Genetic parameters for racing records in trotters using linear and generalized linear models

Area of Science:

• Animal Genetics
• Quantitative Genetics
• Equine Science

Background:

• Estimating genetic parameters for racing performance is crucial for effective breeding programs in trotting horses.
• Understanding heritability and repeatability of racing traits informs selection strategies for improved performance.

Purpose of the Study:

• To estimate heritability, repeatability, and genetic/phenotypic correlations for trotting race records in Finnhorses and Standardbred trotters.
• To evaluate the effectiveness of selection based on racing time, earnings, and other racing success indicators.

Main Methods:

• Utilized linear and generalized linear models with large datasets (over 500,000 records) for Finnhorses and Standardbred trotters.
• Applied various data transformations (logarithmic, fourth-root) and distributions (gamma, multinomial, binomial) to model different racing traits.
• Estimated genetic parameters including heritability, repeatability, and genetic and phenotypic correlations.

Main Results:

• Heritability was greatest for racing time (0.32–0.34) and moderate for annual earnings (0.19–0.27).
• Heritability for single earnings was low (0.01–0.09), while racing success traits ranged from 0.04 to 0.12.
• High genetic correlations were observed among racing traits, with moderate to high repeatability for racing time and annual earnings.

Conclusions:

• Selection for racing time and annual earnings is effective, especially when using repeated records.
• Direct selection for racing time and annual earnings is expected to yield substantial genetic improvement in overall racing success.
• Findings support the use of quantitative genetics principles for optimizing breeding strategies in trotting horse populations.