Phenotypic Associations Between Linearly Scored Traits and Sport Horse Auction Sales Price in Ireland
This study examines the associations between linearly scored phenotypic traits and auction sales prices of young event horses in Ireland, aiming to identify key traits influencing market value. Data from 307 horses sold at public auctions (2022–2023) were analysed using regression analysis, binary o...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Animals |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-2615/15/15/2227 |
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| Summary: | This study examines the associations between linearly scored phenotypic traits and auction sales prices of young event horses in Ireland, aiming to identify key traits influencing market value. Data from 307 horses sold at public auctions (2022–2023) were analysed using regression analysis, binary optimisation, and Principal Component Analysis (PCA). Regression identified Head–neck Connection, Quality of Legs, Walk length of Stride, and Scope as highly significant predictors of sales price (<i>p</i> < 0.001), with Length of Croup, Trot Elasticity, Trot Balance, and Take-off Direction also significant (<i>p</i> < 0.05). Optimised regression reduced the number of relevant traits from 37 to 8, streamlining evaluation. PCA highlighted eight principal traits, including Scope, Elasticity, and Canter Impulsion, explaining 61.19% of variance in the first four components. These results demonstrate that specific conformation, movement, and athleticism traits significantly affect auction outcomes. The findings provide actionable insights for breeders and stakeholders, suggesting that targeted selection for high-impact traits could accelerate genetic progress and improve market returns. Furthermore, these traits could underpin the development of economic or buyer indices to enhance valuation accuracy and transparency, with potential application across equestrian disciplines to align breeding objectives with market demands. |
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| ISSN: | 2076-2615 |