PREDICTING AUTHENTICITY AND PHYSICOCHEMICAL CHARACTERISTICS OF MEAT THROUGH FT-IR SPECTROSCOPY COUPLED WITH MULTIVARIATE ANALYSIS

Major issues related to meat in our modern society are its authenticity and traceability. Meat consumers are facing problems related to addition of low value meat to high quality meat. The current study was designed to explore the potential of analytical method for the rapid detection and identification of meat. Meat of four species (beef, pork, chicken and turkey) were collected for the chemical (moisture content, ash content, crude fat and crude protein), quality (pH, color and drip loss) and spectral analysis through Fourier transform infrared spectroscopy (FT-IR). Pork meat showed highest crude protein (22.20%) and crude fat contents (5.85%). Highest pH (6.14) and drip loss (1.84%) was seen in turkey meat and pork meat, respectively. Spectral data collected from FT-IR spectroscopy was analyzed through principle component analysis and partial least square regression model. The FT-IR spectra obtained after absorption in infrared region explained that all the meat samples were different based on their OH, CH and CH2 stretching in bonds. The near infrared region around 2300-1400 cm -1 had maximum spectral information required for the discriminant investigations based on the pigments contained in different species of meat to the physicochemical characteristics (moisture, intramuscular fats and fatty acids). Coefficients of determination for calibration ((RC)-C-2) and validation ((RV)-V-2), root mean square errors of calibration (RMSEC) and root mean square error of prediction (RMSEP) for moisture, crude protein, crude fat, ash, pH, drip loss and color L*, a*, b* of different meat samples were measured. The color value b* developed strong prediction with (RC)-C-2 = 0.941 and (RV)-V-2= 0.872.