Abstract
Fourier Transform Infrared (FTIR) microspectroscopy, in combination with chemometrics, was investigated as a novel method to discriminate between cyanobacterial strains. In total, 810 absorbance spectra were recorded from one eukaryotic and five cyanobacterial taxa spanning three genera and including two strains of one species, Microcystis aeruginosa. Principal Component Analysis (PCA) based classification techniques such as Soft Independent Modelling of Class Analogy (SIMCA) and K-Nearest Neighbours (KNN) were investigated. Different spectral regions using derivative spectra were investigated to find the best combinations for classification. The highest rate of correct classifications (99–100%) was achieved using first derivative spectra with a spectral region of 1800–950 cm−1 for both the SIMCA and KNN. A dendrogram constructed using averaged spectra of the six taxa studied showed that the two strains of Microcystis aeruginosa exhibited the highest degree of similarity, while the eukaryotic taxon was the most dissimilar from the prokaryotic taxa.
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