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Alternative count Bayesian models for genetic evaluation of litter traits in pigs

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Abstract We compared Hurdle Poisson (Hupoisson), Zero Inflated Poisson (Zipoisson), Poisson and Gaussian Bayesian mixed models for genetic evaluation of litter traits in pigs (number of piglets born alive –… Click to show full abstract

Abstract We compared Hurdle Poisson (Hupoisson), Zero Inflated Poisson (Zipoisson), Poisson and Gaussian Bayesian mixed models for genetic evaluation of litter traits in pigs (number of piglets born alive – NBA; number of piglets weaned – NW; and mortality during the suckling period – MORT). The models’ goodness-of-fit was based on Deviance Information Criteria (DIC), Model Posterior Probabilities (MPP) and Mean Square Error (MSE). The Hupoisson model provided the best fit to MORT, even showing higher heritability estimate (0.13, with credibility interval from 0.0745 to 0.2809). The Hupoisson model proposed in the present study was suitable for genetic evaluation of mortality during the suckling period, and can be indicated as a novel approach to treat count data with excess of zeros under a genetic and breeding viewpoint. The Gaussian model outperformed the other models for NBA and NW.

Keywords: models genetic; traits pigs; evaluation; evaluation litter; genetic evaluation; litter traits

Journal Title: Livestock Science
Year Published: 2019

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