Enhancing Food Safety and Quality Assurance through Artificial Intelligence

Artificial intelligence (AI) is increasingly employed to enhance food safety and quality assurance in food industry. AI tools, including predictive analytics, automated inspection, and real-time monitoring, significantly improve the identification, prevention, and management of food-related risks. Food safety is particularly critical in perishable items like poultry, dairy, fruits, vegetables, and stored products such as cereals, pulses, and oilseeds throughout the supply chain to prevent disease outbreaks. Traditional methods of food inspection are often time-consuming and prone to human error, while AI-based systems automate inspection processes, analyzing images or sensor data to detect defects or contaminants more accurately and efficiently. For instance, computer vision algorithms identify foreign objects or physical defects, while spectroscopic techniques analyze food sample compositions. Predictive analytics, a vital AI application, uses machine learning algorithms to forecast potential foodborne illnesses or quality issues by analyzing extensive datasets. This chapter aims to offer an in-depth analysis of AI&s;s critical role in the food safety. It explores how technologies like deep learning, machine learning, and artificial neural networks are utilized in different food products to maintain a smooth supply chain. Also, underscores AI&s;s critical role in enhancing food safety and quality, discusses its benefits, and outlines future prospects.