Prediction of extractives and lignin contents of Anatolian black pine (Pinus nigra Arnold. var pallasiana) and Turkish pine (Pnus brutia Ten.) trees using infrared spectroscopy and multivariate calibration

Abstract

Determination of quality parameters such as extractives and lignin contents of wood by wet chemistry analyses takes long time. Near-infrared (NIR) and mid-infrared (MIR) spectroscopy coupled with multivariate calibration offer fast and nondestructive alternative to obtain reliable results. However, due to complexity of multi-wavelength spectra, wavelength selection is generally required. Turkish pine and Anatolian black pine are the most growing pine species in Turkey. Forest products industry has widely accepted use of these trees because of their ability to grow on a wide range of sites and their suitability to produce desirable products. Determination of extractives and lignin contents of wood provides information to tree breeders when to cut and on how much chemical is needed in pulping and bleaching process. In this study, 58 samples of Turkish pine and 51 samples of Anatolian black pine were collected to investigate the correlation between NIR and MIR spectra of these samples and their extractives and lignin contents which were determined with reference methods. Genetic inverse least squares (GILS) was used for multivariate calibration. Standard error of calibration (SEC) values were less than 1.86% (w/w) for lignin and 1.19% (w/w) for extractives whereas standard error of prediction (SEP) values were less than 3.81% (w/w) for lignin and 2.04% (w/w) for extractives. Resulting R2 values for calibrations were larger than 0.8. Classification for Turkish pine and Anatolian black pine samples was performed by genetic algorithm based principal component analysis (GAPCA) and these two pine species were classified by using NIR and MIR spectra.