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Registro Completo |
Biblioteca(s): |
Embrapa Café. |
Data corrente: |
16/05/2022 |
Data da última atualização: |
16/05/2022 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
PAIXÃO, P. T. M.; NASCIMENTO, A. C. C.; NASCIMENTO, M.; AZEVEDO, C. F.; OLIVEIRA, G. F.; SILVA, F. L. da; CAIXETA, E. T. |
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. |
Título: |
Factor analysis applied in genomic selection studies in the breeding of Cofea canephora. |
Ano de publicação: |
2022 |
Fonte/Imprenta: |
Euphytica, v. 218, Mar. 2022. |
DOI: |
https://doi.org/10.1007/s10681-022-02998-x |
Idioma: |
Inglês |
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 |
Thesagro: |
Análise Estatística; Coffea Canephora; Ensaio Fatorial; Melhoramento Genético Vegetal; Seleção Genótipa. |
Thesaurus Nal: |
Factor analysis; Genetic improvement; Genotype; Multivariate analysis; Plant breeding; Selection methods. |
Categoria do assunto: |
-- |
Marc: |
LEADER 02549naa a2200337 a 4500 001 2143036 005 2022-05-16 008 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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Embrapa Café (CNPCa) |
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Biblioteca(s): |
Embrapa Soja. |
Data corrente: |
10/09/2018 |
Data da última atualização: |
04/07/2019 |
Tipo da produção científica: |
Documentos |
Autoria: |
CONTE, O.; OLIVEIRA, F. T. de; HARGER, N.; CORREA-FERREIRA, B. S.; ROGGIA, S.; PRANDO, A. M.; SERATTO, C. D. |
Afiliação: |
OSMAR CONTE, CNPSO; ENGENHEIRO AGRÔNOMO, M.SC., EXTENSIONISTA VOLUNTÁRIO, ANDIRÁ, PR; ENGENHEIRO AGRÔNOMO, DR., EXTENSIONISTA DA EMATER, APUCARANA, PR; BIÓLOGA, DRA., PESQUISADORA APOSENTADA DA EMBRAPA SOJA, LONDRINA, PR; SAMUEL ROGGIA, CNPSO; ANDRE MATEUS PRANDO, CNPSO; ENGENHEIRO AGRÔNOMO, MSC., EXTENSIONISTA DA EMATER, MARINGÁ, PR. |
Título: |
Resultados do manejo integrado de pragas da soja na safra 2017/18 no Paraná. |
Ano de publicação: |
2018 |
Fonte/Imprenta: |
Londrina: Embrapa Soja, 2018. |
Páginas: |
66 p. |
Série: |
(Embrapa Soja. Documentos, 402). |
Idioma: |
Português |
Thesagro: |
Controle Integrado; Praga de Planta; Soja. |
Thesaurus NAL: |
Integrated agricultural systems; Pest control programs; Soybeans. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/182653/1/Doc-402-OL.pdf
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Marc: |
LEADER 00746nam a2200265 a 4500 001 2095318 005 2019-07-04 008 2018 bl uuuu 00u1 u #d 100 1 $aCONTE, O. 245 $aResultados do manejo integrado de pragas da soja na safra 2017/18 no Paraná. 260 $aLondrina: Embrapa Soja$c2018 300 $a66 p. 490 $a(Embrapa Soja. Documentos, 402). 650 $aIntegrated agricultural systems 650 $aPest control programs 650 $aSoybeans 650 $aControle Integrado 650 $aPraga de Planta 650 $aSoja 700 1 $aOLIVEIRA, F. T. de 700 1 $aHARGER, N. 700 1 $aCORREA-FERREIRA, B. S. 700 1 $aROGGIA, S. 700 1 $aPRANDO, A. M. 700 1 $aSERATTO, C. D.
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