Characterisation of natural organic matter from the Nordic typing project water samples by chemometric analysis of their near infrared spectral profiles

Abstract

Natural organic matter (NOM) from nine different water sources located in the southern part of Norway selected for the “NOM typing project” was characterised by using near infrared spectroscopy and multivariate data analysis. The near infrared profiles of these NOM samples were corrected for multiple scattering effect and differentiated twice before subjecting them for multivariate data analysis. The preprocessed profiles were first subjected to multivariate calibration using partial least squares (PLS) technique against earlier determined values of four different biopolymer input (carbohydrates, N-acetyl amino sugars, proteins and polyhydroxy aromatics) of the NOM as dependent variables. The profiles were then classified using principal component analysis (PCA). The PLS calibration models obtained demonstrate that the biopolymer input of the NOM samples can be predicted with acceptable precision. The PCA reveals that the samples fall into three different groups. This classification agrees with earlier classifications carried out by using variables that were determined by alternative expensive and time-consuming analytical techniques.