Submitted to: International Symposium on Animal Production
Publication Type: Proceedings
Publication Acceptance Date: 9/29/1997
Publication Date: N/A
Citation: Interpretive Summary: The large dairy industry in the United States is evolving and embracing new technologies. Many organizations cooperate to achieve genetic improvement of the national dairy population: milk-recording agencies, dairy records processing centers, AI organizations, breeding companies, registry societies, universities, and Government research laboratories and extension programs. Genetic evaluations and supplemental information are distributed widely, primarily through industry cooperators and the internet. The steady increase in genetic trend for yield traits is indicative of the success of the genetic evaluation system for U.S. dairy animals. The system is modified frequently to meet U.S. dairy industry needs, such as greater flexibility in milk recording, and to exploit advances in computer technology and evaluation methodology, and the animal model, which is the statistical method that has been used to calculate genetic evaluations since 1989, has undergone frequent enhancement. A new statistical model based on information from individual test days is being developed that will more accurately estimate environmental influences, account for genetic differences in shape of the lactation curve and rate of maturity, better accommodate flexibility of the milk-recording system, and improve evaluation accuracy. The adoption of new technology will enable the U.S. dairy industry to maintain its position as a world leader in dairy cattle improvement.
Technical Abstract: The current genetic evaluation system for U.S. dairy cattle is based on an animal model that enables all relatives of each cow with lactation records to contribute to her and her sire's evaluations. Records from the first 5 lactations are included using a repeatability model. A first lactation is required for a record to affect relatives' evaluations. Changes since 1989 include using records from later herds for cows that change herds, accounting for reduced genetic variance of projected records, adjusting for heterogeneous variance, including age and parity in the model as well as adjusting records multiplicatively before analysis, accounting for inbreeding when forming the relationship matrix inverse, incorporating information from Canadian genetic evaluations, calculating genetic evaluations for productive life and somatic cell score, and including unsupervised records after additional editing to remove less reliable data. Evaluations are distributed primarily through industry cooperators and the internet. A test-day model is planned that will more accurately estimate environmental influences by defining effect of environment on a test-day basis and will account for genetic differences in lactation curve shape and maturity rate. Test-day data have been collected for calvings since 1990. Test-day effects and age and season effects specific to a herd will be estimated by analysis within herd; genetic effects will be estimated by multitrait analysis across herds after within-herd analysis. Simultaneous solutions can be achieved by repeating both analyses. Lactation data before 1990 will be included through correlations with test-day traits. Individual estimates of genetic merit by lactation stage and parity will allow greater precision in defining genetic indexes.