Selection for litter size and litter birthweight in Large White pigs: Maximum, mean and variability of reproduction traits

Gradually increasing trend of litter size poses a challenge to pig farmers in terms of managing larger litters. Therefore, it seems that a balanced approach that optimises litter size, litter birthweight, and uniformity of those traits is needed in order to address animal welfare and farm management concerns. This study aimed to investigate this issue by defining several traits for total number born (TNB), number born alive (NBA) and litter birthweight (LW). First, the highest value from at least five records per sow was selected as maximum (max) value for each reproduction trait. Second, a mean (mean) for each reproduction trait was calculated per sow. Last, the variability of reproduction traits between parities of the sow was calculated as log-transformed variance of residuals of all observations per sow for each reproduction trait (LnVar). In total, 23 193 Large White sows from Topigs Norsvin with 152 282 litter records were used for analysis in ASReml 4.1. Also, a simulation of breeding schemes was performed with the use of SelAction 2.1 and estimates from genetic analysis. Maximum value of reproductive traits had a much higher heritability than repeated observations or mean of reproduction traits, e.g., 0.31 for maxTNB vs. 0.12 for TNB and 0.07 for meanTNB, which allows for a faster response under selection. The maximum value traits, however, were found to carry more risks, i.e. higher ratio of stillborn (not for maxNBA) and increased variability of traits. Thus, using them in breeding programme should be carefully considered. The genetic coefficient of variation on SD level estimated to indicate the genetic magnitude for variability phenotypes indicated a maximum change of 6–9% in genetic SD of TNB, NBA and LW. The genetic correlations between mean and corresponding variability traits varied from 0.66 to 0.74, whereas the correlation between other mean and variability traits ranged from 0.33 to 0.99. The simulation indicated that even with selection targeted against the variability of reproduction traits, a very limited change should be expected due to a complex genetic and phenotypic relationship between the traits. In the scenarios with selection against LnVarTNB and LnVarLW, this was a decrease of 0.1–0.6% per year, whereas in scenario with selection against LnVarNBA, the range was 0.6–1.1% per year. It is still possible to increase litter size and birthweight further, however, a balance between mean and variability of reproduction traits is required, which can be obtained only by a very well designed breeding programme.