Data-analysis of pyrolysis-chromatograms by means of simca pattern-recognition

Abstract

The variability between repetitive pyrolysis—chromatograms of the same type of samples is not totally random, but can in part be modelled by a principal components (PC) model. This makes it possible to use efficiently repetitive pyrolysis-chromatograms of samples of known types to obtain separate PC models for each type. Samples of unknown origin can then be classified according to which of the PC models their pyrolysis-chromatograms are most similar. The methodology is illustrated using pyrolysis—gas chromatograms of two species of the fungal genus Penicillium