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ARS Home » Research » Publications at this Location » Publication #85557
Title: MERIT OF OUTLIERS FOR MILK YIELD AS INDICATORS OF ACCURACY OF GENETIC EVALUATIONS OF SIRES

Author
item MEINERT, TODD - NDHIA, COLUMBUS, OH
item NORMAN, H

Submitted to: Journal of Dairy Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 8/13/1998
Publication Date: N/A
Citation: N/A

Interpretive Summary: A program has been developed that will provide more information about the characteristics of a dairy herd so that dairy industry users can better assess the accuracy of individual herd data. Part of this program is the identification of standardized milk records that exceed 1.5 interquartile ranges below percentile 25 or above percentile 75. Such extreme records are designated as "outliers." To determine if the accuracy of genetic evaluations of bulls can be assessed by the presence of outlier records of daughters, data from daughters of Holstein bulls that were not sampled by artificial insemination (AI) organizations but which later entered AI were studied. Bulls sampled through non-AI that had evaluations that decreased had higher frequencies of 1st daughters in herds with outliers for standardized milk yield, especially where the daughters were positive outliers and daughters of other bulls were negative outliers. Based on results of this study, AI organizations are recommended to consider the number of daughter outliers before purchasing semen from bulls sampled through non-AI.

Technical Abstract: To determine if accuracy of sire genetic evaluations can be assessed by presence of extreme daughter records, herd-years with records from 1st- crop daughters of 217 Holstein bulls that were not sampled by artificial insemination (AI) organizations but which later entered AI were studied. Presence of outliers for standardized milk yield was determined within herd-year. Outliers were defined as records >1.5 interquartile ranges below percentile 25 or above percentile 75. Herd-years were separated into 2 groups based on whether or not an outlier daughter record for an AI bull initially sampled through non-AI was present. Herd-years without daughter outliers from those bulls were divided into herd-years with 1) no daughter outliers from any bull, 2) only negative daughter outliers from other bulls, 3) only positive daughter outliers from other bulls, or 4) negative and positive daughter outliers from other bulls. Herd-years with daughter outliers from AI bulls initially sampled through non-AI were divided into herd-years with 1) only negative daughter outliers, 2) only positive daughter outliers, 3) positive daughter outliers from those bulls and negative daughter outliers from other bulls, or 4) both negative and positive daughter outliers. The relationship between frequency of outlier classes and change in Modified Contemporary Comparison genetic evaluations (difference between last available 2nd-crop evaluation and next-to-last 1st-crop evaluation) was examined with logistic regression. For AI bulls initially sampled through non-AI that had evaluations that decreased >386 kg, 9% of herd-years had positive daughter outliers and negative daughter outliers from other bulls; 38% had no outliers. For bulls with evaluations that increased >194 kg, comparable percentages were 2 and 53%.