Non-destructive Microbial Analysis of Raw Salmon Fillets with Fourier Transform- Near Infrared Spectroscopy

Fourier-transform near-infrared (FT-NIR) spectroscopy is a powerful tool for the rapid and accurate detection of food borne contaminants. It is user-friendly tool for food safety professionals however its applications in detection of food borne pathogens are quite restricted due to complex food matrices. To reduce the risk of foodborne illness, onsite detection is imperative, hence this study is focused on evaluation of FT-NIR as a non-destructive tool for rapid detection of food borne bacteria (using Escherichia coli and total bacterial count) from perishable fishery products on an example of raw salmon fish fillets. Multiple linear regression method with preprocessing techniques like standard normal variant and detrend were applied in this study for generation of suitable calibration and validation models for identification of Escherichia coli (E.coli) and total bacterial count (TBC). Applied methodology with FT-NIR spectrometer and chemometric methods did not impact the quality of products. With further improvement and minimal to non-sample preparation, FT-NIR can be a potential tool for detection of various food borne bacteria. Existing studies provided ideas on wavelengths that identifies structural changes within the products based on the autolytic changes and microbial action, however there is not sufficient information available regarding non-destructive approach. Fast, onsite and non-invasive ways can contribute to food security and enhance the food safety level. Results obtained were able to provide information on bacterial spoilage with correlation value reached to R=0.95 for spoiled group, however for contaminated group, it reached to R=0.83. Low R value related to E.coli identification might be due to the interferences from other bacterial groups and compositional changes as raw salmon is highly perishable. To overcome the limitations and to identify specific bacteria from group, it would be advisable to use antimicrobial agents against other microorganisms that are present in samples. This study highlights the importance of chemometric models along with FT-NIR as a food safety tool as it shows the potential to demonstrate changes in three different groups of raw salmon fillets highlighting that different groups of bacteria with different concentrations act differently on salmon fillets. Hence, FT-NIR possess the ability to detect spoilage and contamination from raw salmon in a non-destructive manner however further research is required to understand the changes in a wide variety of products.