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Cattell, R. B., & Korth, B. (1973). The isolation of temperament dimensions in dogs. Behav Biol, 9(1), 15–30.
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Henneke, D. R., Potter, G. D., Kreider, J. L., & Yeates, B. F. (1983). Relationship between condition score, physical measurements and body fat percentage in mares. Equine Vet J, 15(4), 371–372.
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Carroll, C. L., & Huntington, P. J. (1988). Body condition scoring and weight estimation of horses. Equine Vet J, 20(1), 41–45.
Abstract: Three hundred and seventy two horses of varying breeds, height and fatness were weighed and measured for height at the withers. They were assessed for condition score by adaptation of a previously published method. The heart girth and length of 281 of the horses were also measured. Weight of horses was highly correlated (P less than 0.001) with height (r2 = 0.62), condition score (r2 = 0.22) and girth2 x length (r2 = 0.90). Nomograms were constructed to predict weight from height and condition score, and girth and length measurements. Weight can also be accurately estimated from the formula: (formula, see text) The average value of 'Y' in this experiment was 11900 and this estimated weight with more accuracy than some previously published values of 'Y'. Racing Thoroughbred horses were found to be significantly lighter than non-racing Thoroughbreds of the same height and condition score. The method of assessment of condition score was shown to be repeatable between different operators with varying degrees of experience.
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Staniar, W. B., Kronfeld, D. S., Hoffman, R. M., Wilson, J. A., & Harris, P. A. (2004). Weight prediction from linear measures of growing Thoroughbreds. Equine Vet J, 36(2), 149–154.
Abstract: REASON FOR PERFORMING STUDY: Monitoring weight of foals is a useful management practice to aid in maximising athletic potential while minimising risks associated with deviations from normal growth. OBJECTIVE: To develop predictive equations for weight, based on linear measurements of growing Thoroughbreds (TBs). METHODS: Morphometric equations predicting weight from measurements of the trunk and legs were developed from data of 153 foals. The accuracy, precision and bias of the best fitting equation were compared to published equations using a naive data set of 22 foals. RESULTS: Accuracy and precision were maximised with a broken line relating calculated volumes (V(t + l)) to measured weights. Use of the broken line is a 2 step process. V(t + l) is calculated from linear measures (m) of girth (G), carpus circumference (C), and length of body (B) and left forelimb (F). V(t + I) = ([G2 x B] + 4[C2 x F]) 4pi. If V(t + l) < 0.27 m3, weight is estimated: Weight (kg) = V(t + l) x 1093. If V(t + l) > or = 0.27 m3: Weight (kg) = V(t + l) x 984 + 24. The broken line was more accurate and precise than 3 published equations predicting the weight of young TBs. CONCLUSIONS: Estimation of weight using morphometric equations requires attention to temporal changes in body shape and density; hence, a broken line is needed. Including calculated leg volume in the broken line model is another contributing factor to improvement in predictive capability. POTENTIAL RELEVANCE: The broken line maximises its value to equine professionals through its accuracy, precision and convenience.
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