A novel technique for detection of vanaspati ( hydrogenated fat ) in cow ghee ( clarified butter fat ) using flash gas chromatography electronic nose combined with chemometrics

Abstract

This study aimed to detect various proportions of vanaspati mixed with cow ghee using an electronic nose (e-nose) based on fast gas chromatography. The e-nose apparatus was equipped with a non-polar and medium polar column used to generate two chromatograms simultaneously along with the volatile compound information. Further investigation on the adulteration detection in ghee was carried out using chemometric analysis such as principal component analysis (PCA), discriminant function analysis (DFA), and soft-independent modeling of class analogy (SIMCA). An outstanding differentiation among all the samples was obtained using PCA and DFA with 99.85% and 99.83% classification accuracy in the e-nose dataset. SIMCA presented a validation score of 76, indicating SIMCA could also be a potential method to detect higher levels of adulteration in ghee. The validation study shows good agreement between FGCEN and GC–MS methods. Practical applications Cow ghee is frequently adulterated with vanaspati, due to its high market demand. The existing methods for adulteration detection are time-consuming, and require tedious sample preparation and expertise in these fields. The e-nose based on fast GC combined with chemometric analysis turned out to be a reliable and promising technique for various proportions of adulteration detection in pure cow ghee. The technique was efficient enough to get the volatile compound information from the samples in a fast-performing way. The chemometrics used has shown to be effective to confirm adulterations in ghee.