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Maintaining optimal body condition is an important concern for horse owners and managers as it can affect reproductive efficiency, athletic ability, and overall health of the horse; however, information regarding dietary requirements to maintain or alter BCS in the horse is limited. A recently developed model had high accuracy in predicting the energy required to alter BCS in the horse. However, the model was restricted to sedentary mares, while many horses are subject to physical work. The objective of this study was to expand the scope of that model to include exercising horses by incorporating previously published estimates of exercise energy expenditure and then testing the expanded model. Stock type horses (n = 24) were grouped by initial BCS (3.0 to 6.5) and assigned to treatments of light (L), heavy (H), or no-exercise control (C). Horses were fed according to the model recommendations to increase (I) or decrease (D) two BCS within 60 d. Thus, six treatments were obtained: HD, HI, LD, LI, CD, CI. Mean DE intake Mcal/d for each group was HD = 19.3 ± 0.90, HI = 29 ± 0.84, LD = 13.2 ± 0.54, LI = 23.1 ± 1.39, CD = 12.1 ± 0.79, and CI = 21.9 ± 0.94. BCSs were evaluated by three independent appraisers, days 0 and 60 values were used to calculate the average BCS change for HD = -0.88 ± 0.24, HI = 1.13 ± 0.24, LD = -1.5 ± 0.29, LI = 0.88 ± 0.38, CD = -1.38 ± 0.13, and CI = 1.35 ± 0.14. Statistical comparison of final observed and model predicted values revealed acceptable precision when predicting BCS and BW respectively in control horses (r2 = 0.91, 0.98) but less precision when predicting body fat (BF) (r2 = 0.51). Model precision for BCS, BW, and BF respectively in lightly (r2 = 0.29, 0.85, 0.57) and heavily (r2 = 0.04, 0.84, 0.13) exercised horses was low. Model accuracy was acceptable across all treatments when predicting BW (Cb = 0.97, 0.96, 0.98). However, accuracy varied when predicting BCS (Cb = 0.82, 0.89, 0.41) and BF (Cb = 0.80, 0.55, 0.87) for the control, light, and heavy exercise groups, respectively. These results indicate that the revised model is acceptable for sedentary horses but the predictability of the model was insensitive to the exercising horse, therefore the exercise energy expenditure formulas incorporated into the model require revision. Packaging this model in a format that facilitates industry application could lead to more efficient feeding practices of sedentary horses, generating health, and economic benefit. Further investigation into energy expenditure of exercising horses could yield a model with broader applications.

Development of a mathematical model for predicting digestible energy intake to meet desired body condition parameters in exercising horses