Application of multiple-trait herd cluster model for genetic evaluation of dairy sires from seventeen countries

The multiple-trait across country evaluation method is currently used for international genetic evaluation of dairy sires. This method simultaneously combines national estimated breeding value (EBV) of sires in all countries and produces a separate breeding value to be used in each of the 24 countries that participate in the service. The major drawbacks to this method are the large number of genetic parameters that must be estimated and the large number of EBV produced for each sire. In the current method, each sire receives an EBV for each separate environment, and environments change at the country borders. It is unreasonable to assume that each country contains only one homogeneous environment and that every country has a distinctly different environment from all others. In the present study, an alternative method for international sire evaluation was utilized. Herds were grouped according to important management, climatic, and genetic factors rather than country borders. Data consisted of 16,403,413 first lactation cows in Australia, Austria, Belgium, Canada, Czech Republic, Estonia, Finland, Germany, Hungary, Ireland, Israel, Italy, The Netherlands, New Zealand, South Africa, Switzerland, and the United States. Herds were grouped according to 13 descriptive herd variables, including temperature, rainfall, peak yield, persistency, herd-size, age at calving, seasonality of calving, standard deviation of milk yield, culling percentage, fat-to-protein ratio, days to peak yield, percent of North American Holstein genes, and average PTA milk of sires. Variables were weighted by their relative importance in explaining genotype by environment interactions between herds. Herds were grouped into seven clusters; clusters ranged in size from 4805 to 59,272 herds and 1,414,966 to 3,966,431 cows. The proposed model predicts EBV for dairy sires based on the production environment in which their progeny will perform, rather than the country where they will be located.