Genetic principal components for reproductive and productive traits in dual-purpose buffaloes in Colombia

A multitrait model (MC) and 5 reduced-rank models with principal component structure (components PC, PC, PC, PC, and PC) were compared. The objectives were to determine the most appropriate model for estimating genetic parameters and to evaluate the genetic progress of dual-purpose buffaloes in Colo...

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Veröffentlicht in:Journal of animal science 2015-08, Vol.93 (8), p.3801-3809
Hauptverfasser: Agudelo-Gómez, D A, Pelicioni Savegnago, R, Buzanskas, M E, Ferraudo, A S, Prado Munari, D, Cerón-Muñoz, M F
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Sprache:eng
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Zusammenfassung:A multitrait model (MC) and 5 reduced-rank models with principal component structure (components PC, PC, PC, PC, and PC) were compared. The objectives were to determine the most appropriate model for estimating genetic parameters and to evaluate the genetic progress of dual-purpose buffaloes in Colombia using that model. The traits evaluated were weaning weight (WW), yearling weight (W12), weight at 18 mo of age (W18), weight at 2 yr of age (W24), age at first calving (AFC), and milk yield at 270 d of first lactation (MY270). Genealogy and productive information from 34,326 buffaloes born in Colombia between 1997 and 2014 were used. Colombian Association of Buffalo Breeders (ACB) provided the data. Direct additive genetic and residual random effects were included for all the traits. In addition, the maternal additive genetic effect and permanent environmental random effect were included for WW, while a maternal additive genetic effect was included for W12. The fixed effects were contemporary group (farm, year, and calving season: January to April, May to August, or September to December; for all traits) and sex (for WW, W12, W18, and W24). Additionally, parity was included as a fixed effect for WW and W12. Age at weighing was used as a covariate for WW, W12, W18, and W24. Genetic progress of all traits was analyzed using a generalized smooth model (GAM). According to the Akaike information criteria (AIC), the best model was the one with reduced rank and first 3 principal components (PC). This model maintained 100% of the original variance. Genetic parameters estimated with this model were similar to those estimated by MC, but with smaller standard errors. Heritability for weight-related traits ranged between 0.23 and 0.44. Heritabilities for AFC and MY270 were 0.14 and 0.24, respectively. The genetic correlations obtained between all weights (WW, W12, W18, and W24) were positive and high. Correlations between all weights with AFC were negative and moderate. Correlations between all weights with MY270 were positive and moderate, and between MY270 with AFC were negative and low.
ISSN:1525-3163
DOI:10.2527/jas.2015-8940