Pregnancy scanning can be used as a source of data for genetic evaluation of reproductive traits of ewes

Abstract

Reproductive traits generated from mothering up lambs to ewes (n = 59 603 records) were compared with data resulting from pregnancy scanning (n = 46 663 records), to examine the consistency between the two data sources for deriving specific reproductive traits and to estimate genetic parameters. The reproductive traits considered were fertility (FERT: 0/1) of ewes joined, total litter size (LSIZE: lambs born), the number of lambs surviving at weaning (LSIZEW: lambs weaned) and the percentage of lambs surviving (LSURV = LSIZEW/LSIZE) for ewes that lambed, along with the composite traits number of lambs born (NLB) and number weaned (NLW) for ewes joined. Corresponding trait values were derived from pregnancy scan data (FERT_S, LSIZE_S and NLB_S) for comparison, and were classified as inconsistent if the trait values did not match from scanning and lambing records. Data were obtained from four flocks, representing different time frames, locations, management and breeds or bloodlines. Each flock recorded scan data separately from lambing outcomes. Genetic parameters were estimated separately within each flock. Average levels of inconsistency between scan- and lambing-data values varied between 4.6% and 14.8% across flocks, tending to be highest (9.1–18.5%) for litter size of ewes scanned with multiple fetuses, and lowest (0.29–7.3%) for assignment of fertility. Inconsistencies did not have a significant impact on estimates of trait heritabilities, suggesting recording errors were independent of genetic merit. In three flocks, the genetic correlations (ra) between comparable traits derived from the different data sources were not different from unity (ra ≥ 0.99) even when phenotypic correlations (rp) were lower (rp ≥ 0.84). In the flock with the highest inconsistency rate between data sources, the range in ra varied between 0.60 (fertility) and 1.0 (litter size). Therefore, pregnancy scan data can be directly substituted for reproductive traits traditionally based on lambing data, but attention should be paid to ensuring accuracy of the data sources used. Scan data also provide no information on lamb-survival outcomes after birth, so does not constitute complete data on reproductive outcomes. Genetic evaluation systems might also benefit from fine tuning for scale-induced effects (due to litter size) on parameters to improve the accuracy of across flock prediction of breeding values for reproductive traits.