Evaluating Sire Selection Practices Using Lifetime Net Income Functions

• Published in: Journal of dairy science 2002-12, Vol.85 (12), p.3492-3502
• Main Authors: Cassell, B.G., Jobst, S.M., McGilliard, M.L., Pearson, R.E.
• Format: Article
• Language: English
• Subjects: Animal productions; Animals; Biological and medical sciences; Breeding; Cattle - genetics; Costs and Cost Analysis; Dairying - economics; Dairying - methods; Female; Fundamental and applied biological sciences. Psychology; Income; Insemination, Artificial - veterinary; Lactation - genetics; lifetime profit; Male; Milk - economics; Net Merit; Regression Analysis; Selection, Genetic; sire evaluations; Terrestrial animal productions; Vertebrates
• ISSN: 0022-0302; 1525-3198
• DOI: 10.3168/jds.S0022-0302(02)74438-X

Dairy farmers do not take full advantage of opportunities available for genetic improvement through use of artificial insemination, perhaps because economic advantages of good sire selection may not be fully recognized or understood. This study was undertaken to document differences between use of AI and non-AI bulls and to develop prediction equations to compare lifetime economic merit of future progeny from alternative sire selection policies. We describe the use of two methods of measuring lifetime economic merit, with and without adjustment for opportunity cost of a postponed replacement. Comparison of lifetime relative net income adjusted for opportunity cost on groups of cows sired by different kinds of bulls showed that daughters of proven AI bulls generated $148 and $120 more lifetime net income under fluid and manufactured milk market conditions than daughters of non-AI bulls. Daughters of proven AI bulls produced $60 more than daughters of AI young sires in progeny testing programs at the time of daughter conception. We developed prediction equations from combinations of genetic evaluations for production, productive life, SCS, and linear type traits on sires to predict lifetime relative net income of progeny produced from alternative sire selection strategies. Prediction equations explained 14 to 18% of variation in relative net income (not adjusted for opportunity cost), but herd and year of first freshening accounted for considerably more variation than did genetic evaluations on the sire of the cow. Finally, two independent data sets were used to develop and test predictions of lifetime relative net income adjusted for opportunity cost using genetic evaluations based on the eight traits included in the Merit indexes for the sire of each cow. Prediction equations from odd numbered herds were used to predict lifetime economic merit in even numbered herds and vice versa. Coefficients of determination ranged from 0.088 to 0.103 and averaged 0.004 higher than prediction equations with Net or Fluid Merit. Accuracy of predictions showed that Net and Fluid Merit were robust and useful indexes that accurately identified bulls whose daughters generated highest lifetime economic merit.