The application of artificial intelligence in food fraud and adulteration analysis: a review

Food fraud represents a critical challenge to global food safety and economic integrity, costing the industry an estimated $10-40 billion annually. Traditional analytical methods, while effective, are often time-consuming and resource intensive. Artificial intelligence and machine learning technologies are revolutionising food authentication by offering unprecedented capabilities in detecting, predicting, and preventing fraudulent practices. This review examines the integration of artificial intelligence with analytical techniques, explores current applications across the food supply chain, discusses challenges in implementation, and identifies future directions for intelligent food fraud detection systems.