Data Fusion Approaches for Nondestructive Quality Evaluation of Food and Beverages

The increasing interest of customers in the safety, authenticity and quality of food products has caused more attention to be paid to the nondestructive methods used to check them. In recent years, fast and reliable sensing and spectroscopic, together with multivariate and multipath chemometrics, have improved the entire control process by reducing analysis time and providing more informative results. As more and better data become available, combining the outputs of different instrumental methods has emerged as a way to increase the reliability of nondestructive food classification or prediction compared to using a single analytical method. While promising results have been obtained in the authentication and quality assessment of food and beverages, the integration of data from multiple techniques poses a significant challenge for chemometrics. This paper provides a general overview of data integration techniques that have been used in the field of food and beverage authentication and quality assessment.

Data Fusion Approaches for Nondestructive Quality Evaluation of Food and Beverages Keywords:

Beverages , Food , Data Fusion , Quality , Nondestructive