Estimates of genetic and crossbreeding parameters for reproductive traits of Fogera and its Holstein-Friesian Crosses

This study was initiated with the objectives of estimating genetic and crossbreeding parameters for reproductive traits using data from 624 Fogera and its crossbred cows collected between 1992 and 2014 at Andassa Livestock Research Center. The study focused on pure Fogera and its F 1 crosses with Holstein Friesian genotypes. Variance components, heritability, and repeatability estimates were analysed using AI-REML in WOMBAT, while least squares means for the genetic groups were calculated using the General Linear Model procedure of SAS software. Additive genetic, heterosis, and recombination effects, as crossbreeding parameters, were estimated using a sire model. The study found significant effects ( P < 0.001) of genotype and parity on calving interval, while year had a significant effect ( P < 0.01) on age at first calving and calving interval. The heritability and repeatability estimates for calving interval, days open, age at first calving, and gestation length were 0.47, 0.02, 0.48, and 0.04, and 0.47, 0.02, 0.53, and 0.36, respectively. The estimates of additive genetic effects for the evaluated traits were 0.41, 0.07, 0.43, and 0.31, respectively. The heterosis effects were significant ( P < 0.001), resulting in an increase of 40, 31.5, and 20 days for age at first calving, calving interval, and days open, respectively, as a result of crossbreeding. Recombination losses, however, were not statistically significant. The moderate heritability and repeatability estimates for calving interval and age at first calving suggested that selective breeding could have moderately improved these reproductive traits. Nonetheless, the positive heterosis values indicated that crossbreeding under the existing management conditions did not have reproductive advantages. These findings implied that strategic crossbreeding alone might not have substantially enhanced the reproductive efficiency of indigenous Fogera cattle. Further research using larger and more balanced datasets is recommended to validate these results and to refine breeding strategies for sustainable genetic improvement.