Nutritive evaluation and ingredient prediction of compound feeds for rabbits by near-infrared reflectance spectroscopy (NIRS)

Near-infrared reflectance spectroscopy (MRS) was used to predict the nutrit ive characteristics of 66 compound rabbit feeds from three countries (Belgi um, Spain and Italy) and the main ingredient inclusion rate in 59 of these feeds of known ingredient composition. Principal component analysis (PCA) w as performed to classify the compound feeds according to their origin. The coefficient of multiple determination (R-2) for crude protein concentra tion (CP) was ca. 0.88 in both, calibration and validation with standard er rors of calibration (SEC) and prediction (SEP) equal to 7.5 and 7.7 g (kg D M)(-1), respectively. NIRS prediction of gross energy (GE) and digestible e nergy (DE) concentrations was more precise, with high R-2 (0.90) and low SE P (0.26 and 0.37 MJ (kg DM)(-1), respectively). Satisfactory results were a lso obtained for both, the dry matter digestibility (DMd) and gross energy digestibility (GEd) prediction. The CP-correlated wavelengths were observed to be associated with the bond vibrations of the protein functional groups , while the wavelengths correlated with GE, DE, DMd and GEd were linked wit h starch, protein and crude fiber structure. The calibration on absorbance data to estimate the inclusion rate of the ma in ingredients demonstrated a fair correlation for alfalfa meal, barley and wheat bran, intermediate for sunflower meal and weak for soybean meal. In validation, the precision of the NIRS estimate remained satisfactory for al falfa and sunflower meal but decreased for barley and wheat bran. The calib ration of the spectra transformed in second derivative appeared to improve the quality of estimation by reducing the number of optimal factors from 9- 15 to 2-4; moreover, the estimate precision of soybean and sunflower meal i nclusions improved (R-2: 0.90 and 0.86, respectively) with the reduction of SEC (13.0 and 12.9 g kg(-1), respectively). In validation, however, the es timate precision for all raw materials became weaker than the degree achiev ed using absorbance data. PCA on the transformed spectra grouped the compound rabbit feeds according to their country of origin and indicated the possibility of identifying the presence of specific ingredients (i.e. full-fat rapeseed). (C) 1999 Elsevi er Science B.V. All rights reserved.