Use este identificador para citar ou linkar para este item: http://repositorio.ufla.br/jspui/handle/1/58780
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dc.creatorEvangelista, Jeniffer Santana Pinto Coelho-
dc.creatorPeixoto, Marco Antônio-
dc.creatorCoelho, Igor Ferreira-
dc.creatorFerreira, Filipe Manoel-
dc.creatorMarçal, Tiago de Souza-
dc.creatorAlves, Rodrigo Silva-
dc.creatorChaves, Saulo Fabricio da Silva-
dc.creatorRodrigues, Erina Vitório-
dc.creatorLaviola, Bruno Gálveas-
dc.creatorResende, Marcos Deon Vilela de-
dc.creatorDias, Kaio Olimpio das Graças-
dc.creatorBhering, Leonardo Lopes-
dc.date.accessioned2024-01-16T16:02:12Z-
dc.date.available2024-01-16T16:02:12Z-
dc.date.issued2023-
dc.identifier.citationEVANGELISTA, J. S. P. C. et al. Modeling covariance structures and optimizing Jatropha curcas breeding. Tree Genetics & Genomes, [S.l.], v. 19, 2023.pt_BR
dc.identifier.urihttps://link.springer.com/article/10.1007/s11295-023-01596-9pt_BR
dc.identifier.urihttp://repositorio.ufla.br/jspui/handle/1/58780-
dc.description.abstractJatropha curcas has become a prominent source of biofuel, especially because of the high oil content in its fruit. The aim of this study was to test different statistic models and compare the best-fitted model with the compound symmetry model and study the grain yield persistence of J. curcas progenies. A total of 730 individuals from 73 half-sib families were evaluated for the fruit yield trait over six crop years. Repeated measures models with different covariance structures for the genetic and non-genetic effects were tested. Results show an increase up to in accuracy upon modeling the genetic and non-genetic effects when compared to the compound symmetry model. The selection gain obtained via the best-fit model for 10, 15, 20, and 25 selected best progenies was around 3 to 2% higher than gain obtained via the standard statistical model used by breeders (compound symmetry model). The harvests evaluated exhibited accuracies of high magnitude. The ten progenies that stood out with the best genetic performance are also those with the greatest persistence and greatest accumulated yield. Combining modeling of covariance structures for grain yield and selecting for persistence of production can sustain a successful long-term J. curcas breeding program.pt_BR
dc.languageen_USpt_BR
dc.publisherSpringerpt_BR
dc.rightsrestrictAccesspt_BR
dc.sourceTree Genetics & Genomespt_BR
dc.subjectBest linear unbiased predictionpt_BR
dc.subjectGenetic selectionpt_BR
dc.subjectRenewable energypt_BR
dc.subjectRepeated measurementspt_BR
dc.subjectResidual maximum likelihoodpt_BR
dc.titleModeling covariance structures and optimizing Jatropha curcas breedingpt_BR
dc.typeArtigopt_BR
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