Genotype by environment interaction for fertility, survival, and milk production traits in Australian dairy cattle.
The existence of a genotype x environment interaction (G x E) for fertility traits, survival, and milk yield traits was examined by considering performance recorded in different calving systems (seasonal, split, and year round) or regions as different traits. For fertility traits and survival, G x E were also investigated by applying a random regression model using continuous environmental variables, such as level of herd milk production, temperature-humidity index, and herd size as environmental descriptors. The traits considered were calving interval, calving to first service interval (CFS), 25-d nonreturn rate at first service, pregnancy rate, survival, milk yield, fat yield, and protein yield and percentage. Data on Holstein-Friesian cows that calved between 1997 and 2005 were analyzed. The number of cows included in the analyses ranged from approximately 21,000 for pregnancy rate to approximately one-half million for survival. For all traits, heterogeneity in additive and phenotypic variances was observed. For example, for CFS the additive genetic and phenotypic variance in seasonal calving herds was only 9 and 15% of that in year-round calving herds, respectively. Genetic correlations among calving systems for milk yield traits were greater than 0.96. For calving interval, the lowest genetic correlation, of 0.83, was between split and year-round calving herds, but for CFS and pregnancy rate, genetic correlations as low as 0.37 were observed, although these estimates were associated with large standard errors. Genetic correlations between traits recorded in different Australian regions were greater than 0.89. Heritability and phenotypic variance for milk yield traits were the greatest in region 1, which consisted of Queensland, West Australia, South Australia, and New South Wales, and were least in region 3, which included Gippsland and Tasmania, in accordance with mean milk yield levels. Genetic correlations as low as 0.5 for some fertility traits between the 5th and 95th percentile of the distribution of the environmental descriptors, such as herd size and average herd milk production, were also observed. However, these estimates had large standard errors. Regardless of the environmental descriptor used, there was no evidence for the presence of a large G x E that resulted in economically significant reranking of bulls.
Haile-Mariam
M
M
Biosciences Research Division, Victorian Agribiosciences Centre, La Trobe University, Bundoora, Victoria 3086, Australia. Mekonnen.HaileMariam@dpi.vic.gov.au
Carrick
M J
MJ
Goddard
M E
ME
D000818:Animals; D001315:Australia; D002417:Cattle / Q000235:genetics*; D003612:Dairying; D004777:Environment; D005260:Female; D005298:Fertility / Q000235:genetics*; D005838:Genotype; D007774:Lactation / Q000235:genetics*; D008297:Male; D008892:Milk / Q000737:chemistry / Q000378:metabolism*; D010641:Phenotype; D011247:Pregnancy; D018873:Pregnancy Rate; D012044:Regression Analysis; D012621:Seasons; D016019:Survival Analysis