Abstract

Food adulteration is a widespread illegitimate procedure involving contamination of food with chemical and physical substances. The adulterated food products are not only of decreased quality but also may cause pathogenic effects that jeopardize the human health. Adulteration of liquid foods is majorly performed for economic gains by utilizing cheap adulterants which do not necessarily change the color, taste and appearance of the food to be easily detectable by human senses. In the present study, two different dielectric spectroscopy sensors (parallel plate capacitor (PPC) and cylindrical stub resonator (CSR)) were examined and compared for detection of adulteration in grape syrup. The aim was to address which sensor could be a more precise instrument for detecting the type and level of a variety of common adulterants in grape syrup. The different adulterants tested were the date syrup, grape paste and sugar-water solution mixed at 5, 10, 15, 20, 25 and 30% with pure grape syrup. The multivariate dielectric spectral data were visualized with principal component analysis (PCA). Furthermore, similarity between different adulterants and their levels was identified with the hierarchal cluster analysis (HCA). To perform classification analysis, two different classification techniques i.e., linear discriminant analysis (LDA) and multi-class support vector machines (SVM) were utilized and compared. The results showed that PCA provided clear visualization identifying different types of adulterants over the score plots. Classification of adulteration type using SVM and LDA resulted in 100% accuracy for either of the sensors. For classifying the level of adulteration, PPC sensor associated with SVM classifier resulted in the highest accuracy (100%). In conclusion, the adulteration detection in grape syrup was satisfactorily addressed by the dielectric spectroscopy techniques. As diagnosistic tools, both the instruments could be implemented with standards executed for food security assessments.

Full Text
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