Application of electronic nose for detecting fraud in lemon juice with the help of multivariate analysis techniques

Foodstuff adulteration involves replacing expensive ingredients with low-cost substances to decrease the production cost and reach the maximum profit. In recent years, the issue of food adulteration has reached an alarming stage. The detection methods currently available for this problem are often costly, time-consuming, and require high technical expertise. Lemon juice has repeatedly been the victim of fraud attempts by manufacturers to lower the price of products. Electronic noses are used in many fields, including the beverage industry, for classification and quality control. The process involves detecting and differentiating volatile organic compounds (VOCs) released from food. This study used an electronic nose equipped with 8 metal oxide sensors to evaluate pure lemon juice and 11 counterfeit samples (water, lemon pulp, and wheat straw) to detect fraud through VOC analysis. The response patterns of the sensors were analyzed using chemometric methods, specifically Quadratic Discriminant Analysis (QDA) and Mixture Discriminant Analysis (MDA). According to the results obtained from the QDA and MDA methods, the total variance was 100% and 98.89%, respectively, for the classification of samples. Hence, it can be concluded that the electronic nose based on metal oxide semiconductor sensors combined with chemometric methods can be an effective tool with high efficiency for rapid and non-destructive classification of pure lemon juice and its counterfeits.