Identification and classification of glucose-based polysaccharides by applying Py-GC/MS and SIMCA

Abstract

This paper describes a simplified method for the identification of glucose-based polymers (polysaccharides). The method developed consists of classifying the results from analytical pyrolysis gas chromatography mass spectrometry (Py-GC/MS) by applying soft independent modelling of class analogy (SIMCA). Since the amount of inorganic compounds in the sample influences the pyrolysis results, the classification model is applied to the pyrolysis results obtained from samples in their original form and after pre-treatment. The pre-treatment aims at removing the inorganic compounds from the polysaccharides and consists of washing out the samples with acid solutions. Depending on the acid used, pyrolysis results may differ. Therefore, the pre-treatment impact on the pyrolysis results is evaluated as well. After optimisation of the sample pre-treatment, it is possible to discriminate between various subgroups of starches (native, cationic, oxidised starches and dextrin). This indicates that appropriate sample pre-treatment in combination with chemometric data evaluation results in a clear classification of very similar samples showing very similar pyrograms. The methodology developed facilitates the analysis and identification of deposits originating from polysaccharides found in paper production processes.