Detection and quantification of food colorant adulteration in saffron sample using chemometric analysis of FT-IR spectra

The aim of present study is to investigate the combination of Fourier transform infrared (FT-IR) spectroscopy with pattern recognition to recognize the standard saffron from those which have been adulterated with various types of food colorants. Transmittance FT-IR spectra have been obtained for standard saffron and six mixed samples with food colorants including Tartrazine, Sunset yellow, Azorubine, Quinoline-yellow, Allura red and Sudan II. Genetic algorithm-linear discriminant analysis (GA-LDA) based on the concept of clustering of variables has been applied to transmittance FT-IR spectra for classification of standard saffron from fraudulent samples. Analysis of the selected clusters of variables indicates that three bands corresponding to 1800-1830, 2600-2900 and 3700-3850 cm −1 are responsible for differentiation of standard samples from fraudulent ones. Regression analysis has been introduced in order to obtain information related to the amount of food colorant. A combination of FT-IR and the concept of clustering of variables resulted in the best performances for calibration and an external test set with 100% sensitivity and specificity. The aim of present study is to investigate the combination of Fourier transform infrared spectroscopy with pattern recognition to recognize the standard saffron from those which have been adulterated with various types of food colorants.