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Home / Equine Research Bank / PLoS One / Evaluation of thermal pattern distributions in racehorse sad...
PloS one2019; 14(8); e0221622; doi: 10.1371/journal.pone.0221622

Evaluation of thermal pattern distributions in racehorse saddles using infrared thermography.

Abstract: The impact of a rider's and saddle's mass on saddle thermal pattern distribution was evaluated using infrared thermography (IRT). Eighteen racehorses were ridden by four riders with their own saddle. Images of the saddle panels were captured at each of six thermographic examinations. On each image, six regions of interest (ROIs) were marked on the saddle panels. The mean temperature for each ROI was extracted. To evaluate the influence of load on saddle fit, 4 indicators were used: ΔTmax (difference between the mean temperature of the warmest and coolest ROI); standard deviation of the mean temperature of the six ROIs; right/left; bridging/rocking and front/back thermal pattern indicator. Incorrect saddle fit was found in 25 measurements (23.1%) with ΔTmax greater than 2°C. The relationships between rider and saddle fit as well as saddle fit and horse were significant (p<0.001). An average ΔTmax in rider A was significantly higher than in other riders (p<0.001). The right/left thermal pattern differed significantly from the optimal value for riders A and B; while the bridging/rocking thermal pattern differed significantly from this value for riders A, C and D (p<0.05). Front saddle thermal pattern was most frequent for rider A (41.5%), whereas back saddle thermal pattern was most frequent for rider C (85.7%). Measurement of the mean temperature in 6 ROIs on saddle panels after training was helpful in assessing the influence of rider and saddle mass on saddle fit. IRT offered a non-invasive, rapid and simple method for assessing load on thermal pattern distribution in race saddles.
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Publication Date: 2019-08-26 PubMed ID: 31449556PubMed Central: PMC6709906DOI: 10.1371/journal.pone.0221622Google Scholar: Lookup
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  • 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.

This study investigates how the weight of a rider and saddle influences the thermal pattern distribution in racehorse saddles, using infrared thermography. The research finds significant links between the rider, the fit of the saddle, and the horse itself.

Methodology

  • The study involved eighteen racehorses, each ridden by four different riders using their own saddles.
  • Infrared thermographic (IRT) images were captured of each saddle in certain regions at multiple intervals during the study.
  • The average temperature within six marked regions of interest (ROIs) on each saddle were calculated and noted.

Evaluation

  • The weight load on the saddle fit was evaluated using four indicators: the maximum temperature difference (ΔTmax), the standard deviation of the average temperature across the ROIs, the left/right and front/back balance, and the bridging/rocking thermal pattern.
  • A ΔTmax greater than 2°C, indicating a poorly fitted saddle, was noticed in 25 measurements (23.1% occurrences).

Results

  • The relationship between the rider and saddle fit, as well as between the saddle fit and the horse, were found to be significant.
  • The average ΔTmax index for Rider A was notably higher compared to the other riders.
  • Exceptions were also noticed in the optimum thermal pattern between the left and the right side for Riders A and B, and in the bridging/rocking pattern for Riders A, C, and D.
  • Rider A had a high frequency of the front saddle thermal pattern (41.5%), while Rider C showed a largely occurring back saddle thermal pattern (85.7%).

Conclusion

  • The research found measuring the average temperature in the 6 ROIs on saddle panels after a riding session can help assess the impact of a rider and saddle’s mass on saddle fit.
  • IRT was shown to be a fast, simple, and non-invasive technique for assessing the distribution of thermal pattern load in racing saddles.

Cite This Article

APA
Soroko M, Zaborski D, Dudek K, Yarnell K, Górniak W, Vardasca R. (2019). Evaluation of thermal pattern distributions in racehorse saddles using infrared thermography. PLoS One, 14(8), e0221622. https://doi.org/10.1371/journal.pone.0221622

Publication

PloS one
ISSN: 1932-6203
NlmUniqueID: 101285081
Country: United States
Language: English
Volume: 14
Issue: 8
Pages: e0221622
PII: e0221622

Researcher Affiliations

Soroko, Maria
  • Department of Horse Breeding and Equestrian Studies, Institute of Animal Breeding, Wroclaw University of Environmental and Life Sciences, Wroclaw, Poland.
Zaborski, Daniel
  • Department of Ruminants Science, West Pomeranian University of Technology, Szczecin, Poland.
Dudek, Krzysztof
  • Faculty of Mechanical Engineering, Wroclaw University of Technology, Wroclaw, Poland.
Yarnell, Kelly
  • School of Animal, Rural and Environmental Sciences, Nottingham Trent University, Southwell, Nottinghamshire, United Kingdom.
Górniak, Wanda
  • Department of Environmental Hygiene and Animal Welfare, Wroclaw University of Environmental and Life Sciences, Wroclaw, Poland.
Vardasca, Ricardo
  • INEGI-LAETA, Faculdade de Engenharia, Universidade do Porto, Porto, Portugal.

MeSH Terms

  • Animals
  • Body Weight
  • Horses / physiology
  • Humans
  • Infrared Rays
  • ROC Curve
  • Temperature
  • Thermography

Conflict of Interest Statement

The authors have declared that no competing interests exist.

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Citations

This article has been cited 13 times.
  1. Zielińska P, Soroko-Dubrovina M, Dudek K, Ruzhanova-Gospodinova IS. A Preliminary Study of the Influence of High Intensity Laser Therapy (HILT) on Skin Surface Temperature and Longissimus Dorsi Muscle Tone Changes in Thoroughbred Racehorses with Back Pain. Animals (Basel) 2023 Feb 22;13(5).
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  3. Verdegaal EJMM, Howarth GS, McWhorter TJ, Delesalle CJG. Is Continuous Monitoring of Skin Surface Temperature a Reliable Proxy to Assess the Thermoregulatory Response in Endurance Horses During Field Exercise?. Front Vet Sci 2022;9:894146.
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