Differentiation of mixed bacteria samples in the generic level using infrared spectroscopy and multivariate analysis

In the present study we examined the potential of Fourier Transformed Infrared (FTIR) spectroscopy for accurate identification and differentiation of mixed bacteria samples in a time span of a few minutes. The bacterial samples used in this study are Escherichia (E.) coli, Bacillus (B.) megaterium and a mixture of E. coli and B. megaterium. The best results of differentiation were obtained within the 675-1800 cm^-1 range. In this range the dimension of the feature vector is 293. Principal components analysis (PCA) followed by linear discriminant analysis (LDA) as a linear classifier were performed on the spectra of the three measured classes. When differentiating between the pure sets of E. coli and B. megaterium, 100% success was obtained for a feature vector composed of the first 12 principal components (PCs). An error rate of less than 2% was achieved taking only the first 20 PCs among the three categories of samples.