| |
|
|
| Registros recuperados : 1 | |
| 1. |  | BARILI, L. D.; VALE, N. M. do; SILVA, F. R. e; CARNEIRO, J. E. de S.; OLIVEIRA, H. R. de; VIANELLO, R. P.; VALDISSER, P. A. M. R.; NASCIMENTO, M. Genome prediction accuracy of common bean via Bayesian models. Ciência Rural, v. 48, n. 8, e20170497, 2018.| Biblioteca(s): Embrapa Arroz e Feijão. |
|    |
| Registros recuperados : 1 | |
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Arroz e Feijão. |
|
Data corrente: |
17/09/2018 |
|
Data da última atualização: |
17/09/2018 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
A - 2 |
|
Autoria: |
BARILI, L. D.; VALE, N. M. do; SILVA, F. R. e; CARNEIRO, J. E. de S.; OLIVEIRA, H. R. de; VIANELLO, R. P.; VALDISSER, P. A. M. R.; NASCIMENTO, M. |
|
Afiliação: |
LEIRI DAIANE BARILI, UFV; NAINE MARTINS DO VALE, COODETEC; FABYANO FONSECA E SILVA, UFV; JOSÉ EUSTAQUIO DE SOUZA CARNEIRO, UFV; HINAYAH ROJAS DE OLIVEIRA, UFV; ROSANA PEREIRA VIANELLO, CNPAF; PAULA ARIELLE M RIBEIRO VALDISSER, CNPAF; MOYSES NASCIMENTO, UFV. |
|
Título: |
Genome prediction accuracy of common bean via Bayesian models. |
|
Ano de publicação: |
2018 |
|
Fonte/Imprenta: |
Ciência Rural, v. 48, n. 8, e20170497, 2018. |
|
ISSN: |
1678-4596 |
|
DOI: |
10.1590/0103-8478cr20170497 |
|
Idioma: |
Inglês |
|
Conteúdo: |
We aimed to apply genomic information based on SNP (single nucleotide polymorphism) markers for the genetic evaluation of the traits ?stay-green? (SG), plant architecture (PA), grain aspect (GA) and grain yield (GY) in common bean through Bayesian models. These models were compared in terms of prediction accuracy and ability for heritability estimation for each one of the mentioned traits. A total of 80 cultivars were genotyped for 377 SNP markers, whose effects were estimated by five different Bayesian models: Bayes A (BA), B (BB), C (BC), LASSO (BL) e Ridge regression (BRR). Although, prediction accuracies calculated by means of cross-validation have been similar within each trait, the BB model stood out for the trait SG, whereas the BRR was indicated for the remaining traits. The heritability estimates for the traits SG, PA, GA and GY were 0.61, 0.28, 0.32 and 0.29, respectively. In summary, the Bayesian methods applied here were effective and ease to be implemented. The used SNP markers can help in the early selection of promising genotypes, since incorporating genomic information increase the prediction accuracy of the estimated genetic merit. |
|
Palavras-Chave: |
Cross-validation; Validação cruzada. |
|
Thesagro: |
Feijão; Marcador Molecular; Phaseolus Vulgaris. |
|
Thesaurus NAL: |
Beans; Genetic markers; Marker-assisted selection. |
|
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/183081/1/CNPAF-2018-CienRural.pdf
|
|
Marc: |
LEADER 02091naa a2200325 a 4500
001 2095835
005 2018-09-17
008 2018 bl uuuu u00u1 u #d
022 $a1678-4596
024 7 $a10.1590/0103-8478cr20170497$2DOI
100 1 $aBARILI, L. D.
245 $aGenome prediction accuracy of common bean via Bayesian models.$h[electronic resource]
260 $c2018
520 $aWe aimed to apply genomic information based on SNP (single nucleotide polymorphism) markers for the genetic evaluation of the traits ?stay-green? (SG), plant architecture (PA), grain aspect (GA) and grain yield (GY) in common bean through Bayesian models. These models were compared in terms of prediction accuracy and ability for heritability estimation for each one of the mentioned traits. A total of 80 cultivars were genotyped for 377 SNP markers, whose effects were estimated by five different Bayesian models: Bayes A (BA), B (BB), C (BC), LASSO (BL) e Ridge regression (BRR). Although, prediction accuracies calculated by means of cross-validation have been similar within each trait, the BB model stood out for the trait SG, whereas the BRR was indicated for the remaining traits. The heritability estimates for the traits SG, PA, GA and GY were 0.61, 0.28, 0.32 and 0.29, respectively. In summary, the Bayesian methods applied here were effective and ease to be implemented. The used SNP markers can help in the early selection of promising genotypes, since incorporating genomic information increase the prediction accuracy of the estimated genetic merit.
650 $aBeans
650 $aGenetic markers
650 $aMarker-assisted selection
650 $aFeijão
650 $aMarcador Molecular
650 $aPhaseolus Vulgaris
653 $aCross-validation
653 $aValidação cruzada
700 1 $aVALE, N. M. do
700 1 $aSILVA, F. R. e
700 1 $aCARNEIRO, J. E. de S.
700 1 $aOLIVEIRA, H. R. de
700 1 $aVIANELLO, R. P.
700 1 $aVALDISSER, P. A. M. R.
700 1 $aNASCIMENTO, M.
773 $tCiência Rural$gv. 48, n. 8, e20170497, 2018.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Arroz e Feijão (CNPAF) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
