| |
|
|
|
Registro Completo |
|
Biblioteca(s): |
Embrapa Agroenergia; Embrapa Café. |
|
Data corrente: |
24/06/2021 |
|
Data da última atualização: |
24/06/2021 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Autoria: |
PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; COELHO, I. F; ALVES, R. A.; LAVIOLA, B. G.; SILVA, F. F. e; RESENDE, M. D. V. de; BHERING, L. L. |
|
Afiliação: |
MARCO ANTÔNIO PEIXOTO, Universidade Federal de Viçosa; JENIFFER SANTANA PINTO COELHO EVANGELISTA, Universidade Federal de Viçosa; IGOR FERREIRA COELHO, Universidade Federal de Viçosa; RODRIGO SILVA ALVES, Universidade Federal de Viçosa; BRUNO GALVEAS LAVIOLA, CNPAE; FABYANO FONSECA E SILVA, Universidade Federal de Viçosa; MARCOS DEON VILELA DE RESENDE, CNPCa; LEONARDO LOPES BHERING, Universidade Federal de Viçosa. |
|
Título: |
Multiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy. |
|
Ano de publicação: |
2021 |
|
Fonte/Imprenta: |
PLOS ONE , v. 16, n. 3, e0247775, Mar. 2021. |
|
Volume: |
16 |
|
ISSN: |
1932-6203 |
|
DOI: |
https://doi.org/10.1371/journal.pone.0247775 |
|
Idioma: |
Inglês |
|
Conteúdo: |
Multiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low, moderate, and high magnitude were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials. |
|
Thesagro: |
Bioenergia. |
|
Thesaurus Nal: |
Bioenergy; Biofuels; Genetic polymorphism; Petroleum; Vegetable oil. |
|
Categoria do assunto: |
-- |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/224043/1/Multiple-trait-model-2021.pdf
|
|
Marc: |
LEADER 02186naa a2200325 a 4500
001 2132550
005 2021-06-24
008 2021 bl uuuu u00u1 u #d
022 $a1932-6203
024 7 $ahttps://doi.org/10.1371/journal.pone.0247775$2DOI
100 1 $aPEIXOTO, M. A.
245 $aMultiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy.$h[electronic resource]
260 $c2021
300 $a16
490 $v16
520 $aMultiple-trait model tends to be the best alternative for the analysis of repeated measures, since they consider the genetic and residual correlations between measures and improve the selective accuracy. Thus, the objective of this study was to propose a multiple-trait Bayesian model for repeated measures analysis in Jatropha curcas breeding for bioenergy. To this end, the grain yield trait of 730 individuals of 73 half-sib families was evaluated over six harvests. The Markov Chain Monte Carlo algorithm was used to estimate genetic parameters and genetic values. Genetic correlation between pairs of measures were estimated and four selective intensities (27.4%, 20.5%, 13.7%, and 6.9%) were used to compute the selection gains. The full model was selected based on deviance information criterion. Genetic correlations of low, moderate, and high magnitude were observed between pairs of harvests. Bayesian analyses provide robust inference of genetic parameters and genetic values, with high selective accuracies. In summary, the multiple-trait Bayesian model allowed the reliable selection of superior Jatropha curcas progenies. Therefore, we recommend this model to genetic evaluation of Jatropha curcas genotypes, and its generalization, in other perennials.
650 $aBioenergy
650 $aBiofuels
650 $aGenetic polymorphism
650 $aPetroleum
650 $aVegetable oil
650 $aBioenergia
700 1 $aEVANGELISTA, J. S. P. C.
700 1 $aCOELHO, I. F
700 1 $aALVES, R. A.
700 1 $aLAVIOLA, B. G.
700 1 $aSILVA, F. F. e
700 1 $aRESENDE, M. D. V. de
700 1 $aBHERING, L. L.
773 $tPLOS ONE$gv. 16, n. 3, e0247775, Mar. 2021.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Agroenergia (CNPAE) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
URL |
Voltar
|
|
|
| Registros recuperados : 1 | |
| 1. |  | PEIXOTO, M. A.; EVANGELISTA, J. S. P. C.; COELHO, I. F; ALVES, R. A.; LAVIOLA, B. G.; SILVA, F. F. e; RESENDE, M. D. V. de; BHERING, L. L. Multiple-trait model through Bayesian inference applied to Jatropha curcas breeding for bioenergy. PLOS ONE , v. 16, n. 3, e0247775, Mar. 2021. 16| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Agroenergia; Embrapa Café. |
|    |
| Registros recuperados : 1 | |
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
