Abstract
Compression wood has undesirable properties for structural timber and for paper production. Traditional methods of detecting it are often time consuming and subjective. This study aimed to rapidly and impartially detect compression wood through the use of attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and diffuse reflectance near infrared (NIR) spectroscopy. Compression wood and non-compression wood samples were obtained from young Pinus radiata D. Don trees grown in New Zealand. Longitudinal dimensional changes were measured during drying or water saturation of the samples; lignin and galactose contents were determined using conventional analytical techniques. Chemical composition was here a more reliable discriminator between wood types than longitudinal dimensional changes. It was shown that partial least-squares regression (PLS-R) or discriminatory analysis (PLS-DA) could be used to build models on the training samples that could discriminate between wood types of the independently grown validation samples. Ultimately, both types of spectroscopies could be used to discriminate between compression wood and non-compression wood either through prediction or discriminatory analysis with equal success. Investigation into spectral differences between wood types, including sequential mixtures of wood types, showed that for the mid-IR region absorbance at a well-resolved lignin band could be used to discriminate compression wood from non-compression wood. For NIR, a similar investigation showed that absorbance values at four separate wavenumbers or the 6000–5600 cm−1region of the first derivative spectra were required for that discrimination. It is proposed that if there is a gradual change in the chemical composition of compression wood with its severity, then IR spectroscopy could feasibly be used to rapidly determine compression wood severity.
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