Genetic analysis of milk and milk composition traits in Murrah buffaloes using Bayesian inference.

Accurate and unbiased assessment of genetic parameters of milk and milk composition traits play an important role in formulating breeding program for genetic improvement of Murrah buffaloes. In this study, data spread over 28 years were utilized to estimate genetic parameters of traits viz., 305 d milk yield (305MY), 305 d fat yield (305FY), 305 d solid not fat yield (305SNFY), milk fat percentage (fat%) and solid not fat percentage (SNF) percentage (SNF%) in Murrah buffaloes kept at ICAR-National Dairy Research Institute, Karnal. Bayesian multiple-trait analysis was done using animal model and Gibbs sampling to estimate (co)variance components. Posterior means of heritability and posterior standard deviation for 305MY, 305FY, 305SNFY, fat% and SNF% were 0.18 ± 0.05, 0.17 ± 0.05, 0.18 ± 0.05, 0.07 ± 0.03 and 0.15 ± 0.06 and posterior means of repeatability estimates along with posterior standard deviation for corresponding traits were 0.33 ± 0.04, 0.32 ± 0.04, 0.33 ± 0.04, 0.14 ± 0.02 and 0.30 ± 0.04, respectively. Estimates of genetic correlation varied from -0.080 (305MY and fat %) to 0.999 (305MY and 305SNFY). Permanent environmental correlations varied from -0.060 (305MY and SNF%) to 0.999 (305FY and 305SNFY). This study indicated that all considered traits except fat% have ample genetic variability which can be exploited for selection and genetic improvement of Murrah buffaloes.