Modelling repeated competition records in genetic evaluations of Danish sport horses.

This study is on the genetic evaluation of sport performance in Danish Warmblood horses, comparing various performance records to identify the most effective method of analysis.

Introduction

The research revolves around the genetic evaluations of sport performance in Danish Warmblood horses. It considers various competition records and performance data in models, with the end goal of identifying the most efficient and accurate methodology for performance evaluation. The researchers aim to balance the accuracy of results against the computational demands of the various methods.

Methods

• The research entails multiple runs using different variables and standards for comparison.
• These include repeated competition ranking points (run A), mean ranking points (runs B and C), mean ranking points pre-corrected for effects associated with each competition (run D), and the accumulated lifetime points (run E).
• The computational resources used for every run are compared, termed as CPU times.

Findings

• CPU times required for run A were significantly higher when compared to runs B to E.
• The results indicated that model ‘D’, involving mean ranking points pre-adjusted for each competition, matched perfectly with the results of model ‘A’, that used repeated competition ranking points.
• Highest reliabilities were observed in run E (accumulated lifetime points) and run A (repeated competition ranking points).
• The model offering the best predictive ability and least bias differed for dressage and show jumping. Run C proved best for dressage, while run E was optimal for show jumping.

Conclusion

• Model D was observed to be the second best in both disciplines and is expected to improve over time considering the relatively large amount of historical data incorporated.

In summary, the research identifies the use of mean ranking points pre-adjusted for every competition (model D) as an efficient and effective method for the genetic evaluation of sport performance in Danish Warmblood horses, balancing between computational demand and data accuracy.