Research progress on the artificial intelligence applications in food safety and quality management

Abstract

Background

The maintenance of food safety standards is crucial for protecting public health and the economic integrity of the food industry. Artificial Intelligence (AI) is a groundbreaking tool with great potential in the field of food safety. However, its practical applications still require further exploration to fully unlock its benefits.

Scope and approach

This review synthesizes the applications of AI in food safety, focusing on microbial detection, contamination prediction, and traceability within the food supply chain. Additionally, the review discusses AI applications in food safety regulation, including risk assessment, predictive modeling, and decision support systems.

Key findings and conclusions

The integration of AI technologies into food safety practices not only enhances traditional methods of risk management but also fosters a more proactive approach to identifying and mitigating potential hazards. By leveraging AI capabilities, the food industry can significantly improve safety outcomes, reduce operational inefficiencies, and bolster consumer trust. The continued evolution of AI in this domain promises to drive innovative solutions, paving the way for smarter, more resilient food safety systems that prioritize prevention and proactive management.