Enhancing food authentication through E-nose and E-tongue technologies: Current trends and future directions

Abstract

Background: Food adulteration became a potential threat to the food industries and human health. The conventional laboratory techniques are time and cost intensive, require sample preparation, and require skilled persons. The application of E-nose and E-tongue in association with suitable chemometrics techniques became more popular in food sector for food authentication due to their rapid and non-destructive nature. Scope and approach: This review covered historical evaluation and various types of sensors used for the system development of E-nose and E-tongue, the individual and fusion techqniques employed for food authentication. The strength and weakness of various machine learning techniques, steps to enhance detection of food adulteration, limitations, challenges and future trends of the E-nose and E-tongue system. Key findings and conclusion: The individual application of E-nose and E-tongue systems has limitations such as sensor drift, lack of standardization and complexities in data interpretation. These can overcome by fusion approach. The future prospects for using E-nose and E-tongue for food authentication are encouraging. As a result, further improvements in sensor technology together with breakthroughs in data analytics and ML will help to overcome present hurdles and open up new doors for improved food quality control as well as better consumer protection.