Melhor predição linear não viesada (BLUP) multicaracterística na seleção recorrente de plantas anuais

• Ano de defesa: 2009
• Autor(a) principal: Sobreira, Fábio Moreira
• Orientador(a): Viana, José Marcelo Soriano
• Banca de defesa: Matta, Frederico de Pina , Miranda, Glauco Vieira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Viçosa
• Programa de Pós-Graduação: Mestrado em Genética e Melhoramento
• Departamento: Genética animal; Genética molecular e de microrganismos; Genética quantitativa; Genética vegetal; Me
• País: BR
• Palavras-chave em Português: Metodologia de modelos mistos; Acurácia; Eficiência de seleção; Seleção recorrente; Correlações
• Palavras-chave em Inglês: Mixed model methodology; Accuracy; Recurrent selection; Correlations; Selection efficiency
• Área do conhecimento CNPq: CNPQ::CIENCIAS BIOLOGICAS::GENETICA::GENETICA QUANTITATIVA
• Link de acesso: http://locus.ufv.br/handle/123456789/4696

The BLUP methodology, which is widely used in animal and forestry genetic evaluation, can also be applied to annual crop breeding. The objective of this study was to compare the accuracy and efficiency of among- and within-half-sib family selection through the use of multi-trait BLUP, single-trait BLUP and phenotypic selection. Expansion volume and yield data from two recurrent selection cycles of a popcorn population were analyzed. Progeny tests were designed as a lattice. In order to maximize accuracy of the prediction of breeding values, the BLUP analyses included phenotypic values of the two cycles. All statistical analyses were performed using the ASREML software. The multi-trait BLUP method demonstrated greater accuracy and efficiency in family selection. In the case of within-family selection, both accuracy and efficiency of multi-trait or single-trait BLUP methods were equivalent. The selection efficiency of the multi-trait BLUP was dependent on the estimated genetic parameters, particularly the difference between the genetic and environmental correlations of the traits.