypes evaluated in 10 environments for grain yield trait was used. Variance components, genetic parameters and genetic values were estimated through MCMC algorithm. Environmental stratification was conducted by factor analyses and the selection of soybean genotypes was performed using the FAI/MCMC index. The results indicated the existence of genotypic variability and G×E interaction. The environments were grouped into three factors. The predicted genetic gains from indirect selection was 4.81%. Thus, our results suggest that the FAI/MCMC index can be successfully used in soybean breeding.
650 $aBayesian theory
650 $aGenotype
650 $aSeed stratification
650 $aSoybeans
650 $aGenótipo
650 $aGlycine Soja
650 $aSoja
700 1 $aPEIXOTO, M. A.
700 1 $aCOELHO, I. F.
700 1 $aALVES, R. S.
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
700 1 $aSILVA, F. L. da
700 1 $aBHERING, L. L.
773 $tCrop Breeding and Applied Biotechnology$gv. 21, n. 1, e359721111, 2021.
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Registro original: |
Embrapa Café (CNPCa) |
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