Detection of adulteration in ghee (Clarified butter fat) using electronic nose combined with multivariate analysis
Author(s):
Mrinmoy Roy, Manoj D, S Shanmugasundaram and BK Yadav
Abstract:
Ghee is rich in aroma characteristics, nutrition and the unique mouth feel plays a major role in cooking and human dishes. It is prone to adulteration with low cost substitute material of same nature by manufacturers to earn more money. The available adulteration detection methods of pure ghee were costly and time-consuming processes. Therefore, the use of an electronic nose (e-nose) tool as a rapid method for the detection of pure ghee adulteration with soybean oil has been investigated in this study with six different adulteration concentrations from 10 to 60% (w/w). The e-nose system consists of eight metal oxide semiconductor (MOS) gas sensors with different sensitivity and selectivity. The response signals of these sensors from e-nose analysis of all the pure and adulterated ghee samples were collected and thus subjected to multivariate analysis such as principal component analysis (PCA) and discriminant function analysis (DFA). The discrimination results for calibration set by PCA and DFA model was found to be 95.33% and 94.54%, respectively. The validation accuracy of e-nose system for unknown samples obtained from DFA model was found to be 87.50%. The results demonstrated that e-nose tool might be used as a rapid screening technique for the detection of adulteration in ghee.
How to cite this article:
Mrinmoy Roy, Manoj D, S Shanmugasundaram, BK Yadav. Detection of adulteration in ghee (Clarified butter fat) using electronic nose combined with multivariate analysis. Pharma Innovation 2021;10(9):36-43.