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| Registros recuperados : 30 | |
| 2. |  | NASCIMENTO, M.; SILVA, F. F. e; SAFADI, T.; NASCIMENTO, A. C. C.; FERREIRA, R. de P.; CRUZ, C. D. Abordagem bayesiana para avaliação da adaptabilidade e estabilidade de genótipos de alfafa. Pesquisa Agropecuária Brasileira, Brasília, v. 46, n. 1, p. 26-32, jan. 2011.| Biblioteca(s): Embrapa Pecuária Sudeste; Embrapa Unidades Centrais. |
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| 3. | | NASCIMENTO, M.; NASCIMENTO, A. C. C.; CIRILLO, M. A.; FERREIRA, A.; PETERNELLI, L. A.; FERREIRA, R. de P. Association between responses obtained using adaptability and stability methods in alfalfa. Semina: Ciências Agrárias, Londrina, v. 34, n. 6, p. 2545-2554, nov./dez. 2013.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 4. | | NASCIMENTO, N; FERREIRA, A.; NASCIMENTO, A. C. C.; SILVA, F. F. e; FERREIRA, R. de P.; CRUZ, C. D. Multiple centroid method to evaluate the adaptability of alfalfa genotypes. Revista Ceres, Viçosa, v. 62, n. 1, p. 030-036, jan/fev, 2015| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 7. | | NASCIMENTO, M.; ROCHA, G. S. da; PINTO, D. S.; BARROSO, L. M. A.; NASCIMENTO, A. C. C.; FERREIRA, R. de P.; SILVA, F. F. e. Correlação de Spearman aplicada ao estudo de adaptabilidade e estabilidade em genótipos de alfafa. Investigacion Agrária, v. 15, n. 2, p. 83-90, 2013.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 10. | | SUELA, M. M.; AZEVEDO, C. F.; NASCIMENTO, A. C. C.; MOMEN, M.; OLIVEIRA, A. C. B. de; CAIXETA, E. T.; MOROTA, G.; NASCIMENTO, M. Genome-wide association study for morphological, physiological, and productive traits in Coffea arabica using structural equation models. Tree Genetics & Genomes, v. 19, n. 3, 2023. 17 p.| Biblioteca(s): Embrapa Café. |
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| 12. | | AZEVEDO, C. F.; CARVALHO, I. R.; NASCIMENTO, M.; SILVA, J. A. G. da; NASCIMENTO, A, C. C.; CRUZ, C. D.; HUTH, C.; ALMEIDA, H. C. F. de. Informative prior distribution applied to linseed for the estimation of genetic parameters using a small sample size. Pesquisa Agropecuária Brasileira, v. 57, e02793, 2022. Título em português: Distribuição a priori informativa aplicada à linhaça para estimação de parâmetros genéticos com uso de tamanho amostral reduzido.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 13. | | BARROSO, L. M. A.; NASCIMENTO, M.; NASCIMENTO, A. C. C.; FONSECA, F. F. e; CRUZ, C. D.; BHERING, L. L.; FERREIRA, R. de P. Metodologia para análise de adaptabilidade e estabilidade por meio de regressão quantílica. Pesquisa Agropecuária Brasileira, v. 50, n. 4, p. 290-297, abr. 2015.| Biblioteca(s): Embrapa Pecuária Sudeste. |
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| 14. | | BARROSO, L. M. A.; NASCIMENTO, M.; NASCIMENTO, A. C. C.; SILVA, F. F. e; CRUZ, C. D.; BHERING, L. L.; FERREIRA, R. de P. Metodologia para análise de adaptabilidade e estabilidade por meio de regressão quantílica. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 50, n. 4, p. 267-290-297, abr. 2015. Título em inglês: Methodology for analysis of adaptability and stability using quantile regression.| Biblioteca(s): Embrapa Unidades Centrais. |
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| 15. | | OLIVEIRA, G. F.; MIRANDA, T. L. R.; NASCIMENTO, A. C. C.; NASCIMENTO, M.; CAIXETA, E. T.; SILVA, L. de F.; ALKIMIM, E. R.; SILVA, F. L. da. Discrimination of varietal groups and hybrids of coffea canephora species using multivariate analysis. Revista Brasileira de Biometria, v. 39, n. 1, p. 194-201, 2021.| Biblioteca(s): Embrapa Café. |
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| 16. | | COSTA, J. A. da; AZEVEDO, C. F.; NASCIMENTO, M.; SILVA, F. F.; RESENDE, M. D. V. de; NASCIMENTO, A. C. C. Determination of optimal number of independent components in yield traits in rice. Scientia Agricola, v. 79, n. 6, p. 1-8, 2022.| Biblioteca(s): Embrapa Café. |
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| 17. | | COSTA, J. A. da; AZEVEDO, C. F.; NASCIMENTO, M.; SILVA, F. F. e; RESENDE, M. D. V. de; NASCIMENTO, A. C. C. A comparison of regression methods based on dimensional reduction for genomic prediction. Genetics and Molecular Research, v. 20, n. 2, p. 1-15, 2021.| Biblioteca(s): Embrapa Café. |
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| 18. | | CARVALHO, V. P.; SANT'ANNA, I. C.; NASCIMENTO, M.; NASCIMENTO, A. C. C.; CRUZ, C. D.; ARBEX, W. A.; OLIVEIRA, F. C.; SILVA, F. F. Support vector machines applied to the genetic classification problem of hybrid populations with high degrees of similarity. Genetics and Molecular Research, v. 17, n. 4, gmr18122, 2018. 10 p.| Biblioteca(s): Embrapa Gado de Leite. |
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| 19. | | VOLPATO, L.; ALVES, R. S.; TEODORO, P. E.; RESENDE, M. D. V. de; NASCIMENTO, M.; NASCIMENTO, A. C. C.; LUDKE, W. H.; SILVA, F. L. da; BORÉM, A. Multi-trait multi-environment models in the genetic selection of segregating soybean progeny. PLoS ONE, v. 14, n. 4, e0215315, Apr. 2019. 22 p.| Biblioteca(s): Embrapa Florestas. |
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| 20. | | OLIVEIRA, G. F.; NASCIMENTO, A. C. C.; NASCIMENTO, M.; SANT'ANNA, I. de C.; ROMERO, J. V.; AZEVEDO, C. F.; BHERING, L. L.; CAIXETA, E. T. Quantile regression in genomic selection for oligogenic traits in autogamous plants: a simulation study. Plos One, v. 16, n. 1, e0243666, 2021.| Biblioteca(s): Embrapa Café. |
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| Registros recuperados : 30 | |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Café. Para informações adicionais entre em contato com biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Café. |
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Data corrente: |
16/05/2022 |
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Data da última atualização: |
16/05/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
PAIXÃO, P. T. M.; NASCIMENTO, A. C. C.; NASCIMENTO, M.; AZEVEDO, C. F.; OLIVEIRA, G. F.; SILVA, F. L. da; CAIXETA, E. T. |
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Afiliação: |
PEDRO THIAGO MEDEIROS PAIXÃO, UFV; ANA CAROLINA CAMPANA NASCIMENTO, UFV; MOYSÉS NASCIMENTO, UFV; CAMILA FERREIRA AZEVEDO, UFV; GABRIELA FRANÇA OLIVEIRA, UFV; FELIPE LOPES DA SILVA, UFV; EVELINE TEIXEIRA CAIXETA MOURA, CNPCa. |
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Título: |
Factor analysis applied in genomic selection studies in the breeding of Cofea canephora. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Euphytica, v. 218, Mar. 2022. |
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DOI: |
https://doi.org/10.1007/s10681-022-02998-x |
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Idioma: |
Inglês |
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Conteúdo: |
Brazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These contribute significantly to the selection of higher genotypes, increasing the genetic gain per unit time. In this context, genomic-wide selection (GWS) is a tool that stands out, since it allows predicting the future phenotype of an individual based only on molecular information. Performing joint selection of traits is the interest of most breeding programs, and factor analysis (FA) has been used to assist in this end. The aim of this study was to evaluate the use of FA in the context of GWS, in genotypes of Coffea canephora. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the ?vigor factor? and each variable individually. However, the selection based on ?vigor factor? presented individuals with more suitable size from the phytotechnical point of view. MenosBrazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These contribute significantly to the selection of higher genotypes, increasing the genetic gain per unit time. In this context, genomic-wide selection (GWS) is a tool that stands out, since it allows predicting the future phenotype of an individual based only on molecular information. Performing joint selection of traits is the interest of most breeding programs, and factor analysis (FA) has been used to assist in this end. The aim of this study was to evaluate the use of FA in the context of GWS, in genotypes of Coffea canephora. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the ?vigor factor? and each variable individually. However, the selection based on ?vigor factor? presented individuals with more suitable s... Mostrar Tudo |
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Thesagro: |
Análise Estatística; Coffea Canephora; Ensaio Fatorial; Melhoramento Genético Vegetal; Seleção Genótipa. |
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Thesaurus NAL: |
Factor analysis; Genetic improvement; Genotype; Multivariate analysis; Plant breeding; Selection methods. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02549naa a2200337 a 4500
001 2143036
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008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1007/s10681-022-02998-x$2DOI
100 1 $aPAIXÃO, P. T. M.
245 $aFactor analysis applied in genomic selection studies in the breeding of Cofea canephora.$h[electronic resource]
260 $c2022
520 $aBrazil stands out worldwide in the production of coffee. The observed increases in its productivity and morpho agronomic traits are the results of the improvement of several methodologies applied in obtaining improved cultivars, among which the predictive methods of genetic value stand out. These contribute significantly to the selection of higher genotypes, increasing the genetic gain per unit time. In this context, genomic-wide selection (GWS) is a tool that stands out, since it allows predicting the future phenotype of an individual based only on molecular information. Performing joint selection of traits is the interest of most breeding programs, and factor analysis (FA) has been used to assist in this end. The aim of this study was to evaluate the use of FA in the context of GWS, in genotypes of Coffea canephora. It was found that FA was efficient to elucidate the relationships between the traits and generate new variables. The factors formed can assist in the selection, as in addition to allowing joint interpretations, they present good estimates of predictive capacity, heritability and accuracy. Furthermore, high agreement was observed between the individuals selected based on the factors and those selected considering the individual traits. Additionally, it was observed agreement between the top 10% individuals selected based on the ?vigor factor? and each variable individually. However, the selection based on ?vigor factor? presented individuals with more suitable size from the phytotechnical point of view.
650 $aFactor analysis
650 $aGenetic improvement
650 $aGenotype
650 $aMultivariate analysis
650 $aPlant breeding
650 $aSelection methods
650 $aAnálise Estatística
650 $aCoffea Canephora
650 $aEnsaio Fatorial
650 $aMelhoramento Genético Vegetal
650 $aSeleção Genótipa
700 1 $aNASCIMENTO, A. C. C.
700 1 $aNASCIMENTO, M.
700 1 $aAZEVEDO, C. F.
700 1 $aOLIVEIRA, G. F.
700 1 $aSILVA, F. L. da
700 1 $aCAIXETA, E. T.
773 $tEuphytica$gv. 218, Mar. 2022.
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