Resumen:
An adequate knowledge of the chemical and structural features that characterize the main fractions of humic substances in solution is of great interest to better understand a number of processes occurring in nature. Qualitative analysis of the spectra derived from diverse analytical techniques is frequently complicated, however, partially due to the quantity and complexity of the data. In this context, multivariate statistical analysis has proven to be a useful tool to integrate and interpret all this information. In this study, we applied Pareto analysis to the spectrum data derived from the application of diverse analytical techniques to several samples of humic substances. The humic substances considered in the study belong to the following groups: gray humic acid (GHA), brown humic acid (BHA), and fulvic acid (FA). The analytical techniques applied were ultraviolet¿visible light, synchronous fluorescence, and Fourier transform infrared spectroscopies, 13C nuclear magnetic resonance spectrometry, and pyrolysis gas chromatography¿mass spectrometry. The results show the efficiency of Pareto analysis at discriminating between the different groups of humic substances. Th is discrimination corresponded to specific spectral regions for each group, which corresponded to singular structural features. Thus, GHA presented a marked aliphatic character and low functionality. The BHA group presented high structural homogeneity characterized by a high aromatic character,