Advanced biosensing strategies for high-risk foodborne pathogens: a comprehensive review of Salmonella and Listeria monocytogenes

The goal of this review is to comprehensively analyse advances in biosensors specifically for Listeria monocytogenes and Salmonella spp., two of the leading causes of foodborne illness and mortality worldwide. Unlike previous reviews that broadly survey bioreceptors or transducer classes across many pathogens, this work provides a focused, pathogen-specific comparison, mapping current trends in bioreceptor development and transducer choices uniquely for these two high-priority pathogens. Additionally, while artificial intelligence (AI) applications in biosensing have been reviewed before, this article is the first to examine how AI-driven tools can directly accelerate biosensor design, optimisation, and decision-making for Listeria and Salmonella detection. Importantly, this review bridges the persistent gap between laboratory concepts and real-world implementation by critically evaluating which biosensing strategies have genuine potential for scalability, portability, and routine use in the food industry. Together, these elements position the review as a practical roadmap for steering future biosensor research toward field-ready, industry-relevant solutions. • Biosensor technology has strong potential to advance bacterial detection in food. • Widely used bioreceptors in biosensors are discussed with their pros and cons. • Potential of electrochemical, optical and piezoelectric devices are discussed. • Bioreceptors, transducer engineering, and AI-assisted optimisation are keys to advance biosensors for food born pathogens.