|
|
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 |
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 |
URL |
Voltar
|
|
| Acesso ao texto completo restrito à biblioteca da Embrapa Territorial. Para informações adicionais entre em contato com cnpm.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Territorial. |
Data corrente: |
09/04/2008 |
Data da última atualização: |
24/08/2015 |
Tipo da produção científica: |
Resumo em Anais de Congresso |
Autoria: |
COELHO, P. H. G.; BIONDI NETO, L.; MELLO, J. C. C. B. S. DE; GOMES, E. G.; MEZA, L. A. |
Afiliação: |
PEDRO HENRIQUE GOUVÊA COELHO, UERJ; LUIZ BIONDI NETO, UERJ; JOÃO CARLOS C. B. SOARES DE MELLO, UFF; ELIANE GONCALVES GOMES, CNPM; LÍDIA ANGULO MEZA, UNIVERSIDADE VEIGA DE ALMEIDA. |
Título: |
State space representation in complex recurrent neural networks for mobile communications. |
Ano de publicação: |
2003 |
Fonte/Imprenta: |
In: REUNIÃO REGIONAL DA SOCIEDADE BRASILEIRA DE PESQUISA OPERACIONAL, 2003, Rio de Janeiro. Resumos... Niterói, RJ: UFF, 2003. |
Páginas: |
p. 11. |
Idioma: |
Português |
Palavras-Chave: |
Channel equalization for mobile systems; State space. |
Thesaurus NAL: |
Neural networks. |
Categoria do assunto: |
-- |
Marc: |
LEADER 00675nam a2200193 a 4500 001 1017669 005 2015-08-24 008 2003 bl uuuu u01u1 u #d 100 1 $aCOELHO, P. H. G. 245 $aState space representation in complex recurrent neural networks for mobile communications. 260 $aIn: REUNIÃO REGIONAL DA SOCIEDADE BRASILEIRA DE PESQUISA OPERACIONAL, 2003, Rio de Janeiro. Resumos... Niterói, RJ: UFF$c2003 300 $ap. 11. 650 $aNeural networks 653 $aChannel equalization for mobile systems 653 $aState space 700 1 $aBIONDI NETO, L. 700 1 $aMELLO, J. C. C. B. S. DE 700 1 $aGOMES, E. G. 700 1 $aMEZA, L. A.
Download
Esconder MarcMostrar Marc Completo |
Registro original: |
Embrapa Territorial (CNPM) |
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
Expressão de busca inválida. Verifique!!! |
|
|