Abstract

The aim of the study was to obtain estimates of genetic correlations between direct and maternal calving performance of heifers and cows and beef production traits in Piemontese cattle. Beef production traits were daily gain, live fleshiness, and bone thinness measured on 1,602 young bulls tested at a central station. Live fleshiness (six traits) and bone thinness were subjectively scored by classifiers using a nine-point linear grid. Data on calving performance were calving difficulty scores (five classes from unassisted to embryotomy) routinely recorded in the farms. Calving performance of heifers and cows were considered different traits. A total of 30,763 and 80,474 calving scores in first and later parities, respectively, were used to estimate covariance components with beef traits. Data were analyzed using bivariate linear animal models, including direct genetic effects for calving performance and beef traits and maternal genetic effects only for calving performance. Due to the nature of the data structure, which involved traits measured in different environments and on different animals, covariances were estimated mostly through pedigree information. Genetic correlations of daily gain were positive with direct calving performance (0.43 in heifers and 0.50 in cows) and negative with maternal calving performance (-0.23 and -0.28 for heifers and cows, respectively). Live fleshiness traits were moderately correlated with maternal calving performance in both parities, ranging from 0.06 to 0.33. Correlations between live fleshiness traits and direct calving performance were low to moderate and positive in the first parity, but trivial in later parities. Bone thinness was negatively correlated with direct calving performance (-0.17 and -0.38 in heifers and cows, respectively), but it was positively correlated to maternal calving performance (0.31 and 0.40). Estimated residual correlations were close to zero. Results indicate that, due to the existence of antagonistic relationships between the investigated traits, specific selection strategies need to be studied.

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