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Comparisons of cows and herds in two progeny testing programs and two corresponding states
C N Vierhout1, B G Cassell, R E Pearson
1Department of Dairy Science, Virginia Polytechnic Institute, Blacksburg, USA.
Journal of Dairy Science
|April 23, 1999
Summary
Artificial insemination organizations selected superior herds for progeny testing. Herd characteristics did not predict bull performance, suggesting genetic segregation influences offspring yield deviations.
Area of Science:
- Animal Science
- Genetics
- Dairy Science
Background:
- Holstein progeny-test herds are crucial for genetic evaluations in artificial insemination (AI) programs.
- Understanding herd selection criteria and their impact on bull performance is vital for improving dairy cattle breeding.
Purpose of the Study:
- To analyze herd characteristics used by AI organizations for progeny testing.
- To determine if herd selection influences the predictability of bull genetic merit.
- To investigate the sources of variation in daughter yield deviations.
Main Methods:
- Utilized USDA genetic evaluations and Dairy Herd Improvement (DHI) profiles from 4154 Holstein progeny-test herds.
- Categorized herds based on AI organization (21st Century Genetics, Genex) and geographic location (Minnesota, New York).
- Analyzed daughter yield deviations relative to herd mean and variance, excluding extreme records.
Main Results:
- AI organizations selected herds that were larger, genetically superior, and better managed.
- Herd characteristics did not predict whether a bull's daughters would meet or exceed pedigree predictions.
- Extreme production records did not disproportionately appear in progeny of bulls considered for culling or further use.
Conclusions:
- The selection of superior herds by AI organizations is confirmed.
- Predicting progeny performance based solely on herd characteristics is not feasible.
- Observed differences in yield deviations for young sires likely stem from Mendelian segregation of genes.