article · animal
Raising pigs in groups introduces social interactions that affect their feeding behaviour and growth. This research evaluated how accounting for indirect genetic effects, which capture the impact of an individual pig on the performance of its group mates, influences genetic evaluations. Data was gathered from 1144 Duroc pigs during their fattening phase, measuring production traits such as growth rate and feed conversion alongside feeding behaviours like feeding frequency and visit durations. Using Bayesian methods to compare classical models with models that integrate indirect genetic effects, researchers found that indirect effects captured additional heritable variation across most traits. Furthermore, including indirect genetic effects revealed stronger correlations between feeding behaviours and production outcomes. As a result, incorporating behavioural traits alongside social genetic effects can refine the accuracy of breeding value predictions for production characteristics.
When farm animals are housed together, one animal's behaviour directly influences the well-being and growth of others. Understanding how genetics shape these social interactions enables more comprehensive evaluation tools. This insight allows breeders to select livestock based not only on individual productivity, but also on how positively animals interact with their peers, potentially improving both group efficiency and welfare.
This research provides analytical methodology for livestock breeding programmes and commercial genetic evaluation providers seeking to optimise selection in group-housed pigs. Because the findings are based on statistical modelling of a measured dataset rather than a deployable commercial tool, the work represents early-stage development requiring integration into existing commercial evaluation pipelines.
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Performance and feeding behaviour traits in growing pigs could be affected by social interaction effects when animals are raised in group. So, properly knowing the genetic correlations between direct and social interaction effects among performance and feeding behaviour traits could improve the accuracy of the genetic evaluations. Our aim was to explore the role of feeding behaviour traits (FBT) and indirect genetic effects (IGEs) in the genetic evaluations of growing pigs. Thus, genetic parameters were estimated for production traits (PT): average daily gain, average daily feed consumption, feed conversion ratio and backfat thickness; as well as for FBT: average daily feeding rate, average daily feeding frequency, average daily occupation time and average daily time between consecutive visits. Traits were recorded in 1144 Duroc pigs during the fattening period. Two bivariate models were fitted: classic animal model and an animal model fitting IGE. Estimations were done following Bayesian procedures. Heritability estimates obtained with classic animal model for all studied traits were medium-high. The additional heritable variation captured by IGE supposed that the ratios of total genetic variance to phenotypic variance (T2) were higher than the heritability estimates obtained with the classic model, except for occupation time trait, when a lower value (0.20 ± 0.19) was estimated. This is due to a high and negative correlation between IGE and direct genetic effects (DGEs) of this particular trait (-0.78 ± 0.27). Results from classic animal model do not evidence a clear role of FBT to improve the accuracy of breeding value predictions for PT; only average daily feeding rate seems to show a positive correlation (around 0.50 to 0.60) with average daily gain, average daily feed consumption and backfat thickness. However, when IGE model was fitted, the number of estimates of genetic correlations between FBT and PT showing a relevant magnitude increased, generally for the correlations between IGE of FBT and DGE of PT; or particularly for the correlations between IGE of average daily feeding frequency, and the IGE of all the PT, except average daily gain. Thus, in evaluations using the animal model with IGE fitted, the inclusion of FBT could aid the improvement of the accuracy of breeding value predictions for PT. This is a consequence of the improved genetic relationships between traits that can be fitted when considering such models.
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DOI: 10.1017/s1751731119002179
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