title: Estimates of genetic parameters for daily somatic cell count of Australian dairy cattle.
abstract: Genetic parameters for daily somatic cell counts (SCC) of the first three parities were estimated for Australian Dairy Cattle. Most of the data analyses were carried out with a sire random regression model. The estimates were compared with those from conventional ten-trait analyses and animal models. In the first-parity estimates of heritabilities (h2) were low (0.04 to 0.05) at the beginning of the lactation and higher (0.11 to 0.13) at the end. The average h2 estimated from random regression sire model, random regression animal model and conventional multitrait sire model were 0.09, 0.09, and 0.08, respectively, in the first lactation. The average h2 were 0.09 and 0.11 in the second and third parities, respectively. Genetic correlations between daily log(e) SCC within parity were high for adjacent tests (nearly 1) and low (as low as 0.30) between the beginning and the end of the lactation. Generally, the genetic correlations between parities depend on how far apart they are and on whether they are on the same day in any two parities. Across parities, on average, genetic correlations between parities 1 and 3 were the lowest and those between 1 and 2 intermediate, while those between 2 and 3 were the highest. The estimated environmental correlations were lower than the genetic correlations, but the trends were generally similar. Differences in genetic parameter estimates due to model were small, except for some genetic correlations. The high residual error variances, the low h2, and the inconsistency in genetic correlations that were observed particularly at the beginning of the first lactation suggest that log(e) SCC early in the first lactation may be related to a spike in SCC as result of infection and (or) onset of lactation while SCC later in lactation represents a sustained response to infection. Accounting for the variation in heritabilities and correlations should improve the accuracy of genetic evaluations for SCC based on test day records.
authors.affiliation: Institute of Land and Food Resources, University of Melbourne, Parkville, Vic, Australia. Mekonnen.HaileMariam@nre.vic.gov.au
authors.forename: M
authors.initials: M
authors.lastname: Haile-Mariam
authors.forename: M E
authors.initials: ME
authors.lastname: Goddard
authors.forename: P J
authors.initials: PJ
authors.lastname: Bowman
mesh_terms: D000818:Animals; D002417:Cattle; D002452:Cell Count / Q000662:veterinary; D005260:Female; D007774:Lactation / Q000502:physiology*; D008414:Mastitis, Bovine / Q000235:genetics*; D008892:Milk / Q000166:cytology*; D008957:Models, Genetic; D010298:Parity; D012044:Regression Analysis