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A Tool for Monitoring Genetic Selection Differentials in Dairy Herds in Canada
B. A. Hagan, R. I. Cue
Department of Animal Science, McGill University, Macdonald Campus, Ste-Anne-de-Bellevue, Quebec, H9X 3V9, Canada

A software tool was developed to allow a dairy producer and/or agricultural advisor to monitor the genetic selection differentials (GSD) that a dairy farm is making. The objectives of this study were (i) to monitor GSD in individual farms, over years, so that producers can be advised as to whether or not they are achieving their selection objectives (and hence optimizing productivity and profitability); (ii) the development of a prototype software tool and visualization model to assist producers in interpreting the results for their individual farm, and to compare their farm results with suitable benchmarks. Data used for this study were the EBVs routinely calculated by the Canadian Dairy Network (CDN), for Milk Yield, Fat Yield, Protein Yield and Lifetime Profit Index. The Canadian Ayrshire breed has been used as a model, test breed; records on animals born between January 1980 and April 2016 were used. For each day between this period, the average sire EBV of all the sires available for use on that day was calculated; sires availability determined from the dates of sires’ first and last usage. Sire GSD was then calculated as the EBV of the Sire of a cow minus the average sire EBV on the date the cow was conceived. The average GSD for the entire population, top and bottom 10% sires, and top and bottom 10% of herds per year of conception were computed and stored in a database. This then allows an individual producer to compare and visualize the individual animal selection he/she is making, and also to compare his/her herd against the average herd and the top 10% of herds (as a reference goal to potentially aim to also achieve). The developed software tool is updatable every time CDN releases new genetic evaluation list. The concept can be equally well applied to the other dairy breeds and livestock species for which genetic evaluations are routinely computed. This methodology is not limited to only the four named traits but can also be used for all traits genetically evaluated (currently approximately 30 traits in Canada), allowing a producer to monitor multiple traits and hence decide upon his/her selection objectives.

Keyword: Ayrshire, dairy, Estimated Breeding Values, Genetic selection differential, milk yield