Cold Atmospheric Plasma-Assisted Deposition of SiOx-Ag Nanocomposites for SERS-Based Detection of Listeria monocytogenes in Complex Food Matrices

冷大气等离子体辅助沉积SiOx-Ag纳米复合材料用于基于SERS的复杂食品基质中单核细胞增生李斯特菌检测

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Abstract

Foodborne pathogens remain a persistent global threat, posing serious health and economic challenges across increasingly complex food supply chains. Among them, Listeria monocytogenes (L. monocytogenes) is particularly concerning due to its high mortality rate and ability to survive in cold-chain environments, prompting strict zero-tolerance regulations for ready-to-eat foods. While current diagnostics such as microbial culture and PCR offer high accuracy, they are limited by long turnaround times and dependence on centralized laboratory infrastructure, making them unsuitable for rapid, on-site contamination control. In this work, we present a cold atmospheric plasma (CAP)-engineered SiO(x)-Ag nanocomposite coating as a robust substrate for surface-enhanced Raman scattering (SERS)-based detection of L. monocytogenes. The CAP process enables ambient, in situ fabrication of Ag nanoparticles encapsulated within a SiO(x) matrix, ensuring long-term plasmonic stability and high batch-to-batch reproducibility. Structural and compositional analyses confirmed homogeneous nanoparticle dispersion and effective matrix integration. Upon immuno-functionalization with a Raman reporter and L. monocytogenes-specific antibodies, the platform exhibited high selectivity and achieved a sensitivity of 3771.5 a.u./log(CFU/mL) with a detection limit of ~1.89 CFU/mL. Sensor stability was maintained over 60 days under nitrogen-purged storage and 30 days under ambient conditions, with less than ±5% variation in performance. As a proof of concept, the sensor demonstrated quantitative recoveries of ~101% ± 6.3% when applied to artificially contaminated cheese, lettuce, and meat samples, confirming compatibility with complex food matrices. These results establish the CAP-assisted SERS platform as a scalable, field-deployable, and reliable approach for real-time pathogen monitoring at critical control points in modern food safety systems.

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