Multibreed genetic parameters and predicted genetic values for first lactation 305-d milk yield, fat yield, and fat percentage in a bos taurus X bos indicus multibreed dairy population in Thailand

Estimates of multibreed covariance components, genetic parameters, and predicted genetic values for first lactation 305-d milk yield (MY), 305-d fat yield (FY), and 305-d fat percentage (FP) were obtained using production records from 481 purebred and crossbred cows in a Thai multibreed dairy population. Multibreed covariance components were estimated by restricted maximum likelihood procedures using a generalized expectation-maximization algorithm suitable for multibreed populations. Two multibreed sire-maternal grandsire models (BTBI and HO) that accounted for intrabreed additive genetic effects, and intralocus intra and interbreed nonadditive genetic effects were used for the analyses. The BTBI model considered Bos Taurus (BT) and Bos indicus (BI) fractions, whereas the HO model accounted for Holstein (H) and Other breeds (O) fractions. Additive and nonadditive genetic covariance estimates for base population BI (or O) were larger than those for base population BT (or H) for all traits, while base environmental covariance estimates for BI (or O) were smaller than BT (or H). Ranges of multibreed heritability estimates for MY (0.07 to 0.42), FY (0.08 to 0.45), and FP (0.04 to 0.39) across all breed group combinations represented in the data set were within the ranges of unibreed estimates found elsewhere. Estimates of interactibilities were smaller than those of heritabilities for all traits. Multibreed additive and nonadditive genetic correlations ranged from 0.37 to 0.79 for (MY, FY), and they were close to zero for (MY, FP) and (FY, FP). Ranges of sire additive, nonadditive, and total multibreed predicted genetic values (MPGV) were wider for MY and FY in the HO than in the BTBI model. The opposite occurred for FP. Sire rankings by additive, nonadditive, and total MPGV in the BTBI were highly correlated (0.98) to those in the HO model. High correlations (0.99) also existed between sire rankings by additive, nonadditive, and total MPGV within models. The analyses conducted here showed the feasibility of using multibreed procedures for prediction of genetic values and estimation of covariance components in highly unbalanced small multibreed field dairy datasets. However, the large standard errors of prediction obtained here pointed out the need for substantially larger and more balanced multibreed datasets to obtain more reliable genetic predictions useable for genetic improvement programs in Thailand.