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| 12. |  | SUSSEL, A. A. B.; SILVA NETO, S. P. da; MOREIRA, C. T.; ALVES, R. S.; ALMEIDA, N. J. Correlação de diferentes metodologias de avaliação da ferrugem asiática em linhagens de soja. In: CONGRESSO BRASILEIRO DE SOJA, 6., 2012, Cuiabá. Soja: integração nacional e desenvolvimento sustentável: anais. Brasília, DF: Embrapa; Londrina: Embrapa Soja, 2012. 1 CD-ROM. Editado por Adilson de Oliveira Júnior, Clara Beatriz Hoffmann-Campo, Regina Maria Villas Bôas de Campos Leite, Ricardo Vilela Abdelnoor. VI CBSoja.| Biblioteca(s): Embrapa Cerrados. |
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| 13. | | SUSSEL, A. A. B.; SILVA NETO, S. P. da; MOREIRA, C. T.; ALVES, R. S.; ALMEIDA, N. J. Diferentes parâmetros patométricos para avaliação da ferrugem asiática em linhagens transgênicas de soja. In: CONGRESSO BRASILEIRO DE SOJA, 6., 2012, Cuiabá. Soja: integração nacional e desenvolvimento sustentável: anais. Brasília, DF: Embrapa; Londrina: Embrapa Soja, 2012. 1 CD-ROM. Editado por Adilson de Oliveira Júnior, Clara Beatriz Hoffmann-Campo, Regina Maria Villas Bôas de Campos Leite, Ricardo Vilela Abdelnoor. VI CBSoja.| Biblioteca(s): Embrapa Cerrados. |
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| 14. | | 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. Adaptability of cotton (Gossypium hirsutum) genotypes analysed using a Bayesian AMMI model. Crop and Pasture Science, v. 70, n. 7, p. 615-621, 2019.| Biblioteca(s): Embrapa Algodão. |
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| 15. | | CAIXETA, E. T.; RESENDE, M. D. V. de; ALKIMIM, E. R.; SOUSA, T. V.; OLIVEIRA, A. C. B. de; PEREIRA, A. A.; ALVES, R. S. Aceleração do melhoramento do cafeeiro via seleção genômica: agilidade e eficácia no lançamento de novas cultivares. Brasília, DF: Embrapa Café, 2022. 54 p. PDF. (Embrapa Café. Documentos, 17). Projeto SI04 - Genotipagem e seleção genômica em populações de melhoramento de Coffea arabica.| Biblioteca(s): Embrapa Café. |
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| 16. | | ALMEIDA, A. S.; ALVES, R. S.; FILGUEIRAS, H. A. C.; MENEZES, J. B.; PEREIRA, M. E. C.; MOURA, C. F. H. Conservação de melão Cantaloupe Hy-Mark tratado em pós-colheita com 1- metilciclopropeno (1- MC.POSTAL). Horticultura Brasileira, Brasília, v. 21, n. 2, jul. 2003. Suplemento 2. Trabalho apresentado no 43º Congresso Brasileiro de Olericultura, 2003. Publicado também como resumo em: Horticultura Brasileira, Brasília, v. 21, n. 2, p. 382, jul. 2003. Suplemento 1.| Biblioteca(s): Embrapa Hortaliças. |
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| 17. | | PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; ALVES, R. S.; FARIAS, F. J. C.; CARVALHO, L. P.; TEODORO, L. P. R.; TEODORO, P. E.; BHERING, L. L. Models for optimizing selection based on adaptability and stability of cotton genotypes. Ciência Rural, v. 51, n. 5, e20200530, p. 1-8, 2021. 8 p.| Biblioteca(s): Embrapa Algodão. |
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| 18. | | MALIKOUSKI, R. G.; PEIXOTO, M. A.; FERREIRA, F. M.; MORAIS, A. L. de; ALVES, R. S.; ZUCOLOTO, M.; BARBOSA, D. H. S. G.; BHERING, L. L. Genotypic diversity and genetic parameters of 'Tahiti' acid lime using different rootstocks. Pesquisa Agropecuária Brasileira, v. 58, e02768, 2023. Título em português: Diversidade genotípica e parâmetros genéticos de lima ácida 'Tahiti' com uso de diferentes porta-enxertos.| Biblioteca(s): Embrapa Mandioca e Fruticultura; Embrapa Unidades Centrais. |
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| 19. | | SILVA, J. O. da C. e; BRUCKNER, C. H.; CARNEIRO, P. C. S.; RESENDE, M. D. V. de; ALVES, R. S.; SILVA, D. F. P. da. Estimates of genetic parameters, genetic variability, and selection in the S1 generation of peach. Ciência Rural, v. 50, n. 10, e20190976, 2020. Título em português: Estimativas de parâmetros genéticos, variabilidade genética e seleção em geração S 1 de pessegueiros.| Biblioteca(s): Embrapa Café. |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Amazônia Oriental. Para informações adicionais entre em contato com cpatu.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
01/12/2022 |
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Data da última atualização: |
01/12/2022 |
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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: |
CHAVES, S. F. S.; EVANGELISTA, J. S. P. C.; ALVES, R. S.; FERREIRA, F. M.; DIAS, L. A. S.; ALVES, R. M.; DIAS, K. O. G.; BHERING, L. L. |
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Afiliação: |
SAULO F. S. CHAVES, UNIVERSIDADE FEDERAL DE VIÇOSA; JENIFFER S. P. C. EVANGELISTA, UNIVERSIDADE FEDERAL DE VIÇOSA; RODRIGO S. ALVES, UNIVERSIDADE FEDERAL DE LAVRAS; FILIPE M. FERREIRA, UNIVERSIDADE FEDERAL DE VIÇOSA; LUIZ A. S. DIAS, UNIVERSIDADE FEDERAL DE VIÇOSA; RAFAEL MOYSES ALVES, CPATU; KAIO O. G. DIAS, UNIVERSIDADE FEDERAL DE VIÇOSA; LEONARDO L. BHERING, UNIVERSIDADE FEDERAL DE VIÇOSA. |
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Título: |
Application of linear mixed models for multiple harvest/site trial analyses in perennial plant breeding. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Tree Genetics & Genomes, v. 18, n. 6, Article number: 44, Dec. 2022. |
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DOI: |
https://doi.org/10.1007/s11295-022-01576-5 |
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Idioma: |
Inglês |
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Conteúdo: |
The optimization of perennial plant breeding necessarily involves the evaluation of multi-harvest and/or multi-site trials. In these situations, modeling covariance structures can elevate accuracy. This study aimed to evaluate different covariance structures for multi-harvest and multi-site trial analyses, using two datasets (D1 and D2). In D1, 25 hybrids of Theobroma grandiflorum were evaluated in a complete randomized block design, during twelve consecutive harvest years. In D2, 215 clones of Eucalyptus spp. were evaluated in a complete randomized block design, in four sites. For both datasets, the covariance structures of the random effects were modeled, and their adequacy was tested by the Akaike and Bayesian information criteria. From the selected model, the variance components and genetic parameters were estimated. We also compared the expected genetic gains and the rankings of genotypes based on the genotypic values provided by the basic and the selected models. For D1, the third-order factor analytic model was the most suitable for genetic effects, while for D2, the unstructured model showed the best fit for such effects. The models provided a better insight into the variances dynamics over the harvest years/sites. The genetic gains were 3.52 percentage points higher in D1 and did not change in D2. Despite similar results, the standard model, modeled with covariance structures that assume homogeneity of co-variances, was not the most statistically appropriate model for D2 according to the information criteria. Therefore, the modeling of covariance structures can and should be used in the genetic evaluation of perennial plants MenosThe optimization of perennial plant breeding necessarily involves the evaluation of multi-harvest and/or multi-site trials. In these situations, modeling covariance structures can elevate accuracy. This study aimed to evaluate different covariance structures for multi-harvest and multi-site trial analyses, using two datasets (D1 and D2). In D1, 25 hybrids of Theobroma grandiflorum were evaluated in a complete randomized block design, during twelve consecutive harvest years. In D2, 215 clones of Eucalyptus spp. were evaluated in a complete randomized block design, in four sites. For both datasets, the covariance structures of the random effects were modeled, and their adequacy was tested by the Akaike and Bayesian information criteria. From the selected model, the variance components and genetic parameters were estimated. We also compared the expected genetic gains and the rankings of genotypes based on the genotypic values provided by the basic and the selected models. For D1, the third-order factor analytic model was the most suitable for genetic effects, while for D2, the unstructured model showed the best fit for such effects. The models provided a better insight into the variances dynamics over the harvest years/sites. The genetic gains were 3.52 percentage points higher in D1 and did not change in D2. Despite similar results, the standard model, modeled with covariance structures that assume homogeneity of co-variances, was not the most statistically appropriate model f... Mostrar Tudo |
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Thesagro: |
Árvore Frutífera; Floresta; Melhoramento. |
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Categoria do assunto: |
K Ciência Florestal e Produtos de Origem Vegetal |
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Marc: |
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024 7 $ahttps://doi.org/10.1007/s11295-022-01576-5$2DOI
100 1 $aCHAVES, S. F. S.
245 $aApplication of linear mixed models for multiple harvest/site trial analyses in perennial plant breeding.$h[electronic resource]
260 $c2022
520 $aThe optimization of perennial plant breeding necessarily involves the evaluation of multi-harvest and/or multi-site trials. In these situations, modeling covariance structures can elevate accuracy. This study aimed to evaluate different covariance structures for multi-harvest and multi-site trial analyses, using two datasets (D1 and D2). In D1, 25 hybrids of Theobroma grandiflorum were evaluated in a complete randomized block design, during twelve consecutive harvest years. In D2, 215 clones of Eucalyptus spp. were evaluated in a complete randomized block design, in four sites. For both datasets, the covariance structures of the random effects were modeled, and their adequacy was tested by the Akaike and Bayesian information criteria. From the selected model, the variance components and genetic parameters were estimated. We also compared the expected genetic gains and the rankings of genotypes based on the genotypic values provided by the basic and the selected models. For D1, the third-order factor analytic model was the most suitable for genetic effects, while for D2, the unstructured model showed the best fit for such effects. The models provided a better insight into the variances dynamics over the harvest years/sites. The genetic gains were 3.52 percentage points higher in D1 and did not change in D2. Despite similar results, the standard model, modeled with covariance structures that assume homogeneity of co-variances, was not the most statistically appropriate model for D2 according to the information criteria. Therefore, the modeling of covariance structures can and should be used in the genetic evaluation of perennial plants
650 $aÁrvore Frutífera
650 $aFloresta
650 $aMelhoramento
700 1 $aEVANGELISTA, J. S. P. C.
700 1 $aALVES, R. S.
700 1 $aFERREIRA, F. M.
700 1 $aDIAS, L. A. S.
700 1 $aALVES, R. M.
700 1 $aDIAS, K. O. G.
700 1 $aBHERING, L. L.
773 $tTree Genetics & Genomes$gv. 18, n. 6, Article number: 44, Dec. 2022.
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