Biopolymer encapsulated silver nitrate nanoparticle substrates with surface-enhanced Raman spectroscopy (SERS) for Salmonella detection from chicken rinse

Salmonella is commonly found on broiler chickens during processing. This study investigates the Salmonella detection method that reduces the necessary time for confirmation, by collecting surface-enhanced Raman spectroscopy (SERS) spectra from bacteria colonies, applied to a substrate of biopolymer encapsulated AgNO3 nanoparticles. Chicken rinses containing Salmonella Typhimurium (ST) were analyzed by SERS and compared to traditional plating and PCR analyses. SERS spectra from confirmed ST and non -Salmonella colonies appear similar in spectra composition, but with different peak intensities. t-Test on the peak intensities showed that ST and non -Salmonella colonies were significantly different (alpha = 0.0045) at 5 peaks, 692 cm-1, 718 cm-1, 791 cm-1, 859 cm-1, and 1018 cm-1. A support vector machine (SVM) classification algorithm was able to separate ST and non -Salmonella samples with an overall classification accuracy of 96.7 %.

Automated summary

This study investigates a Salmonella detection method using surface-enhanced Raman spectroscopy (SERS) to reduce the time required for confirmation. Chicken rinses containing Salmonella Typhimurium (ST) were analyzed using SERS and compared to traditional plating and PCR analyses. The results show that the SERS method, combined with a support vector machine (SVM) classification algorithm, can accurately differentiate between ST and non-Salmonella samples with a classification accuracy of 96.7%.