Information fusion of emerging non-destructive analytical techniques for food quality authentication: A survey

Authentication of food quality is a global concern. In recent years, multiple-level information fusion technologies have been widely studied and applied to make further improvement for food pattern recognition and property parameters estimation. Information from different sources can help the decision system better understand the internal and external states of food samples. This review surveys the applications of information fusion in food quality authentication, especially concerning that for meat, fruits, vegetables, medicinal foods, mushrooms, beverages, and edible vegetal oils. We introduce briefly the sensing technologies for the information acquisition and further summarize in detail of the research objective, observation tools, data processing algorithms, fusion strategies as well as the comparison between fusion and non-fusion methods. This survey provides clear evidence of the superiority of fusion-based methods for food authentications. Furthermore, we bring some trends of information fusion approaches into attention and discuss the challenges and future perspectives with recommendations. © 2020 Elsevier B.V.