Estimating total-tract digestibility of nutrients and their contribution to digestible energy supplies in equine diets.
Authors: Webster A P, Price T P, Ingersoll T, Suagee-Bedore J K, White R R
Journal: Journal of equine veterinary science
Summary
# Editorial Summary Accurately predicting digestible energy (DE) supply is fundamental to equine nutrition, yet current estimation methods often fail to account for how individual feed components and dietary composition interact to affect nutrient availability. Webster and colleagues synthesized data from 54 published studies using statistical modelling to develop predictive equations for the apparent total-tract digestibility of seven nutrient fractions (dry matter, crude protein, neutral detergent fibre, ether extract, non-structural carbohydrates, non-fibre carbohydrates, and residual organic matter), incorporating variables such as dry matter intake, feed composition, and forage-to-concentrate ratios. The resulting models demonstrated strong predictive accuracy, with concordance correlation coefficients ranging from 0.740 to 0.969—particularly robust for non-structural carbohydrate digestibility (0.969) and crude protein digestibility (0.886)—and these nutrient-specific estimates were subsequently used to calculate total DE content and validated against measured values from an additional 17 independent studies. Rather than relying on fixed energy values, practitioners can now use these models to account for how forage quality, starch content, oil inclusion, and individual horse intake patterns influence the actual energy yield from specific diets, offering a more nuanced approach to ration formulation for performance horses, veterans, and those with metabolic considerations. This tool bridges a significant gap between theoretical energy requirements and practical feeding reality, particularly valuable for nutritionists and veterinarians seeking to optimise performance or manage metabolic conditions without expensive calorimetry trials.
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Practical Takeaways
- •Use these models to more accurately predict digestible energy in custom equine diets by inputting feed composition and dry matter intake data, improving feed formulation precision
- •Non-structural carbohydrate digestibility is highly predictable, making it a reliable parameter for energy calculations in grain-based and supplemental feeding programs
- •The models account for variation across studies and feed types, making them more robust than single-source estimation methods for diverse management scenarios
Key Findings
- •Linear mixed-effect regression models explained variation in nutrient digestibility well, with concordance correlation coefficients ranging from 0.740 to 0.969 across different nutrients
- •Non-structural carbohydrate digestibility (NSCD) showed the strongest predictive performance (CCC: 0.969), while residual organic matter digestibility (rOMD) showed the lowest (CCC: 0.740)
- •Models incorporating dry matter intake, dietary composition, and feed type proportions successfully estimated digestible energy content comparable to existing DE estimation methods
- •The quantitative approach provides a practical tool for predicting energy supplies in equine diets based on feed composition and intake patterns