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Short communication: Genetic parameters of production traits in Chinese Holsteins using a random regression test-day model

F. Miglior^*,,1,2, W. Gong^,1, Y. Wang, G. J. Kistemaker, A. Sewalem^*, and J. Jamrozik

^* Agriculture and Agri-Food Canada, Dairy and Swine Research and Development Centre, Sherbrooke, Quebec, Canada, J1M 1Z3
Canadian Dairy Network, Guelph, Ontario, Canada, N1G 4T2
China Agricultural University, Beijing, China, 100193
Centre for the Genetic Improvement of Livestock, University of Guelph, Guelph, Ontario, Canada, N1G 2W1

² Corresponding author: miglior{at}cdn.ca

The objective of this study was to estimate genetic parameters of production traits in the first 3 parities in Chinese Holsteins. Data were a random sample of complete herds (109,005 test-day records of 9,706 cows from 54 herds) extracted from the original data set, which included 362,304 test-day records of 30,942 Holstein cows from 105 herds. A test-day animal model with multiple-trait random regression and the Gibbs sampling method were used for parameter estimation. Regression curves were modeled using Legendre polynomials of order 4. The multiple-trait analysis included milk, fat, and protein yield, and somatic cell score (SCS). Average daily heritabilities ranged between 0.222 and 0.346 for the yield traits and between 0.092 and 0.187 for SCS. Heritabilities were higher in the third lactation for all traits. Within-parity genetic correlations were very high among the yield traits (>0.806) and were close to zero between SCS and yield traits, especially for first-parity cows. Results were similar to previous literature estimates from studies that used the same model as applied to this study. The estimates found in this study will be used to perform breeding value estimation for national genetic evaluations in Chinese Holsteins.

Key Words: genetic parameter • random regression model • Chinese Holstein