Species Differentiation of Two Common Lumber Mixes by Diffuse Reflectance Fourier Transform Infrared (DRIFT) Spectroscopy

Diffuse reflectance Fourier transform infrared (DRIFT) spectroscopy was used to differentiate coniferous woods by species. Species mixtures studied were SPF (composed of white spruce [Picea glauca Voss], Engelmann spruce [Picea engelmannii Parry], lodgepole pine [Pinus contorta Dougl.] and subalpine fir [Abies lasiocarpa Nutt.]) and HEM/FIR (composed of western hemlock [Tsuga heterophylla Sarg.], amabilis fir [Abies amabilis Dougl.] and Sitka spruce [Picea sitchensis Carr.]). DRIFT spectra of the green wood samples were used in SIMCA (simple modeling of class analogy) pattern recognition to differentiate species. This approach was able to classify SPF with 90% accuracy when all samples were identified, and 94% accuracy when poorly classified samples were eliminated. For the HEM/FIR group, the method was able to classify all samples with 81% accuracy, and up to 99% accuracy when poorly classified samples were eliminated

Differentiation of Some Canadian Coniferous Woods by Combined Diffuse and Specular Reflectance Fourier Transform Infrared Spectrometry

Infrared spectroscopy was used to differentiate coniferous woods commonly found in mixtures in lumber producing mills in British Columbia. The method required collection of reflectance Fourier transform infrared spectra of wood samples at a 2 cm-1 resolution. From a small subset of spectra, frequencies useful for species differentiation were selected using a combination of correlation analysis and principal component analysis. The selected frequencies were used to develop methods for differentiating species using discriminant analysis. These models were then tested against the remainder of the spectra. This approach was successfully used to classify the same wood samples in freeze-dried and green conditions, but was unsuccessful in classifying extractive free samples