Advancements in food authentication using soft independent modelling of class analogy (SIMCA): a review

Food authentication verifies the match between product characteristics and claims and it is crucial in a globalized and complex food sector. Class modelling approaches, like Soft Independent Modelling of Class Analogy (SIMCA), are powerful tools at disposal nowadays to assess food authenticity. The aim of this review is then to discuss the application of SIMCA for food authentication, also describing the conceptual differences between discriminant and class modelling approaches. The discussion of research articles is organized around three elements: i) the research objectives, ii) the analytical methodologies, and iii) the food products investigated. Moreover, the challenges and future perspectives considering the development of innovative food products will be discussed. Adulteration is the most investigated food authentication issue, followed by the verification of geographical origin. Food authenticity appeared to be predominantly evaluated using non-destructive spectroscopy. Overall, the articles collectively cover a broad spectrum of food categories, representing those most prone to adulteration. However, a notable lack of food authentication studies in innovative food product was evident, underscoring the urgency for further research in this field.