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| 19. |  | MOREIRA, S. O.; KUHLCAMP, K. T.; BARROS, F. L. de S.; OLIVEIRA, S. B. de; TRINDADE, R. dos S. Path analysis under multicollinearity for papaya production of the Solo and Formosa groups. Revista Brasileira de Fruticultura, Jaboticabal, v. 40, n. 3, e-110, 2018.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 20. | | BERILLI, A. P. C. G.; PEREIRA, M. G.; TRINDADE, R. dos S.; COSTA, F. R. da; CUNHA, K. S. da. Response to the selection in the 11th cycle of reciprocal recurrent selection among full-sib families of maize. Acta Scientiarum, Maringá, v. 35, n. 4, p. 435-441, 2013.| Biblioteca(s): Embrapa Milho e Sorgo. |
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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: |
23/03/2023 |
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Data da última atualização: |
14/06/2023 |
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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: |
CHAVES, S. F. S.; EVANGELISTA, J. S. P. C.; TRINDADE, R. dos S.; DIAS, L. A. S.; GUIMARAES, P. E. de O.; GUIMARAES, L. J. M.; ALVES, R. S.; BHERING, L. L.; DIAS, K. O. G. |
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Afiliação: |
SAULO F. S. CHAVES, Universidade Federal de Viçosa; JENIFFER S. P. C. EVANGELISTA, Universidade Federal de Viçosa; ROBERTO DOS SANTOS TRINDADE, CNPMS; LUIZ A. S. DIAS, Universidade Federal de Viçosa; PAULO EVARISTO DE O GUIMARAES, CNPMS; LAURO JOSE MOREIRA GUIMARAES, CNPMS; RODRIGO S. ALVES, Universidade Federal de Viçosa; LEONARDO L. BHERING, Universidade Federal de Viçosa; KAIO O. G. DIAS, Universidade Federal de Viçosa. |
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Título: |
Employing factor analytic tools for selecting high-performance and stable tropical maize hybrids. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Crop Science, v. 63, n. 3, p. 1114-1125, 2023. |
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DOI: |
https://doi.org/10.1002/csc2.20911 |
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Idioma: |
Inglês |
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Conteúdo: |
Genotype-by-environment interaction (GEI) is a major concern in tropical maize breeding. Here, we used factor analytic mixed models (FAMM) to study GEI in a tropical maize dataset. Our goal was to select high-performance and stable hybrids using factor analytic selection tools (FAST) derived from FAMM outputs. Because the dataset comprised two different planting seasons, we also investigated differences in the genetic gains between seasonal and general selection (i.e., for both seasons simultaneously). The trials were installed in a lattice design with 36 hybrids containing two replicates and blocks with six plants each. We evaluated 53 hybrids and seven checks in 48 environments, represented by a combination of locations, years and seasons. We fitted the FAMMs with distinct sets of factors. The best-fitted FAMM was selected considering a parsimony-explained variance balance. Using the best FAMM for both seasonal and general analyses, we estimated the following selection tools: overall performance (OP); root mean square deviation (RMSD), which represents general stability; and responsiveness , which represents specific stability. We selected hybrids based on an index built with OP and RMSD. Five and three hybrids were selected considering both general and seasonal analyses for the first and second season, respectively. Two hybrids were amongst the top eight for both seasonal analyses (i.e., only first season and only second season simultaenously). Higher genetic gains may be obtained by employing FAMM and using FAST in each season rather than analysing both seasons in a joint fashion. MenosGenotype-by-environment interaction (GEI) is a major concern in tropical maize breeding. Here, we used factor analytic mixed models (FAMM) to study GEI in a tropical maize dataset. Our goal was to select high-performance and stable hybrids using factor analytic selection tools (FAST) derived from FAMM outputs. Because the dataset comprised two different planting seasons, we also investigated differences in the genetic gains between seasonal and general selection (i.e., for both seasons simultaneously). The trials were installed in a lattice design with 36 hybrids containing two replicates and blocks with six plants each. We evaluated 53 hybrids and seven checks in 48 environments, represented by a combination of locations, years and seasons. We fitted the FAMMs with distinct sets of factors. The best-fitted FAMM was selected considering a parsimony-explained variance balance. Using the best FAMM for both seasonal and general analyses, we estimated the following selection tools: overall performance (OP); root mean square deviation (RMSD), which represents general stability; and responsiveness , which represents specific stability. We selected hybrids based on an index built with OP and RMSD. Five and three hybrids were selected considering both general and seasonal analyses for the first and second season, respectively. Two hybrids were amongst the top eight for both seasonal analyses (i.e., only first season and only second season simultaenously). Higher genetic gains may be... Mostrar Tudo |
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Palavras-Chave: |
Interação genótipo-ambiente. |
|
Thesagro: |
Genética Vegetal; Hibrido; Milho; Zea Mays. |
|
Categoria do assunto: |
F Plantas e Produtos de Origem Vegetal |
|
Marc: |
LEADER 02486naa a2200289 a 4500
001 2152618
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008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1002/csc2.20911$2DOI
100 1 $aCHAVES, S. F. S.
245 $aEmploying factor analytic tools for selecting high-performance and stable tropical maize hybrids.$h[electronic resource]
260 $c2023
520 $aGenotype-by-environment interaction (GEI) is a major concern in tropical maize breeding. Here, we used factor analytic mixed models (FAMM) to study GEI in a tropical maize dataset. Our goal was to select high-performance and stable hybrids using factor analytic selection tools (FAST) derived from FAMM outputs. Because the dataset comprised two different planting seasons, we also investigated differences in the genetic gains between seasonal and general selection (i.e., for both seasons simultaneously). The trials were installed in a lattice design with 36 hybrids containing two replicates and blocks with six plants each. We evaluated 53 hybrids and seven checks in 48 environments, represented by a combination of locations, years and seasons. We fitted the FAMMs with distinct sets of factors. The best-fitted FAMM was selected considering a parsimony-explained variance balance. Using the best FAMM for both seasonal and general analyses, we estimated the following selection tools: overall performance (OP); root mean square deviation (RMSD), which represents general stability; and responsiveness , which represents specific stability. We selected hybrids based on an index built with OP and RMSD. Five and three hybrids were selected considering both general and seasonal analyses for the first and second season, respectively. Two hybrids were amongst the top eight for both seasonal analyses (i.e., only first season and only second season simultaenously). Higher genetic gains may be obtained by employing FAMM and using FAST in each season rather than analysing both seasons in a joint fashion.
650 $aGenética Vegetal
650 $aHibrido
650 $aMilho
650 $aZea Mays
653 $aInteração genótipo-ambiente
700 1 $aEVANGELISTA, J. S. P. C.
700 1 $aTRINDADE, R. dos S.
700 1 $aDIAS, L. A. S.
700 1 $aGUIMARAES, P. E. de O.
700 1 $aGUIMARAES, L. J. M.
700 1 $aALVES, R. S.
700 1 $aBHERING, L. L.
700 1 $aDIAS, K. O. G.
773 $tCrop Science$gv. 63, n. 3, p. 1114-1125, 2023.
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