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

Abstract

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.