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| 56. |  | RAMSEY, G. B.; SMITH, M. A. Market Diseases of cabbage, cauliflower, turnips, cucumber, melons, and related crops. Washington, D. C.: Agricultural Marketing Service, 1961. p. 1-49 (Agricultural Marketing Service, Agriculture Handbook, 184).| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| Registros recuperados : 163 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Milho e Sorgo. Para informações adicionais entre em contato com cnpms.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Milho e Sorgo. |
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Data corrente: |
19/07/2021 |
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Data da última atualização: |
05/10/2021 |
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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: |
SOUZA, V. F. de; RIBEIRO, P. C. de O.; VIEIRA JÚNIOR, I. C.; OLIVEIRA, I. C. M.; DAMASCENO, C. M. B.; SCHAFFERT, R. E.; PARRELLA, R. A. da C.; DIAS, K. O. das G.; PASTINA, M. M. |
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Afiliação: |
VANDER FILLIPE DE SOUZA; PEDRO CÉSAR DE OLIVEIRA RIBEIRO, Universidade Federal de Viçosa; INDALÉCIO CUNHA VIEIRA JÚNIOR, Universidade Federal de Lavras; ISADORA CRISTINA MARTINS OLIVEIRA; CYNTHIA MARIA BORGES DAMASCENO, CNPMS; ROBERT EUGENE SCHAFFERT, CNPMS; RAFAEL AUGUSTO DA COSTA PARRELLA, CNPMS; KAIO OLIMPIO DAS GRAÇAS DIAS, Escola Superior de Agricultura Luiz de Queiroz; MARIA MARTA PASTINA, CNPMS. |
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Título: |
Exploring genotype x environment interaction in sweet sorghum under tropical environments. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
Agronomy Journal, v. 113, p. 3005-3018, 2021. |
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DOI: |
http://dx.doi.org/10.1002/agj2.20696 |
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Idioma: |
Inglês |
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Conteúdo: |
Understanding the genotype-by-environment interactions (GEI) is crucial to release sweet sorghum [Sorghum bicolor (L.) Moench] cultivars with stable and high agronomic performance under tropical environments. Therefore, linear mixed models could be used to face this challenge by leveraging the biological process of GEI into cultivar recommendation. The goals of this study were: (a) to explore GEI patterns under tropical conditions to select stable and high-yielding genotypes for energyuse in the bioethanol industry; and (b) to evaluate the advantages of linear mixed models taking into account simultaneously the genetic and the residual correlations across environments and the genomic relationship between genotypes. The breeding dataset was comprised of 41 genotypes evaluated for Tonnes of brix per hectare (TBH) in late-stage trials over 32 tropical environments. The models incorporating simultaneously the genomic relationship matrix of genotypes and the genetic and the residual correlations across environments showed the lowest values of Akaike Information Criterion (AIC) compared to the standard phenotypic models, and also increased the expected genetic gains of TBH across years. Based on the best models selected by AIC, the genotypes 38 (CMSXS5006), 6 (BRS511), 5 (CMSXS633), 9 (CMSXS637), and 12 (BRS506) exhibited the highest productivity in TBH. Particularly, the genotype 9 (CMSXS637) showed broad stability and high productivity under tropical environments, besides the desirable traits for bioethanol production. These results highlight the importance of modeling the genomic relationship between genotypes and the genetic and the residual correlations across environments to increase the breeding efficiency of sweet sorghum under tropical environments MenosUnderstanding the genotype-by-environment interactions (GEI) is crucial to release sweet sorghum [Sorghum bicolor (L.) Moench] cultivars with stable and high agronomic performance under tropical environments. Therefore, linear mixed models could be used to face this challenge by leveraging the biological process of GEI into cultivar recommendation. The goals of this study were: (a) to explore GEI patterns under tropical conditions to select stable and high-yielding genotypes for energyuse in the bioethanol industry; and (b) to evaluate the advantages of linear mixed models taking into account simultaneously the genetic and the residual correlations across environments and the genomic relationship between genotypes. The breeding dataset was comprised of 41 genotypes evaluated for Tonnes of brix per hectare (TBH) in late-stage trials over 32 tropical environments. The models incorporating simultaneously the genomic relationship matrix of genotypes and the genetic and the residual correlations across environments showed the lowest values of Akaike Information Criterion (AIC) compared to the standard phenotypic models, and also increased the expected genetic gains of TBH across years. Based on the best models selected by AIC, the genotypes 38 (CMSXS5006), 6 (BRS511), 5 (CMSXS633), 9 (CMSXS637), and 12 (BRS506) exhibited the highest productivity in TBH. Particularly, the genotype 9 (CMSXS637) showed broad stability and high productivity under tropical environments, besides the de... Mostrar Tudo |
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Palavras-Chave: |
Interação genotipo x ambiente. |
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Thesagro: |
Colheita; Seleção; Sorgo; Sorgo Açucareiro; Variedade. |
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Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
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Marc: |
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008 2021 bl uuuu u00u1 u #d
024 7 $ahttp://dx.doi.org/10.1002/agj2.20696$2DOI
100 1 $aSOUZA, V. F. de
245 $aExploring genotype x environment interaction in sweet sorghum under tropical environments.$h[electronic resource]
260 $c2021
520 $aUnderstanding the genotype-by-environment interactions (GEI) is crucial to release sweet sorghum [Sorghum bicolor (L.) Moench] cultivars with stable and high agronomic performance under tropical environments. Therefore, linear mixed models could be used to face this challenge by leveraging the biological process of GEI into cultivar recommendation. The goals of this study were: (a) to explore GEI patterns under tropical conditions to select stable and high-yielding genotypes for energyuse in the bioethanol industry; and (b) to evaluate the advantages of linear mixed models taking into account simultaneously the genetic and the residual correlations across environments and the genomic relationship between genotypes. The breeding dataset was comprised of 41 genotypes evaluated for Tonnes of brix per hectare (TBH) in late-stage trials over 32 tropical environments. The models incorporating simultaneously the genomic relationship matrix of genotypes and the genetic and the residual correlations across environments showed the lowest values of Akaike Information Criterion (AIC) compared to the standard phenotypic models, and also increased the expected genetic gains of TBH across years. Based on the best models selected by AIC, the genotypes 38 (CMSXS5006), 6 (BRS511), 5 (CMSXS633), 9 (CMSXS637), and 12 (BRS506) exhibited the highest productivity in TBH. Particularly, the genotype 9 (CMSXS637) showed broad stability and high productivity under tropical environments, besides the desirable traits for bioethanol production. These results highlight the importance of modeling the genomic relationship between genotypes and the genetic and the residual correlations across environments to increase the breeding efficiency of sweet sorghum under tropical environments
650 $aColheita
650 $aSeleção
650 $aSorgo
650 $aSorgo Açucareiro
650 $aVariedade
653 $aInteração genotipo x ambiente
700 1 $aRIBEIRO, P. C. de O.
700 1 $aVIEIRA JÚNIOR, I. C.
700 1 $aOLIVEIRA, I. C. M.
700 1 $aDAMASCENO, C. M. B.
700 1 $aSCHAFFERT, R. E.
700 1 $aPARRELLA, R. A. da C.
700 1 $aDIAS, K. O. das G.
700 1 $aPASTINA, M. M.
773 $tAgronomy Journal$gv. 113, p. 3005-3018, 2021.
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