Calculation of lifetime net income per year (LTNI/year) of Australian Holstein cows to validate the Australian profit ranking of their sires. 2. Validation of the Australian profit ranking of sires and test for genotype by environment interaction based on LTNI/year
M. Haile-Mariam A C , P. J. Bowman A and M. E. Goddard A BA Biosciences Research Division, Department of Primary Industries, La Trobe R&D Park, 1 Park Drive, Bundoora, Vic. 3083, Australia.
B Department of Agriculture and Food Systems, The University of Melbourne, Vic. 3010, Australia.
C Corresponding author. Email: mekonnen.hailemariam@dpi.vic.gov.au
Animal Production Science 50(8) 767-774 https://doi.org/10.1071/AN09233
Submitted: 29 December 2009 Accepted: 8 June 2010 Published: 31 August 2010
Abstract
In Australia, the Australian Dairy Herd Improvement Scheme publishes the Australian profit ranking (APR), which is an economic index combining all economic traits. The APR is used to select sires that will breed the most profitable daughters. The objectives of this study were to test the predictive power of the APR by looking at the relationship between the APR of sires and lifetime net income per year (LTNI/year) of their future daughters and to test if this prediction was accurate in different types of herds. The importance of re-ranking was also tested by considering LTNI/year of cows in different herds as different traits and estimating the genetic correlation between LTNI/year in different herd types (herds differing in calving systems, region or production level). An additional objective was to test the value of individual trait Australian breeding values (ABV) of sires to predict LTNI/year of their future daughters.
The results show that overall the relationship between the APR of bulls and the LTNI/year of their daughters was as expected. That is, the regression of daughter’s LTNI/year on sire’s APR equals 0.5 as expected because cows inherit half their genes from their sire. When LTNI/year of cows was regressed on sire’s APR separately for different herd types, the regression coefficients varied from 0.36 (low production herds) to 0.62 (high production herds). The genetic correlation for LTNI/year between herd types was always high indicating little re-ranking of sires. The lowest was 0.89 between LTNI/year of cows in seasonal and year-round calving systems as well as between Regions 3 (Gippsland and Tasmania) and Region 1 (New South Wales, Queensland, South Australia and Western Australia) herds. Thus, an APR calculated across all herd types will give a good ranking of bulls in any herd type. When LTNI/year of cows was regressed on individual sire ABV the regression coefficients were approximately half the economic weight for each trait as expected. Within seasonal calving and low production herds the regression on sire’s fertility ABV was higher than expected and the regression in year-round and high production herds was less than expected.
In conclusion, over all herds the sire’s APR predicts LTNI/year of future daughters as expected. Owners of low production, seasonal calving herds will get slightly less benefit from 1 unit increase in APR than owners of high production, year-round calving herds and could perhaps benefit from placing additional emphasis on the fertility ABV when selecting sires.
Acknowledgements
This research is funded by Dairy Australia and the Victorian Department of Primary Industries. We thank ADHIS for providing the data. We also thank Dr Kon Konstantinov and Kevin Beard for their help with obtaining ABV of bulls.
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