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Update on the Test-Day Model

Update on the Test-Day Model. Test-Day Model. Data includes individual cow milk weights and component percentages recorded on test day

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Update on the Test-Day Model

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  1. Update on theTest-Day Model

  2. Test-Day Model • Data includes individual cow milk weights and component percentages recorded on test day • Genetic evaluations based on test-day (instead of lactation) data can account for environmental influences more accurately and for genetic differences in shape of the lactation curve

  3. Test-Day Model continued • Used in Canada and several European countries; Australia has used a test-day model since 1985 • Cornell Foundation granted patent in 1993, which has prevented the U.S. from implementing a test-day model; 2000 re-examination upheld the patent

  4. Test-Day Model continued • Canadian Dairy Network requested re-examination of patent in Canada; expects to learn if patent was upheld during 2002 • Several European groups are collecting information to show that patent should not be upheld in Europe

  5. Test-Day Data • Received at least weekly from regional computing centers • Includes information from nearly 30 million lactations from calvings since 1990 • Many checks to ensure data integrity

  6. Test-Day Data continued Lactation records calculated using best prediction • Upper and lower limits imposed • 60-150% of expected yield derived from preceding or adjoining normal test days • Floor and ceiling used • 1-2% of test-day yields affected • Test-days weighted according to correlation with 305-day yield • Weights affected by closeness to other test days

  7. Test-Day Data continued Recent changes: • Minimum days in milk decreased to 5 • Specific reporting of lactations that start with an abortion or reasons other than a normal calving

  8. Detecting Outlier Lactation Records • Some herds have high percentage of "elite" cows • Investigation showed abnormal distributions for lactations from those herds

  9. Outliers continued Possible solution: • Develop criteria based on normality statistics to detect herds with outlier lactation records • Adjust weight that records receive based on departure from normality • For extreme cases, cow's own records would have little influence on her evaluation Determine if reduced weight for extreme records improves accuracy of parent average in predicting future progeny performance

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