Emerging Technologies for Viability Assessment of Foodborne Pathogens: From Molecular Dyes to Artificial Intelligence.

Abstract

To critically examine emerging technologies for assessing foodborne-pathogen viability and to evaluate their relevance for improving food safety monitoring and public-health risk assessment. This review examines the literature on viability-detection using biological indicators such as membrane integrity, infectivity, and virulence. It addresses technologies such as viability dye-based PCR, RNA and CRISPR detection methods, biosensors, bacteriophage assays, Raman spectroscopy, and AI-supported analysis. Compared to conventional culture-based and DNA-only molecular methods, viability-focused techniques support more biologically meaningful detection, particularly for viable but non-culturable (VBNC) cells that may retain pathogenic potential. However, assay performance varies depending on food-matrix complexity, the presence of inhibitors, sensitivity limitations, and the degree of validation. Integrated systems combining multi-modal sensing, microfluidics, and machine learning have shown increasing promise for rapid on-site application, although standardization and regulatory validation remain limited. The emerging viability-focused technologies substantially refine microbial-risk assessment by accurately capturing the infectious potential of foodborne pathogens, including traditionally undetected VBNC populations. Nevertheless, integrating these technologies into routine surveillance remains constrained by matrix interference and the absence of standardized protocols. Future efforts must prioritize developing matrix-resilient methodologies and establishing regulatory validation frameworks to facilitate their practical implementation in food safety management.

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