Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/28/1999
Publication Date: N/A
Citation: N/A Interpretive Summary: More than 30 new test plans for milk recording were proposed and introduced in the United States between 1989 and 1995 in response to market requests. The various test plans differ widely in the numbers of milk weights recorded and component samples taken. From 1980 to August 1998, records in progress were extended to 305 days for use in national genetic evaluations by using the test interval method. However, equations that include all test day yields can provide more accurate estimates of lactation yield, especially if the relationship between individual test days is considered in the prediction equations. This study determined the relationships among individual daily yields of milk, fat, and protein and somatic cell sore and developed a method of expressing those relationships among all test day observations accurately and in a manner that minimized computer memory requirements. The computer programs that resulted from this study are being made available to the dairy industry and can be used to improve predictions of daily and lactation yields of milk, fat, and protein and somatic cell score nationally, regionally, or on the farm and to indicate the accuracy of the predictions.
Technical Abstract: Prediction of lactation yields and accuracies of yields for use in genetic evaluation can be improved by including information from test day correlations, especially for milk recording plans that vary in the numbers of milk weights recorded and component samples taken. Daily milk weights for 658 lactations of Canadian cows and monthly test records of milk, fat, and protein yields and somatic cell scores for 500,000 lactations of U.S. cows were used to estimate phenotypic correlations between test days within herd-year. Correlations between daily yields for a designated interval between test days generally were highest for mid-lactation and lowest for early and late lactation. Regression (two linear, two quadratic, and interaction effects) on mean DIM and interval between test days predicted correlations with a squared correlation of .94 for daily milk yields. Similar relationships were found for U.S. monthly data. Sampling variation was reduced, and computer memory was minimized by fitting regression equations to large correlation matrices. The equations developed can be used to derive covariances and subsequently to estimate individual daily milk, fat, and protein yields and somatic cell score or lactation totals for any combination of daily recordings for those traits.