Salmonella causes illness in millions of people each year with severe cases resulting in death. Traditional detection methods are well established but are associated with disadvantages such as time or reoccurring sample cost. Hyperspectral microscope imaging (HMI) has shown potential as an early and rapid detection method, identifying bacteria based on spectral signatures unique to the microorganism. Bacteria undergo physiological changes when introduced to environmental stresses. Understanding how these physiological changes impact the resulting cellular spectra is critical to developing robust HMI methodologies for early and rapid detection of bacteria. Salmonella Enteritidis (SE) and Salmonella Typhimurium (ST) were incubated on plate agars of brilliant green sulfa, tryptic soy agar, xylose lysine deoxycholate, and xylose lysine tergitol 4, at incubation pH ranging from 4.7 to 8.3, and at incubation temperatures between 27 and 47 °C. All samples were incubated for 24 h. A principal component analysis (PCA) was performed for each experiment, with Mahalanobis distances (MD) calculated for each sample to its respective cluster’s center, quantifying intraclass variation. One-way ANOVA of MD values showed no significant difference for SE and ST grown on four agars (P > 0.05), or at varying incubation temperatures (P > 0.05). SE and ST incubated at five pH values showed significantly different spectra (P < 0.01). Results suggest that future HMI tools for identifying Salmonella can be developed regardless of the growth media or temperature but should take into consideration acidic growth environments.
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The authors would like to thank Drs. Nasreen Bano and Jing Chen, of the Quality and Safety Assessment Research Unit located at the U.S. National Poultry Research Center in Athens, GA, for their assistance with hyperspectral image collection and experiments.
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Matthew Eady declares that he has no conflict of interest. Bosoon Park declares that he has no conflict of interest.
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Eady, M., Park, B. The Influence of Environmental Growth Conditions on Salmonella Spectra Obtained from Hyperspectral Microscope Images. Food Anal. Methods 12, 2638–2646 (2019). https://doi.org/10.1007/s12161-019-01618-0
- Hyperspectral microscopy
- Rapid detection
- Foodborne bacteria
- Food safety