NIRs calibration models for chemical composition and fatty acid families of raw and freeze-dried beef: a comparison

Abstract The aim of this study was to develop near-infrared reflectance spectroscopy (NIRS) calibrations for estimation of chemical components (protein, fat, ash and moisture) and the principal fatty acid (FA) groups (SFA, MUFA, PUFA, n−3, n−6) in beef meat. Beef samples (n = 207) of three different muscles (Longissimus dorsi, Rectus abdominis and Semitendinosus) were used for the study. The calibration models were performed both on raw and freeze-dried (FD) meat. Raw meat predictions for protein, fat and ash were performed, using reference values expressed as percentage on dry-matter (DM) or fresh-minced (FM) weights. In addition, FD meat predictions for the same chemical components were developed. FA predictive models were based on the relative composition of FA (weight percent of total FA). The predictability of calibrations based on FD meat was higher than that of models based on raw samples, except for n−3. Regarding the raw meat, the calibration models obtained from reference values expressed on DM basis were better than those obtained from data expressed on FM basis. In addition, because of the low coefficients of determination of prediction (R2p) and the low RPD obtained, NIRS models of FA families are not useful for a quantitative fatty acid analysis.