Abstract
Hyperspectral imaging (HSI) provides both spatial and spectral information of a sample by combining imaging with spectroscopy. The objective of this study was to generate hyperspectral graphs of common foodborne pathogens and to develop and validate prediction models for the classification of these pathogens. Four strains of Cronobacter sakazakii, five strains of Salmonella spp., eight strains of Escherichia coli, and one strain each of Listeria monocytogenes and Staphylococcus aureus were used in the study. Principal component analysis and kNN (k‐nearest neighbor) classifier model were used for the classification of hyperspectra of various bacterial cells, which were then validated using the cross‐validation technique. Classification accuracy of various strains within genera including C. sakazakii, Salmonella spp., and E. coli, respectively, was 100%; except within C. sakazakii, strain BAA‐894, and E. coli, strains O26, O45, and O121 had 66.67% accuracy. When all strains were studied together (irrespective of their genus) for the classification, only C. sakazakii P1, E. coli O104, O111, and O145, S. Montevideo, and L. monocytogenes had 100% classification accuracy, whereas E. coli O45 and S. Tennessee were not classified (classification accuracy of 0%). Lauric arginate treatment of C. sakazakii BAA‐894, E. coli O157, S. Senftenberg, L. monocytogenes, and S. aureus significantly affected their hyperspectral signatures, and treated cells could be differentiated from the healthy, nontreated cells.
Highlights
Hyperspectral imaging (HSI) is an emerging technology that has a great potential in rapid detection and identification of foodborne pathogens
The captured images were clarified using various image‐clarifying tools available in ENVI for the better visualization of bacterial cells; clarification of images did not affect the hyperspectral signatures of bacterial cells or other pixels in the images
Based on the preliminary work and personal communication with CytoViva® personnel, wavelength range from 425.57 to 753.84 nm was selected for Principal component analysis (PCA) and kNN classifier modeling because wavelengths below 425.57 nm and above 753.84 nm were overlapping for all bacterial strains and no useful information could be utilized for the differentiation and classification purposes
Summary
Hyperspectral imaging (HSI) is an emerging technology that has a great potential in rapid detection and identification of foodborne pathogens. Traditional methods are still used for the detection and identification of pathogens in food, these methods are cumbersome, labor‐intensive, expensive, and can take from 4 to 7 days to give confirmatory results. Rapid detection methods for foodborne pathogens, at least at the presumptive level, are required for the functioning of a safe and fast food supply chain. The HSI is a nondestructive method of analyzing and detecting a specimen and combines imaging with spectroscopy to acquire both spatial and spectral information of a specimen (such as bacterial cells or colonies) by using visible near‐infrared spectra
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