Comparative analysis of methods for assessing the breeding value of stud bulls
Abstract
In the context of restructuring the dairy cattle breed composition in the Russian Federation and the ongoing Holsteinization of populations, an accurate assessment of the breeding value of stud bulls is a crucial task for effective selection. The BLUP (Best Linear Unbiased Prediction) method, while being the international standard, requires adaptation and comparative assessment with traditional methods in domestic practice. The aim of this study is to conduct a comparative assessment of Holstein bulls used in the Vologda Region population based on offspring quality, using the BLUP method and the traditional “daughter-peer” method. The study was carried out on data from 6,760 first-calf heifers sired by 283 bulls from 25 breeding farms in the Vologda Region. A mixed-type biometric model was used to predict breeding value (EBV) and calculate its reliability (R²). A comparative analysis of the methods was performed using correlation (r) and Spearman rank correlation analysis (ρ). The BLUP method assessed all 283 bulls, of which 115 were identified as improvers for milk yield, 60 as neutral, and 108 as deteriorators. Reliability of the estimate (R² ≥ 0.5) was obtained for 125 animals (44.2%). Only a few bulls simultaneously improved two traits, and none improved all three. The “daughter-peer” method allowed for the assessment of only 88 bulls (31.1%). A moderate positive correlation was found between the results of the two methods (r = 0.33–0.43; p < 0.001). The BLUP method demonstrates an advantage in terms of assessment coverage and provides a more accurate accounting of genetic and paratypic factors. However, for practical breeding, it is necessary to establish clear threshold values for assessment reliability (R²). The correlation identified between the methods confirms the overall consistency of the results, indicating the potential for implementing BLUP in the breeding system, provided that the criteria for bull selection based on prediction reliability are standardized.