Genetic and Environmental Factors Influencing Lactation Traits in Jersey x Sahiwal Crossbred Cattle: Variance Component Estimation

Crossbreeding programs enhance dairy productivity by combining desirable traits from different breeds. Accurate genetic evaluation is essential for improving economically important lactation traits in crossbred cattle. This study aimed to estimate genetic parameters and variance components for 305-day milk yield (305-DMY), total milk yield (TMY), lactation length (LL) and peak yield (PY) using Derivative-Free Restricted Maximum Likelihood (DFREML) method (Meyer, 1998). A total of 4,877 first lactation performance records of Jersey x Sahiwal crossbred cattle, maintained under the progeny testing program in Chittoor district of Andhra Pradesh, India were utilized for this study. Six univariate animal models were fitted for each trait by including or excluding maternal additive genetic (m2) and permanent environmental (c2) effects. Selection of the best-fitted model for each trait was based on AIC, BIC and log-likelihood values. The overall least-square means for 305-DMY, TMY, LL and PY were 2276.46±8.57 kg, 2300.23±9.20 kg, 283.93±0.49 days and 10.23±0.03 kg, respectively. The effect of sire, period and season of calving were highly significant (P<0.01) for all traits, indicating the influence of environmental factors on milk production. Direct heritability estimates were moderate to high, with values of 0.50 for 305-DMY, 0.53 for TMY, 0.42 for LL and 0.15 for PY, suggesting substantial genetic variability for selection. Maternal genetic (m2) and permanent environmental (c²) effects had minimal influence on 305-DMY, TMY and LL, whereas individual permanent environmental effects (c2) accounted for 39% of the total phenotypic variance in PY, emphasizing the critical role of environmental management in improving peak yield. These findings emphasize the necessity of selecting appropriate models for accurate genetic evaluations and advocate for an integrated approach that combines genetic selection with strategic environmental management. By optimizing both genetic potential and environmental conditions, this approach ensures balanced and sustainable improvements in dairy productivity, contributing to the long-term success of crossbreeding programs.