Leveraging Blockchain and AI for Biofilm Control in Food Processing Environments

Abstract

Biofilm formation in food processing environments significantly threatens food safety and quality due to its resistance to conventional cleaning and disinfection methods. These resilient microbial communities contribute to contamination, spoilage and foodborne illnesses, highlighting the need for innovative and technology-driven control strategies. Emerging digital tools, particularly blockchain technology and artificial intelligence (AI), offer new opportunities for enhancing biofilm management. Blockchain ensures secure, real-time traceability of hygiene records, contamination events and compliance activities across the supply chain. Complementing this, AI technologies such as machine learning and sensor-based analytics support early detection of microbial growth, anomaly identification and predictive risk assessment. Together, these tools promote data-driven decision-making and more proactive contamination prevention. While pilot applications show promise in improving transparency and sanitation outcomes, challenges remain, including data integration, implementation costs and regulatory barriers. Addressing these issues will require interdisciplinary collaboration and supportive policy frameworks. This review summarizes the current and potential roles of blockchain and AI in biofilm control and outlines future directions for research and industrial application.