Application of electronic nose with chemometrics methods to the detection of juices fraud

Abstract

Today, consumer demands for fresh foods with desirable sensory properties are increasing. Lack of easy, cheap, and nondestructive methods to control the quality of fruit juices is one of the main challenges in the beverage industry. The present study has examined two types of natural and industrial juices. Machine olfaction with 9-metal oxide semiconductor (MOS) sensors was used for the experiments. Sensor response patterns were analyzed using chemometrics methods, including principal component analysis (PCA), linear and quadratic discriminant analyses (LDA and QDA), and support vector machine (SVM). According to the results, the classification accuracy of SVM, QDA, and LDA methods was 96.25%, 95.8%, and 94.4%, respectively. Practical applications It is important to note that most fruit juices sold in supermarkets contain only a small percentage of natural fruit juice and usually include added sweeteners. As a result, these juices lead to the intake of large amounts of calories without providing nutrients for the body. In addition, performing chemical tests to determine the quality of fruit juices are time-consuming, destructive, and costly and requires several glassware and reagents. E-nose could be used for real-time monitoring of the volatile components of the food to evaluate different features of the product. Generally, E-nose evaluates a mixture of smells released from a sample and is a reliable, nondestructive, cost-effective, and portable method with high feasibility and speed as well as simple use.