Artificial intelligence for food safety: From predictive models to real-world safeguards

Food safety is no longer just a lab issue; it’s a real-world challenge that affects everyone from farmers and vendors to regulators and consumers. With rising concerns about adulteration, spoilage, and contamination in everyday items like milk, oils, fruits, and ready-to-eat meals, traditional testing methods often fall short; they’re too slow, too expensive, and not designed for real-time action. This review explores how artificial intelligence (AI) and machine learning (ML) are stepping in as game-changers. We highlight real case studies where AI models, combined with tools like spectroscopy, smart sensors, and computer vision, are detecting food fraud and spoilage quickly and accurately. Beyond the…