Estimation of Genetic Parameters Using Linear Spline Function for Test Day Milk Yield Records in Murrah Buffaloes

Abstract

Abstract

This study estimated variance components and genetic parameters for first-lactation test-day milk yield records in Murrah buffaloes using random regression models fitted with linear B-spline functions. A total of 10,615 test day milk yield records from 965 buffaloes maintained at the National Dairy Research Institute, Karnal, were analysed. Models with 3, 4, 5, and 6 knots were evaluated under the assumption of homogeneous residual variance, and model fit was compared using the log-likelihood, Akaike information criterion, and Bayesian information criterion. The BSL6H1_F model, with six knots positioned at test days 5, 65, 125, 185, 245, and 305, provided the best fit and accounted for 96.2% of the variation in the estimated mean lactation trajectory. The highest additive genetic variance was observed at test day 65 (1.58 ± 0.33 kg²), whereas the highest permanent environmental variance occurred at test day 305 (3.36 ± 0.34 kg²). Heritability estimates ranged from 0.07 ± 0.05 at TDMY 35 to 0.38 ± 0.07 at TDMY 65 and were lower during mid-lactation. Genetic correlations between successive test-day milk yields ranged from 0.35 ± 0.24 to 0.99 ± 0.01. Genetic and permanent environmental correlations generally declined as the interval between test days increased. These findings indicate that the six-knot linear B-spline model was the best-fitting model among those evaluated for estimating genetic parameters across the first lactation.