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| Registros recuperados : 12 | |
| 1. |  | SOUZA, B. M. de; FREITAS, M. L. M.; GEZAN, S. A.; ZANATTO, B.; AGUIAR, A. V. de. Genetic parameters, genotype-by-environment interaction, and genetic gains in Corymbia citriodora hook. In: SIMPOSIO INTERNACIONAL DE RECURSOS GENÉTICOS PARA LAS AMÉRICAS Y EL CARIBE, 11., 2017, Guadalajara. Resúmenes... Guadalajara: [s. n.], 2017. p. 172.| Biblioteca(s): Embrapa Florestas. |
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| 3. | | DIAS, K. O. das G.; GEZAN, S. A.; GUIMARAES, C. T.; NODA, R. W.; SOUZA, J. C. de; PASTINA, M. M.; GUIMARAES, L. J. M. Seleção genômica para tolerância ao déficit hídrico em milho. In: CONGRESSO NACIONAL DE MILHO E SORGO, 31., 2016, Bento Gonçalves. Milho e sorgo: inovações, mercados e segurança alimentar: anais. Sete Lagoas: Associação Brasileira de Milho e Sorgo, 2016.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 4. | | MUÑOZ, P. R.; RESENDE JUNIOR, M. F. R.; GEZAN, S. A.; RESENDE, M. D. V. de; CAMPOS, G. de los; KIRST, M.; HUBER, D.; PETER, G. F. Unraveling additive from nonadditive effects using genomic relationship matrices. Genetics, v. 198, p. 1759-1768, Dec. 2014.| Biblioteca(s): Embrapa Florestas. |
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| 5. | | SOUZA, B. M. de; FREITAS, M. L. M.; SEBBENN, A. M.; GEZAN, S. A.; ZANATTO, B.; ZULIAN, D. F.; LOPES, M. T. G.; LONGUI, E. L.; GUERRINI, I. A.; AGUIAR, A. V. de. Genotype-by-environment interaction in Corymbia citriodora (Hook.) K.D. Hill, & L.A.S. Johnson progeny test in Luiz Antonio, Brazil. Forest Ecology and Management, v. 460, article 117855, Mar. 2020. 8 p.| Biblioteca(s): Embrapa Florestas. |
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| 6. | | RIOS, E. F.; ANDRADE, M. H. M. L.; RESENDE JR, M. F. R.; KIRST, M.; RESENDE, M. D. V. de; ALMEIDA FILHO, J. O. E. de; GEZAN, S. A.; MUNOZ, P. Genomic prediction in family bulks using different traits and cross-validations in pine. G3: Genes, Genomes, Genetics, v. 11, n. 9, p. 1-12, 2021.| Biblioteca(s): Embrapa Café. |
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| 7. | | MULLER, B. S. F.; ALMEIDA FILHO, J. E. de; LIMA, B. M.; GARCIA, C. C.; MISSIAGGIA, A.; AGUIAR, A. M.; TAKAHASHI, E.; KIRST, M.; GEZAN, S. A.; SILVA JUNIOR, O. B. da; NEVES, L. G.; GRATTAPAGLIA, D. Independent and Joint-GWAS for growth traits in Eucalyptus by assembling genome-wide data for 3373 individuals across four breeding populations. The New phytologist, v. 221, n. 2, p. 818-833, 2019. Na publicação: Orzenil B. Silva-Junior.| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 8. | | FERREIRA, F. M.; CHAVES, S. F. S.; BHERING, L. L.; ALVES, R. S.; TAKAHASHI, E. K.; SOUSA, J. E.; RESENDE, M. D. V. de; LEITE, F. P.; GEZAN, S. A.; VIANA, J. M. S.; FERNANDES, S. B.; DIAS, K. O. G. A novel strategy to predict clonal composites by jointly modeling spatial variation and genetic competition. Forest Ecology and Management, v. 548, Article 121393, 2023. 10 p.| Biblioteca(s): Embrapa Café. |
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| 9. | | OLIVEIRA, I. C. M.; GUILHEN, J. H. S.; RIBEIRO, P. C. de O.; GEZAN, S. A.; SCHAFFERT, R. E.; SIMEONE, M. L. F.; DAMASCENO, C. M. B.; CARNEIRO, J. E. de S.; CARNEIRO, P. C. S.; PARRELLA, R. A. da C.; PASTINA, M. M. Genotype-by-environment interaction and yield stability analysis of biomass sorghum hybrids using factor analytic models and environmental covariates. Field Crops Research, v. 257, 107929, 2020.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 10. | | DIAS, K. O. das G.; GEZAN, S. A.; GUIMARÃES, C. T.; NAZARIAN, A.; SILVA, L. da C. e; PARENTONI, S. N.; GUIMARAES, P. E. de O.; ANONI, C. de O.; PÁDUA, J. M. V.; PINTO, M. de O.; NODA, R. W.; RIBEIRO, C. A. G.; MAGALHAES, J. V. de; GARCIA, A. A. F.; SOUZA, J. C. de; GUIMARAES, L. J. M.; PASTINA, M. M. Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials. Heredity, London, v. 121, n. 1, p. 24-37, 2018.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 11. | | PADUA, J. M. V.; DIAS, K. O. das G.; PASTINA, M. M.; SOUZA, J. C. de; QUEIROZ, V. A. V.; COSTA, R. V. da; SILVA, M. B. P. da; RIBEIRO, C. A. G.; GUIMARAES, C. T.; GEZAN, S. A.; GUIMARAES, L. J. M. A multi-environment trials diallel analysis provides insights on the inheritance of fumonisin contamination resistance in tropical maize. Euphytica, Dordrecht, v. 211, n. 3, p. 277-285, 2016| Biblioteca(s): Embrapa Milho e Sorgo. |
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| 12. | | DIAS, K. O. das G.; GEZAN, S. A.; GUIMARAES, C. T.; MAGALHAES, J. V. de; GUIMARAES, P. E. de O.; CARNEIRO, N. P.; PORTUGAL, A. F.; BASTOS, E. A.; CARDOSO, M. J.; ANONI, C. de O.; SOUZA, J. C. de; GUIMARAES, L. J. M.; PASTINA, M. M. Estimating genotype X environment interaction for and genetic correlations among drought tolerance traits in maize via factor analytic multiplicative mixed models. Crop Science, Madison, v. 58, p. 72-83, Jan. 2018. Publicado online em 30 out. 2017.| Biblioteca(s): Embrapa Milho e Sorgo. |
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| Registros recuperados : 12 | |
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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: |
10/11/2017 |
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Data da última atualização: |
24/06/2019 |
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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: |
DIAS, K. O. das G.; GEZAN, S. A.; GUIMARAES, C. T.; MAGALHAES, J. V. de; GUIMARAES, P. E. de O.; CARNEIRO, N. P.; PORTUGAL, A. F.; BASTOS, E. A.; CARDOSO, M. J.; ANONI, C. de O.; SOUZA, J. C. de; GUIMARAES, L. J. M.; PASTINA, M. M. |
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Afiliação: |
Kaio Olímpio das Graças Dias, Universidade Federal de Lavras; Salvador Alejandro Gezan, University of Florida; CLAUDIA TEIXEIRA GUIMARAES, CNPMS; JURANDIR VIEIRA DE MAGALHAES, CNPMS; PAULO EVARISTO DE O GUIMARAES, CNPMS; NEWTON PORTILHO CARNEIRO, CNPMS; ARLEY FIGUEIREDO PORTUGAL, CNPMS; EDSON ALVES BASTOS, CPAMN; MILTON JOSE CARDOSO, CPAMN; Carina de Oliveira Anoni, Escola Superior de Agricultura "Luiz de Queiroz"; João Cândido de Souza, Universidade Federal de Lavras; LAURO JOSE MOREIRA GUIMARAES, CNPMS; MARIA MARTA PASTINA, CNPMS. |
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Título: |
Estimating genotype X environment interaction for and genetic correlations among drought tolerance traits in maize via factor analytic multiplicative mixed models. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
Crop Science, Madison, v. 58, p. 72-83, Jan. 2018. |
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DOI: |
10.2135/cropsci2016.07.0566 |
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Idioma: |
Inglês |
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Notas: |
Publicado online em 30 out. 2017. |
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Conteúdo: |
Water deficit is one of the most common causes of severe crop-production losses worldwide in maize (Zea mays L.). The main goal of this study was to infer about genotype X environment interaction (G X E) and to estimate genetic correlations between drought tolerance traits in maize using factor analytic (FA) multiplicative mixed models in the context of multi-environment trial (MET) and multi-trait multi-environment trial (MTMET) analyses. The traits measured were: grain yield (GY), ears per plot (EPP), anthesis-silking interval (ASI), female flowering time (FFT), and male flowering time (MFT). Three-hundred and eight hybrids were evaluated in a total of eight trials conducted under water-stressed (WS) and well-watered (WW) conditions across 2 yr and two locations in Brazil. For most of the traits (GY, ASI, and FFT), the magnitude of the genetic variances differed across WS and WW conditions. Genetic correlations between water conditions for FFT and MFT were 0.81 and 0.82, respectively, indicating that it might be unnecessary to measure these traits in both water conditions. Grain yield and EPP showed moderate to high G X E, with genetic correlations of 0.57 and 0.39 between WS and WW conditions, respectively, which suggested that gene expression was not consistent across different water regimes. Therefore, it is necessary to evaluate these traits under both water conditions. Genetic correlations between pairs of traits, in general, were higher under WS conditions compared with WW conditions.Grain yield exhibited moderate correlations with EPP (r = 0.62) and FFT (r = - 0.42) under WS conditions. The FA models can be a useful tool for MET and MTMET analyses in maize breeding programs for drought tolerance. MenosWater deficit is one of the most common causes of severe crop-production losses worldwide in maize (Zea mays L.). The main goal of this study was to infer about genotype X environment interaction (G X E) and to estimate genetic correlations between drought tolerance traits in maize using factor analytic (FA) multiplicative mixed models in the context of multi-environment trial (MET) and multi-trait multi-environment trial (MTMET) analyses. The traits measured were: grain yield (GY), ears per plot (EPP), anthesis-silking interval (ASI), female flowering time (FFT), and male flowering time (MFT). Three-hundred and eight hybrids were evaluated in a total of eight trials conducted under water-stressed (WS) and well-watered (WW) conditions across 2 yr and two locations in Brazil. For most of the traits (GY, ASI, and FFT), the magnitude of the genetic variances differed across WS and WW conditions. Genetic correlations between water conditions for FFT and MFT were 0.81 and 0.82, respectively, indicating that it might be unnecessary to measure these traits in both water conditions. Grain yield and EPP showed moderate to high G X E, with genetic correlations of 0.57 and 0.39 between WS and WW conditions, respectively, which suggested that gene expression was not consistent across different water regimes. Therefore, it is necessary to evaluate these traits under both water conditions. Genetic correlations between pairs of traits, in general, were higher under WS conditions compared w... Mostrar Tudo |
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Palavras-Chave: |
Tolerância à seca. |
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Thesagro: |
Genótipo; Milho. |
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Categoria do assunto: |
G Melhoramento Genético |
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Marc: |
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024 7 $a10.2135/cropsci2016.07.0566$2DOI
100 1 $aDIAS, K. O. das G.
245 $aEstimating genotype X environment interaction for and genetic correlations among drought tolerance traits in maize via factor analytic multiplicative mixed models.$h[electronic resource]
260 $c2018
500 $aPublicado online em 30 out. 2017.
520 $aWater deficit is one of the most common causes of severe crop-production losses worldwide in maize (Zea mays L.). The main goal of this study was to infer about genotype X environment interaction (G X E) and to estimate genetic correlations between drought tolerance traits in maize using factor analytic (FA) multiplicative mixed models in the context of multi-environment trial (MET) and multi-trait multi-environment trial (MTMET) analyses. The traits measured were: grain yield (GY), ears per plot (EPP), anthesis-silking interval (ASI), female flowering time (FFT), and male flowering time (MFT). Three-hundred and eight hybrids were evaluated in a total of eight trials conducted under water-stressed (WS) and well-watered (WW) conditions across 2 yr and two locations in Brazil. For most of the traits (GY, ASI, and FFT), the magnitude of the genetic variances differed across WS and WW conditions. Genetic correlations between water conditions for FFT and MFT were 0.81 and 0.82, respectively, indicating that it might be unnecessary to measure these traits in both water conditions. Grain yield and EPP showed moderate to high G X E, with genetic correlations of 0.57 and 0.39 between WS and WW conditions, respectively, which suggested that gene expression was not consistent across different water regimes. Therefore, it is necessary to evaluate these traits under both water conditions. Genetic correlations between pairs of traits, in general, were higher under WS conditions compared with WW conditions.Grain yield exhibited moderate correlations with EPP (r = 0.62) and FFT (r = - 0.42) under WS conditions. The FA models can be a useful tool for MET and MTMET analyses in maize breeding programs for drought tolerance.
650 $aGenótipo
650 $aMilho
653 $aTolerância à seca
700 1 $aGEZAN, S. A.
700 1 $aGUIMARAES, C. T.
700 1 $aMAGALHAES, J. V. de
700 1 $aGUIMARAES, P. E. de O.
700 1 $aCARNEIRO, N. P.
700 1 $aPORTUGAL, A. F.
700 1 $aBASTOS, E. A.
700 1 $aCARDOSO, M. J.
700 1 $aANONI, C. de O.
700 1 $aSOUZA, J. C. de
700 1 $aGUIMARAES, L. J. M.
700 1 $aPASTINA, M. M.
773 $tCrop Science, Madison$gv. 58, p. 72-83, Jan. 2018.
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