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Fourier-transform infrared equipped with attenuated total reflection (ATR–FT-IR) was used in combination with multivariate statistical analysis for classification and identification of food pathogens Staphylococcus and Salmonella . The goals of the present study were to validate the feasibility of ATR–FT-IR in collecting information for discriminating different bacteria, and to assess the merits of two routes for effectively identify target foodborne bacteria. The results showed that ATR–FT-IR was able to provide enough chemical information of each species. Cluster-analysis-test was able to identify target bacteria at the genus and species level using Pearson's product-moment correction coefficient and Ward's algorithm. Partial least squares regression discriminant analysis (PLS-DA) coupled with multiplicative scatter correction (MSC), standard normal variate (SNV) and their derivatives demonstrated the probable use of this routine method to differentiate food pathogens at the sub-species level.

Routine classification of food pathogensStaphylococcusandSalmonellaby ATR–FT-IR spectroscopy