Omneity® Pellets
All-In-One Vitamin & Mineral Pellet
Assessing the predictability of racing performance of Thoroughbreds using mixed-effects model.
Abstract: The inheritance of racing performance in Thoroughbreds is of interest to breeders and geneticists. Therefore, the genetic parameters of racing performance have been investigated in various populations of Thoroughbreds. However, the predictability of the racing performance of a racehorse has not been assessed well. In this study, we built mixed-effects models for Japanese Thoroughbreds and assessed their predictability of racing performance. We used the average velocity as an index of racing performance and treated each category of racecourse and distance as different traits. Model selection using the deviance information criterion showed that explanatory variables, such as race, age and jockey effects are important for racing performance. Using the selected models, the phenotypic values of horses born after 2009, adjusted using the entire dataset, were predicted with the breeding values estimated from a partial dataset until 2010. The correlation coefficients ranged from 0.000 to 0.235 (average of 0.084 ± 0.066) and were higher for longer distances. When predicting the graded race winners born after 2009 from the partial dataset until 2010, the area under the curve values ranged from 0.516 to 0.776 (average of 0.613 ± 0.073) and were also higher for longer distances. Although these results indicate the predictability of racing performance, further efforts, including exploring more suitable racing performance indices and refining statistical modelling, are required for improvement.
© 2023 The Authors. Journal of Animal Breeding and Genetics published by John Wiley & Sons Ltd.
Publication Date: 2023-08-28 PubMed ID: 37635693DOI: 10.1111/jbg.12822Google Scholar: Lookup The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
Summary
This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.
The research article explores the predictability of racing performance of Thoroughbreds using a mixed-effects model, with the average velocity as the key indicator of performance. Various factors were taken into consideration, such as race, age, and jockey effects.
Objective of the Research
- The main goal of the research was to understand the predictability of the racing performance of Thoroughbreds by building and assessing mixed-effects models. This research is significant for breeders and geneticists who are interested in the inheritance of racing performance in these horses.
The Mixed-Effects Models
- Researchers used mixed-effects models specifically for Japanese Thoroughbreds, treating each category of racecourse and distance as separate traits.
- The average velocity was used as the primary index of racing performance.
- Factors such as the type of race, the horse’s age, and effects from the jockey were identified as essential explanatory variables impacting the racing performance.
Model Selection and Predictions
- Using the deviance information criterion, they conducted model selection that indicated the importance of race, age and jockey effects for racing performance.
- The selected models were used to predict the phenotypic values of horses born after 2009 using breeding values estimated from a partial dataset available until 2010.
- The correlation between these predicted and actual performances varied greatly (from 0.000 to 0.235), with the average correlation being weak (0.084 ± 0.066). The correlation was found to be higher for longer distances.
Evaluation
- When predicting the graded race winners born after 2009 from the partial dataset till 2010, the researchers got an average area under the curve value of 0.613 ± 0.073, with values ranging from 0.516 to 0.776, indicating the moderate success of their model. The values were higher for longer distances.
- These results demonstrate that racing performance can be somewhat predicted, but further refinement of the statistical modelling and better identification of suitable racing performance indices are required to enhance the predictability.
Cite This Article
APA
Oda D, Onogi A.
(2023).
Assessing the predictability of racing performance of Thoroughbreds using mixed-effects model.
J Anim Breed Genet.
https://doi.org/10.1111/jbg.12822 Publication
Researcher Affiliations
- Department of Life Sciences, Faculty of Agriculture, Ryukoku University, Otsu, Shiga, Japan.
- Department of Life Sciences, Faculty of Agriculture, Ryukoku University, Otsu, Shiga, Japan.
References
This article includes 17 references
- Abraham G, Inouye M. Genomic risk prediction of complex human disease and its clinical application. Current Opinion in Genetics & Development 33, 10-16.
- Bailey E, Petersen JL, Kalbfleisch TS. Genetics of Thoroughbred racehorse performance. Annual Review of Animal Biosciences 10, 131-150.
- Bedford J. The world atlas of horse racing. .
- Bugislaus A, Roehe R, Willms F, Kalm E. The use of a random regression model to account for change in racing speed of German trotters with increasing age. Journal of Animal Breeding and Genetics 123(4), 239-246.
- Ekiz B, Koçak Ö. Estimates of genetic parameters for racing times of Thoroughbred horses. Turkish Journal of Veterinary & Animal Sciences 31(1), 1-5.
- Ekiz B, Kocak Ö, Yilmaz A. Phenotypic and genetic parameter estimates for racing traits of Thoroughbred horses in Turkey. Archives Animal Breeding 48(2), 121-129.
- Hayes BJ, Daetwyler HD, Goddard ME. Models for genome x environment interaction: Examples in livestock. Crop Science 56(5), 2251-2259.
- Misztal I, Tsuruta S, Strabel T, Auvray B, Druet T, Lee DH. BLUPF90 and related programs. Proc. 7th World Congress on Genetics Applied to Livestock Production, Montpellier, France .
- Moritsu Y, Funakoshi H, Ichikawa S. Genetic evaluation of sires and environmental factors influencing best racing times of Thoroughbred horses in Japan. Journal of Equine Science 5(2), 53-58.
- Moritsu Y, Terai A, Tashiro T. Relationship between sire breeding values for the rating score on turf and dirt racing tracks in Thoroughbred racehorses. Journal of Equine Science 9(3), 89-92.
- Mota MD, Abrahão AR, Oliveira HN. Genetic and environmental parameters for racing time at different distances in Brazilian Thoroughbreds. Journal of Animal Breeding Genetics 122, 393-399.
- Oki H, Sasaki Y, Lin CY, Willham RL. Influence of jockeys on racing time in Thoroughbred horses. Journal of Animal Breeding and Genetics 112(1-6), 171-175.
- Oki H, Sasaki Y, Willham RL. Genetic parameter estimates for racing time by restricted maximum likelihood in the thoroughbred horse of Japan. Journal of Animal Breeding and Genetics 112(1-6), 146-150.
- R Core Team. R: A language and environment for statistical computing. .
- Sobczynska M. Genetic correlations between racing performance at different racing distances in Thoroughbreds and Arab horses. Czech Journal of Animal Science 51(12), 523.
- Thiruvenkadan AK, Kandasamy N, Panneerselvam S. Inheritance of racing performance of Thoroughbred horses. Livestock Science 121(2-3), 308-326.
- Velie BD, Hamilton NA, Wade CM. Heritability of racing performance in the Australian thoroughbred racing population. Animal Genetics 46, 23-29.
Citations
This article has been cited 0 times.Use Nutrition Calculator
Check if your horse's diet meets their nutrition requirements with our easy-to-use tool Check your horse's diet with our easy-to-use tool
Talk to a Nutritionist
Discuss your horse's feeding plan with our experts over a free phone consultation Discuss your horse's diet over a phone consultation
Submit Diet Evaluation
Get a customized feeding plan for your horse formulated by our equine nutritionists Get a custom feeding plan formulated by our nutritionists
