Chemometric adaptations in wood processing chemistry

Abstract

Multivariate chemometric data analysis techniques were applied to various research challenges mainly encountered in the selected process stages in the manufacture of raft pulp. The applicability of these methods was demonstrated by several examples regarding characterization of the kraft lignin and determination of the combustion properties of kraft black liquors as well as determination of the kappa number, yield, and ISO brightness of kraft pulps. In addition, the structural elucidation of soluble high-molecular-mass lignin in receiving waters was performed. In this study, various types of differently pre-treated spectroscopic and chromatographic data on the materials investigated were subjected to the principal component analysis (PCA), principal component regression (PCR), projection to latent structures (PLS) regression, and two-dimensional cross-correlation calculations (2DCC). Several types of predictive and descriptive models were established. These models functioned well within the experimental limits, producing results with good accuracy, and giving detailed information from inherently complex empirical datasets. Thus, it can generally be concluded that the adaptation of chemometric methods into wood processing applications will be of great benefit to the further development of these applications.