Prediction of digestible energy content across feed ingredients and fish species by linear regression

In an attempt to develop predictive relationships, apparent digestible energy (ADE) content (n = 361) as biological dependent variable and dietary contents of crude protein (CP), lipid, ash and gross energy (GE) as independent variables, obtained in 40 studies with 65 different feed ingredients and evaluated with 26 fish species, were subjected to linear correlation and multiple linear regression analysis. With dietary CP and GE contents identified as significant predictors, only 58% of the variation in ADE content could be explained. No improvement in accuracy of regression equations was gained by classification of values according to either feed ingredient (animal proteins, plant proteins, cereals) or fish species (water type, water temperature, feed habit). An R (2)-value of 0.4570 and mean prediction error (MPE) of 0.2085 between predicted and observed ADE values from eight independent studies (n = 37) illustrated the inability of the derived regression equation to accurately predict ADE contents of feed ingredients. Inclusion of dietary crude fibre and nitrogen-free extract (NFE) contents as independent variables did not improve the accuracy of prediction equations. The inadequacy of the use of linear regression to predict DE content from dietary composition across feed ingredients and fish species with high accuracy is discussed.