Reduced-rank estimation of genetic parameters for egg production traits and cluster analyses with predicted breeding values

• Autor(a) principal: Freitas, Luara Afonso de [UNESP]
• Data de Publicação: 2018
• Outros Autores: Savegnago, Rodrigo Pelicioni [UNESP], Grupioni, Natalia Vinhal [UNESP], Ramos, Salvador Boccaletti, Stafuzza, Nedenia Bonvino [UNESP], Pereira de Figueiredo, Elsio Antonio, Schmidt, Gilberto Silber, Ledur, Monica Correa, Munari, Danisio Prado [UNESP]
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UNESP
• Texto Completo: http://dx.doi.org/10.1080/09064702.2019.1580308; http://hdl.handle.net/11449/185827
• topic: Genetic correlation; heritability; k-means; laying hens; Ward clustering

The aims of this study were to compare the suitability of the multi-trait (MUT) model to estimate genetic parameters with that of 13 reduced-rank principal component models (PC1 to PC13), and then to explore the additive genetic patterns of the breeding values obtained from these using clustering analyses of egg production traits. A total of 1,212 records were used to estimate genetic parameters using the MUT and PC models. The PC4 model was the best representation of the data since it had a lower AIC value and was more parsimonious than the MUT model. The estimated heritability of the age at the first egg (AFE) trait from this model was 0.28 +/- 0.06, and the estimated genetic correlation between AFE and total egg production (TP) was -0.52 +/- 0.23. Potentially animals from cluster 2 are more likely to be in the selected group to help improve the egg production.