Integrating genomic selection for rapid improvement of milk yield in small-scale dairy farms

Abstract

The objective was to evaluate the efficiency of single-step genomic BLUP (ssGBLUP) compared with conventional BLUP for milk yield in Thai-Holstein dairy cows. Data included 130,195 test-day milk yield records from the first parity of 16,383 cows between 1999 and 2018, divided into 5 data sets according to different regions of Thailand. Genetic analyses were done with the BLUP and ssGBLUP methods using a repeatability test-day model. Fixed effects included farm–calving season combination, breed group–months in milk combination, and age at first calving. Random effects included additive genetic effects, permanent environmental effects, and herd-month-year of test. The heritability values for milk yield between BLUP and ssGBLUP methods did not yield any differences. However, those values among regions differed in accordance with environmental factors, i.e., weather and feed resources, which are apparently different among Thailand regions. The accuracy of the EBV in the ssGBLUP method (0.53–0.65) was greater than that of the BLUP method (0.50–0.60) in all regions, with a difference in accuracy from 3.85 to 8.33%. The EBV using the BLUP and ssGBLUP methods showed similar trends within regions, but those obtained by the ssGBLUP method were greater than those using the BLUP method in all regions. Genomic selection using the ssGBLUP method was accurate and computationally efficient. Considering accuracy and average of EBV, the switch from traditional methods to the ssGBLUP method for the Thai dairy cattle breeding program is a viable option.