Optimizing the genetic evaluation criteria for the small herd of Saanen x Beetal crossbred dairy goats of Indian sub-tropic

This study focused on the accurate genetic evaluation of a small dairy flock of crossbred dairy goats, specifically developed for high milk production in the Indian sub-tropical climate. The study was conducted on Saanen x Beetal (SxB) crossbred goats, which utilized 12,660 test day records for first parity. Additionally, complete lactation records (N=1283) across multiple parities and for the first parity (N=659) were analyzed separately for genetic evaluation. The main traits examined were 150-day milk yield (150DMY), days in milk (DIM), peak yield (PY), and total milk yield (TMY), with averages of 198.80±2.83 kg, 227.90±4.18 days, 1.17±0.02 kg, and 262.40±6.12 kg, respectively, highlighting the genetic superiority of SB goats over native Indian goats. Across parities, the estimates for 150DMY, DIM, and TMY were 230±6.16 kg, 210±7.0 days, and 277±11.82 kg, respectively. Given the moderate heritability (0.24±0.08) and repeatability (0.29±0.04) estimates of 150DMY, the study recommends using 150DMY as the primary selection criterion for genetic improvement in SxB goats. The single-trait random regression model (RRM) utilizing various orders of orthogonal Legendre polynomials (LEG) and B-spline (BS) functions with heterogeneous residual variances was also employed. The test day milk yield (TDMY) showed a least squares mean of 1.30±0.01 kg, with moderate heritability estimates across test days (0.26±0.08). The optimal model was identified as a quadratic B-spline function with six knots (BS6Q). Positive genetic correlations were observed between consecutive test-day milk yield values, while correlations decreased for more distant test days. The study demonstrated the superiority of the B-spline model in genetically assessing Saanen x Beetal dairy goats, highlighting its benefits in curve fitting, genetic parameter estimation, and higher breeding value prediction accuracy. Looking into the moderate heritability and desirable genetic correlation of 150 DMY with other lactation traits, we recommend using 150 DMY for further selection programs. As the concordance of ranking between different approaches for breeding value prediction was high, we recommend using the random regression test day model (RR-TDM) when data recording across lactation is costly.