Northrop, A, J, Hobbs, Sarah Jane ORCID: 0000-0002-1552-8647, Holt, D, Clayton-Smith, E and Martin, J, H (2016) Spatial variation of the physical and biomechanical properties within an equestrian arena surface. Procedia Engineering, 147 . pp. 866-871. ISSN 1877-7058
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Official URL: http://dx.doi.org/10.1016/j.proeng.2016.06.288
Abstract
There is limited information about spatial variation of equestrian arena surfaces despite unequivocal evidence to suggest that lack of uniformity increases risk of injury. Spatial differences in the functional properties of an arena are likely to be due to a number of intrinsic and extrinsic characteristics including variation in the physical properties of the surface. The aim of this work was to examine spatial variation of peak load (cushioning) across an arena surface and investigate the influence that physical properties had on these variations using Principal Component Analysis. Sampling (n=61) of a 20 m by 65 m indoor synthetic equestrian arena surface occurred in one day using an Orono biomechanical surface tester (OBST). The OBST was used at every location to measure peak load (dropped twice on the same point). A 200 g sample of the surface was taken from the point of impact (at every location) and the physical properties were assessed in the laboratory. Samples were oven dried at 45⁰C for 24 hours in order to measure moisture content and percentage binder was quantified using Soxhlet extraction. Sand particle size distribution were determined using sieving and sedimentation methods and percentage organic matter was achieved by burning off organic material using a muffle furnace at 440⁰C. The surface was characterized by three principal components (PC1, PC2 and PC3). Peak load and moisture were the first principal components that accounted for 41% of surface variation. Percentage organic matter and percentage binder were identified as PC2 (20%) and PC3 (18%) respectively. This highlights their respective importance in surface variation. There was a moderate negative correlation between moisture and peak load (rs = 54%; P<0.0001) however cluster analysis revealed that peak load and moisture were grouped into five areas of similarity that corresponded to sample location, reinforced using an ANOVA (P<0.0001). The findings demonstrate an effective method of assessing uniformity and additionally, identify physical factors relevant to the load carrying capacity of this specific surface. Uneven surfaces can influence horse and rider safety therefore recognizing appropriate techniques to monitor spatial variation and implement relevant maintenance, is of key importance to equestrian athletes.
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