Predicting degradability parameters of diets for ruminants using regressions on chemical components

BACKGROUND: Dry matter degradability (DMD) parameters (a, b and c in the Ørskov and McDonald model) are usually determined by the nylon bag technique. The aim of this study was to estimate DMD parameters of ruminant mixed diets, which are in general unavailable, through multiple linear regressions on their chemical composition (ash, crude protein, neutral detergent fibre (NDF), acid detergent fibre (ADF) and acid detergent lignin (ADL)). The regressions were based on data from 77 feeds. RESULTS: The prediction model for a was reduced to a simple linear regression on NDF (adjusted R(2) = 0.727, F test P < 0.001). A regression model for b was obtained with ADL as the sole predictor (adjusted R(2) = 0.691, P < 0.001). The model's upper asymptote (a + b) was predicted from ADL, NDF and ash (adjusted R(2) = 0.908, P < 0.001). Modelling c proved more difficult (adjusted R(2) with all five predictors = 0.481, P < 0.001). CONCLUSION: Regressing model parameters on feed chemical composition is a promising method for estimating the degradability of mixed diets, providing an alternative to invasive and expensive laboratory techniques.