AI-Driven Farm-To-Fork Biofilm Detection and Control in Aquatic Foods: From Industry 4.0 to Industry 5.0.

Abstract

Aquatic foods are essential sources of protein and micronutrients and play a critical role in global nutrition, trade, and livelihoods. However, their safety and sustainability are frequently compromised by microbial contamination and biofilm formation during farming, processing, storage, and retail. Biofilms persist on moist surfaces, resist conventional cleaning practices, and contribute to spoilage, cross-contamination, and economic loss. This article reviews emerging applications of artificial intelligence and Industry 4.0 technologies for biofilm prevention and control in aquaculture and seafood systems. Particular emphasis is placed on the use of continuous water quality sensing, imaging platforms for early detection and cleaning verification, genomic and omics tools for microbial trait-level insight, and digital twin frameworks for virtual simulation of sanitation strategies. Recent advances demonstrate that sensor telemetry can predict biofilm-favorable conditions, imaging can verify removal in real time, and genomic data can identify persistence traits and tolerance mechanisms. When integrated, these approaches enable facility-specific digital twins that anticipate surface-specific risks and recommend optimized interventions before implementation. The convergence of AI, sensor networks, imaging, and omics offers a shift from reactive to proactive biofilm management in aquatic food systems. Positioned within the transition to Industry 5.0, these innovations support earlier detection, targeted interventions, and measurable improvements in food safety, quality, sustainability, and resilience, while aligning production systems with human-centric goals.