Fourier transform infrared spectroscopy (FTIR) as a tool for discriminating Salmonella typhimurium contaminated beef

Detection of beef contamination from harmful pathogens will be helpful in protecting the consumer safety and controlling the outbreaks. In this paper, the potential of Fourier transform infrared spectroscopy (FTIR) was investigated to discriminate the Salmonella contaminated packed beef. A suitable headspace sampling system was designed and used to collect the headspace volatiles from the packed meat to the FTIR gas cell. Spectral signatures of headspace volatiles of meat packages were used to classify the packed meat samples as contaminated or not. FTIR spectrum was divided into several regions in order to reduce the dimensionality as well as to select the regions based on the absorbance properties of various volatiles present in headspace of meat package. Principal component analysis was performed on the entire spectrum (4000-500 cm ^-1) as well as on the selected sub-regions of entire spectrum. Two statistical classification techniques (linear and quadratic discriminate analysis) were used to develop classification models. The statistical models were validated using bootstrap cross validation technique. The total average classification accuracies were evaluated in terms of coefficient of variance (% CV). Based on the mean of total average classification accuracies and its % CV calculated from five similarly conducted experiments, it was found that the statistical models developed on a part of the spectra (500-850 cm ^-1) and full spectra (4000-500 cm ^-1) can be used as potential classification models for non-destructive discrimination of Salmonella contaminated packed beef samples from uncontaminated ones. These results need to be further validated on dataset with larger sample size.