Analyses were carried out for the estimation of (co)variance components and genetic parameters for birth weight (BWT), 6-month weight (6WT), 12-month weight (12WT), 18-month weight (18WT), 24-month weight (24WT), 30-month weight (30WT), 36-month weight (36WT), weight at first service (WFS), and weight at first calving(WFC) in Sahiwal cattle. Data for 802 lifetime records (raw data) were collected over a period of 30 years (1990-2019) for various growth traits in the herd for Sahiwal cows maintained at the livestock farm unit of ICAR-NDRI Karnal, Haryana, India. Bayesian estimates using the multi-trait Gibbs sampling animal model approach were calculated in the present study. Total heritability for BWT, 6WT, 12WT, 18WT, 24WT, 30WT, 36WT, WFS, and WFC by Bayesian modeling was estimated as 0.22 ± 0.0052, 0.47 ± 0.0037, 0.30 ± 0.0025, 0.65 ± 0.0021, 0.32 ± 0.0039, 0.33 ± 0.0027, 0.39 ± 0.0031, 0.49 ± 0.0020, and 0.57 ± 0.0023, respectively, along with its Monte Carlo error in Sahiwal cattle. Direct genetic covariances between body weight traits were ranging from - 2762.5 for 18WT and WFC to 4739.6 between WFS and WFC. Environmental covariances were ranging from - 169.98 for 30WT and 36WT to 4539.4 between WFS and WFC. Family relationships as well as the existing interaction effects between two or more traits in opposite direction effect lead to negative estimates for genetic covariances between some of the combinations with various growth traits. Although most of the estimates for posteriori were somewhat skewed, the marginalization effect enabled them to fit into the Gaussian distribution, by comparing the mean, mode, and median with each other. Results suggest that genetic progress through growth traits can be achieved if the selection is carried out for highly heritable 18-month weight as well as for the selection of pubertal and fertility traits, viz., 24WT, 30WT, 36WT, WFS, and WFC with a balanced feeding and optimum management.
Keywords: Bayesian estimates; Genetic and phenotypic parameters; Growth traits; Sahiwal cattle.
© 2022. The Author(s), under exclusive licence to Springer Nature B.V.