A rapid detection method of three foodborne pathogens based on physical and chemical Raman spectroscopy enhanced

Abstract

Escherichia coli, Listeria monocytogenes, and Salmonella typhi are three pathogens commonly found in food. Label-free enhanced substrates have limitations in achieving high sensitivity in three bacteria detection. To enable low-concentration detection and differentiation of foodborne pathogens, this research presents an optimized detection strategy using Au @Ag NPs as the enhancing substrate for SERS technology. The impact of the particle size of Au @Ag NPs and the pH of the borate buffer solution on enhancing the Raman signals of these bacteria was investigated through electromagnetic and chemical enhancement mechanisms. By evaluating the intensity of bacterial Raman spectra, and employing chemometric techniques, the concentration and classification of the three bacterial species were predicted and analyzed. The research findings revealed that the optimized detection method was able to detect three pathogens at the concentration lower than 3 lg CFU/mL. Logarithmic fitting of the bacteria enabled prediction correlations above 0.98 and prediction root mean square errors below 0.17. After normalizing, efficient discrimination of low-concentration bacteria was achieved using the PLS-DA, with a classification prediction correlation greater than 0.94. The fabrication process of the proposed enhancement substrate is simple, but the stability of signal detection needs further improvement in subsequent experimental testing steps.