Prediction of chemical composition, nutritive value and ingredient composition of European compound feeds for rabbits by near infrared reflectance spectroscopy (NIRS)

Abstract

Near infrared reflectance spectroscopy (NIRS) was used to predict the chemical constituents, digestibility and energy value of 164 experimental compound feeds for rabbits using harmonised methods in six European institutes. NIRS equations were developed by partial least square regression (PLSR) using two-thirds of the samples as a calibration set and the remaining samples as a validation set. Prediction was satisfactory for the following characteristics: dry matter (coefficient of determination in validation, R v 2=0.70; standard error of prediction, SEP=4.8 g kg −1), crude protein ( R v 2=0.86; SEP=5.6 g kg −1 DM), ether extract ( R v 2=0.93; SEP=4.2 g kg −1 DM), ADF ( R v 2=0.82; SEP=14 g kg −1 DM), starch ( R v 2=0.90; SEP=16 g kg −1 DM), DM digestibility ( R v 2=0.79; SEP=0.019), gross energy digestibility ( R v 2=0.81; SEP=0.019) and digestible energy ( R v 2=0.77; SEP=0.39 MJ kg −1 DM). NIRS prediction was less accurate for crude fibre ( R v 2=0.60; SEP=16 g kg −1 DM), NDF ( R v 2=0.50; SEP=32 g kg −1 DM), gross energy ( R v 2=0.57; SEP=0.25 MJ kg −1 DM), while poor results were obtained for organic matter ( R v 2=0.25; SEP=8.6 g kg −1 DM), ADL ( R v 2=0.59; SEP=11 g kg −1 DM) and crude protein digestibility ( R v 2=0.44; SEP=0.026). The prediction of the inclusion rate of the main ingredients provided approximate indications on the feed formula. In particular, the prediction was good for the inclusion level of added fat ( R v 2=0.87), moderate for alfalfa meal (0.73), dried beet pulp (0.69), sunflower meal (0.68), wheat bran (0.66) and whole soya bean (0.63), but was poor ( R v 2<0.50) for grains (barley, wheat) and wheat straw. Grouping similar ingredients (starch concentrates, protein concentrates, wheat by-products) slightly improved the prediction of the inclusion rate.