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Animals : an open access journal from MDPI2022; 12(19); 2630; doi: 10.3390/ani12192630

Comparison of Random Regression Models with Different Order Legendre Polynomials for Genetic Parameter Estimation on Race Completion Speed of Arabian Horses.

Abstract: This work aimed to compare the fitting performance of the random regression models applied to the different order orthogonal Legendre polynomials on the race completion speed (m/s) of Arabian racing horses. Legendre polynomial function for additive genetic, permanent environmental variances and heritability values with the L(2,2), L(2,3), L(3,2) and L(3,3) models (where L(i,j) means L(order of fit for additive genetic effects, order of fit for permanent environmental effects)) was estimated. A total of 233,491 race speed records (m/s) of Arabian horses were taken from the Jockey Club of Turkey between 2005 and 2016. The mean and standard deviation of heritability values were estimated as 0.294 ± 0.0746, 0.285 ± 0.0620, 0.302 ± 0.0767 and 0.290 ± 0.1018 for L(2,2), L(2,3), L(3,2), and L(3,3), respectively. The steady decreasing trend of permanent environmental variances for L(2,2) provided stationery for heritability values. According to Akaike information criterion (AIC) and Bayesian information criterion (BIC) values, the L(2,2) model could be reliably used to estimate heritability values for the racing speed of Arabian horses in the presence of repeated observations.
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Publication Date: 2022-09-30 PubMed ID: 36230370PubMed Central: PMC9559003DOI: 10.3390/ani12192630Google Scholar: Lookup
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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.

This research paper compares the effectiveness of random regression models applied to different orders of orthogonal Legendre polynomials for estimating genetic parameters related to the race completion speed of Arabian horses. The findings suggest that the L(2,2) model, a specific application of Legendre polynomials, is the most reliable method for estimating these parameters.

Study Scope and Data Collection

  • The study focused on estimating the genetic, environmental, and heritability parameters that influence the race completion speed (m/s) of Arabian horses.
  • The parameters were modeled using Legendre polynomials, a type of mathematical function suited for approximating complex curves.
  • Different models, detailed as L(2,2), L(2,3), L(3,2), and L(3,3), were compared in this study. The labels refer to the order of fit for the additive genetic effects and the environmental effects, respectively.
  • A large dataset of 233,491 records from the Jockey Club of Turkey, collected between the years 2005 and 2016, was utilized for this research.

Finding and Interpretation

  • The mean and standard deviation of the heritability values were calculated for each model. The L(2,2) model resulted in the most stationary values, with a mean of 0.294 and a standard deviation of 0.0746.
  • The study also found a steady decrease in environmental variances for the L(2,2) model, further supporting the superior performance of this model for estimating heritability values.
  • Heritability, in this context, refers to the proportion of observed differences in racing speed that can be attributed to inherited genetic differences as opposed to environmental factors.

Model Selection

  • The Akaike information criterion (AIC) and the Bayesian information criterion (BIC) were used to discuss the relative goodness of the models tested.
  • Both these criteria consider the ideal balance between adding complexity (and hence better accuracy) to a model and the risk of overfitting to the training data.
  • Based on these criteria, the L(2,2) model emerged as the optimal model for estimating heritability values for the racing speed of Arabian horses when dealing with repeated observations.

This research provides a solid foundation for future genetic modeling and horse breeding efforts, with potential implications for performance enhancement strategies adopted in the equestrian racing industry.

Cite This Article

APA
Önder H, Şen U, Piwczyński D, Kolenda M, Drewka M, Abacı SH, Takma Ç. (2022). Comparison of Random Regression Models with Different Order Legendre Polynomials for Genetic Parameter Estimation on Race Completion Speed of Arabian Horses. Animals (Basel), 12(19), 2630. https://doi.org/10.3390/ani12192630

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 12
Issue: 19
PII: 2630

Researcher Affiliations

Önder, Hasan
  • Department of Animal Science, Ondokuz Mayis University, 55139 Samsun, Turkey.
Şen, Uğur
  • Department of Agricultural Biotechnology, Ondokuz Mayis University, 55139 Samsun, Turkey.
Piwczyński, Dariusz
  • Department of Animal Biotechnology and Genetic, Faculty of Animal Breeding and Biology, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland.
Kolenda, Magdalena
  • Department of Animal Biotechnology and Genetic, Faculty of Animal Breeding and Biology, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland.
Drewka, Magdalena
  • Department of Animal Breeding and Nutrition, Faculty of Animal Breeding and Biology, Bydgoszcz University of Science and Technology, 85-796 Bydgoszcz, Poland.
Abacı, Samet Hasan
  • Department of Animal Science, Ondokuz Mayis University, 55139 Samsun, Turkey.
Takma, Çiğdem
  • Department of Animal Science, Ege University, 35040 İzmir, Turkey.

Grant Funding

  • PPI/APM/2019/1/00003 / Polish National Agency for Academic Exchange

Conflict of Interest Statement

The authors declare no conflict of interest and none of the authors of this paper has a financial or personal relationship with other people or organizations that could inappropriately influence or bias the content of the paper.

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