Multivariate Statistical Analysis of Mass Spectra as a Tool for the Classification of the Main Humic Substances According to Their Structural and Conformational Features

The aim of this work is to explore the suitability of the complementary use of mass spectra and the corresponding statistical analysis (principal components-Pareto analysis (PCA) and discriminant analysis (DA)) of these spectra to differentiate diverse humic samples as a function of their structural and conformational features. To this end, the mass spectra of humic samples belonging to the main humic fraction types (gray humic acid, brown humic acid, and fulvic acid) were obtained by electrospray ionization mass spectrometry (ESI-MS). The results obtained showed that the application of PCA yielded a clear separation between blanks and humic samples. However, a clear differentiation among the humic fraction types was not achieved. The DA of PCA data, however, yielded a clear separation among the humic substances (HS) samples belonging to each HS fraction type considered: gray humic acids, brown humic acids, and fulvic acids. These results showed that the mass spectra of each humic sample include characteristic mass/charge (m/z) distribution values that can be considered as a “fingerprint” representative of its specific structural features. Our results also indicate that, although the m/z values principally corresponded to single-charged ions, we cannot identify these molecular weight distributions with those of humic samples, since sample molecular fragmentation, as well as partial molecular ionization, cannot be ruled out under our experimental and instrumental conditions.