Increasing litter sizes require cross-fostering to regulate litter size, but also to homogenize the weight of piglets growing up together. This practice increases labour costs and poses immunity concerns, but increases preweaning survival and thus farm productivity. Therefore, identifying factors resulting in birth weight (BW) variability is a priority. We estimated the genetic component of residual variance for BW using a data set with 23,313 BW records from 1,748 litters of 813 sows and 26,107 individuals in the pedigree. The heteroscedastic model included the sex (2 levels), farm-month-year (75 levels), litter size (21 levels), breed (4 levels), and age of the sow (300 to 1,956 days) as fixed effects. The litter effect (nested to the sow) was included as random effect in addition to the genetic effect. The data was assigned to the mother, and the same effects were fitted for mean BW and its variability. The model was fitted using a Markov chain Monte Carlo software (GSEVM). The genetic coefficient of variation was 0.189, and the genetic correlation between the mean BW and its variability was 0.398 (SE=0.116). Regarding fixed effects, female piglets were more consistent regarding BW variability despite having lower weight, and litters with more than 9 piglets were less variable than smaller ones. The age of the sow affected mean BW positively, and reduced BW variation. The results are in line with previous genetic parameters estimated for BW uniformity in pigs. Even though the mean birth weight might decrease, selection for uniformity is expected to be beneficial since selection for uniformity has been shown to increase the robustness of the animal. Finally, homogenizing BW might reduce the occurrence of intrauterine growth retardation, thereby improving piglet health and carcass value.
Kasper-Völkl C., Lepori A., Gutiérrez J. P., Formoso-Rafferty N., Sell-Kubiak E., Cervantes I.
Genetic parameters for genetic variance uniformity in Swiss pigs’ birth weight.
In: Book of Abstracts of the 74th Annual Meeting of the European Federation of Animal Science. Ed. EAAP European Federation of Animal Science. 2023, 204.
ISBN: 978-90-8686-384-6
ID pubblicazione (Codice web): 54968
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