Chemometric Optimization of a Demineralization Method for Analysing Sediment Organic Matter by Fourier Transform Infrared Spectroscopy

Abstract

Fourier transform infrared (FTIR) spectroscopy is a widespread and useful technique for characterizing the chemical composition of soil/sediment organic matter (SOM). However, the mineral components of the samples limit spectral analysis since they mask SOM’s distinctive signals. Big efforts have been made in this matter to eliminate the spectral interferences of mineral constituents of the samples, by demineralization with hydrofluoric acid (DHF), or spectral subtraction. This work aimed to upgrade reported DHF methods and optimize a sample preparation methodology for SOM characterization by FTIR spectroscopy combining the potential of spectral and multivariate analysis. Semi-quantitative FTIR ratios were introduced as input variables for principal component analysis to determine the optimal DFH conditions to characterize SOM. One-way analysis of variance (ANOVA, α = 0.05) test revealed that the optimal demineralization was achieved with two cycles of HF 10% v/v at 60 °C, against five HF cycles and room temperature, previously reported. The DHF at the optimal conditions not only improved the demineralization efficiency against that of the reported methods but also did not cause significant undesirable modifications in SOM that could distort the FTIR analysis. These conclusions have statistical significance and are based on the qualitative information of the spectra and also on a comprehensive semi-quantitative study of them.