Application of Near Infrared Reflectance (NIR) spectroscopy to predict the moisture, protein, and fat content of beef for gourmet hamburger preparation

Abstract

Near Infrared Reflectance (NIR) spectroscopy provides a rapid, easy to use, and non-destructive alternative to the methods traditionally employed in the determination of the chemical composition of food stuff, since it does not require reagents, time consuming procedures based on manual labor, and can determine multiple parameters simultaneously. Therefore, the use of NIR spectroscopy was evaluated in the quantification of the moisture, fat, and crude protein content of raw bovine meat, in order to support the development for industrial use of an Azorean Protected Geographical Indication (PGI) beef hamburgers, with a target fat content of 20 g/100 g. Sixty-six meat samples were studied, including the carcass cut of neck, shin, brisket, chuck and blade, flanks (thin flank and forequarter flank), plate ribs, ribs and flanks, mixture of unspecified cuts (minced meat), and commercial hamburgers. The samples were chemically analyzed according to standard methods, for moisture (drying method), total fat (solvent extract), and crude protein content (micro-Kjeldahl method). It was observed that the samples had a high fat content heterogeneity. The spectra of all samples were collected (400–2500 nm) and a calibration was performed using partial least squares regression (PLS) and cross validation. Several spectral pre-treatment techniques were applied, including the standard normal variate (SNV). The best calibration for the chemical properties under evaluation showed coefficient of determination (R2) and standard error of cross validation (SECV) values of 0.93 and 1.25%, respectively, for fat content, 0.89 and 0.99% for crude protein, and 0.72 and 2.18% for moisture. It was concluded that the use of NIR spectroscopy provides a good estimate of the fat and protein content of raw bovine meat.