Simulation study of teat score in first-parity Gelbvieh cows: parameter estimation

Area of Science:

• Animal Science
• Genetics
• Quantitative Genetics

Background:

• Accurate data collection is crucial for genetic improvement in livestock.
• Teat scoring in Gelbvieh cows, a subjective measure of teat size, can be complex.
• Simplifying data collection methods may improve producer adoption and reduce misclassifications.

Purpose of the Study:

• To evaluate the adequacy of different teat score grouping approaches.
• To determine if simplified scoring methods decrease misclassifications and streamline data collection.
• To assess the impact of scoring methods on genetic progress for teat traits.

Main Methods:

• Utilized teat scores from 9,598 first-parity Gelbvieh cows.
• Tested scoring methods (all values, 10 classes, five classes) using simulated and field data.
• Employed a linear mixed model including herd-year, calving month, age, Gelbvieh percentage, and additive breeding values (BV).

Main Results:

• High Pearson correlations (≥0.92) were observed between estimated breeding values (BV) across different scoring methods (S50, S10, S5) in simulated data.
• Field data validation showed extremely high correlations (≥0.93) between BV estimated using different scoring classifications (F50, F10, F5).
• Simplified scoring classifications (10 and five classes) showed high agreement with the full scoring scale (S50/F50).

Conclusions:

• Simplified teat score classification methods can be adopted in Gelbvieh cattle breeding programs.
• These simplified methods are unlikely to compromise expected genetic progress for teat traits.
• Discrepancies between simulated and field data correlations may indicate real-world scoring inconsistencies.