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 | Acesso ao texto completo restrito à biblioteca da Embrapa Algodão. Para informações adicionais entre em contato com cnpa.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Algodão. |
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Data corrente: |
15/01/2020 |
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Data da última atualização: |
20/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
TEODORO, P. E.; AZEVEDO, C. F.; FARIAS, F. J. C.; ALVES, R. S.; PEIXOTO, L. de A.; RIBEIRO, L. P.; CARVALHO, L. P. de; BHERING, L. L. |
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Afiliação: |
Paulo Eduardo Teodoro, Universidade Federal de Mato Grosso do Sul - UFMS/CPCS; Camila Ferreira Azevedo, Universidade Federal de Viçosa - UFV; FRANCISCO JOSE CORREIA FARIAS, CNPA; Rodrigo Silva Alves, Universidade Federal de Viçosa - UFV; Leonardo de Azevedo Peixoto, Universidade Federal de Viçosa - UFV; Larissa Pereira Ribeiro, Universidade Federal de Viçosa - UFV; LUIZ PAULO DE CARVALHO, CNPA; Leonardo Lopes Bhering, Universidade Federal de Viçosa - UFV. |
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Título: |
Adaptability of cotton (Gossypium hirsutum) genotypes analysed using a Bayesian AMMI model. |
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Ano de publicação: |
2019 |
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Fonte/Imprenta: |
Crop and Pasture Science, v. 70, n. 7, p. 615-621, 2019. |
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Idioma: |
Inglês |
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Conteúdo: |
Cotton (Gossypium spp.) provides ~90% of the world?s textile fibre. The aim of this study was to use the principal additive effects and multiplicative interaction (AMMI) model under the Bayesian approach to recommend cotton genotypes for the Central-West region of Brazil. Eight trials with upland cotton genotypes were conducted during the 2008?09 harvest in the State of Mato Grosso, Brazil. The experiment included a randomised block design with 16 genotypes. The genotypes were evaluated for fibre yield, length and strength. Chains were simulated via the Markov chain Monte Carlo method with 300 000 iterations for the parameters of the Bayesian AMMI model. From the chains generated, the first 20 000 burn-in observations were discarded and samples were taken by jumping every 20 observations (thin). Bayesian analysis provided additional results to those obtained by the frequentist approach, highlighting the credibility regions in the biplot for the genotypic and environmental scores. Bayesian AMMI model allowed identification of a genotype that can be widely recommended; this genotype has genotypic values above the overall mean for the three evaluated traits and did not contribute to the genotype x environment interactions observed in these traits. In addition, adaptability of genotypes to specific environments was observed, which makes it possible to capitalise the positive effect of the genotype x environment interaction. |
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Palavras-Chave: |
Genetic selection; MCMC. |
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Thesaurus NAL: |
Cotton; Gossypium; Models. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02189naa a2200265 a 4500
001 2118774
005 2020-01-20
008 2019 bl uuuu u00u1 u #d
100 1 $aTEODORO, P. E.
245 $aAdaptability of cotton (Gossypium hirsutum) genotypes analysed using a Bayesian AMMI model.$h[electronic resource]
260 $c2019
520 $aCotton (Gossypium spp.) provides ~90% of the world?s textile fibre. The aim of this study was to use the principal additive effects and multiplicative interaction (AMMI) model under the Bayesian approach to recommend cotton genotypes for the Central-West region of Brazil. Eight trials with upland cotton genotypes were conducted during the 2008?09 harvest in the State of Mato Grosso, Brazil. The experiment included a randomised block design with 16 genotypes. The genotypes were evaluated for fibre yield, length and strength. Chains were simulated via the Markov chain Monte Carlo method with 300 000 iterations for the parameters of the Bayesian AMMI model. From the chains generated, the first 20 000 burn-in observations were discarded and samples were taken by jumping every 20 observations (thin). Bayesian analysis provided additional results to those obtained by the frequentist approach, highlighting the credibility regions in the biplot for the genotypic and environmental scores. Bayesian AMMI model allowed identification of a genotype that can be widely recommended; this genotype has genotypic values above the overall mean for the three evaluated traits and did not contribute to the genotype x environment interactions observed in these traits. In addition, adaptability of genotypes to specific environments was observed, which makes it possible to capitalise the positive effect of the genotype x environment interaction.
650 $aCotton
650 $aGossypium
650 $aModels
653 $aGenetic selection
653 $aMCMC
700 1 $aAZEVEDO, C. F.
700 1 $aFARIAS, F. J. C.
700 1 $aALVES, R. S.
700 1 $aPEIXOTO, L. de A.
700 1 $aRIBEIRO, L. P.
700 1 $aCARVALHO, L. P. de
700 1 $aBHERING, L. L.
773 $tCrop and Pasture Science$gv. 70, n. 7, p. 615-621, 2019.
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