Identifying Timber Species by Diffuse Reflection Spectra in the Near-Infrared Region Using a Linear Discriminant Analysis

The article presents an algorithm of analysis of coniferous timber materials ( Pinus sylvestris L., Pinus sibirica Du Tour, Larix decidua Mill., Abies alba L. and Picea abies (L.) Karst.) using the spectroscopy method in the near-infrared region. Timber is a complex organic material consisting of cellulose, hemicellulose, lignin, and extractive substances. These compounds generate absorption bands in the near-infrared region which are mainly overtones and combination bands of the O-H, N-H and C-H functional groups. The authors suggest the best ways to correct scattering considering the specific features of the samples under examination. Based on the application of linear discriminant analysis, a method is proposed for the automatic identification of the timber species by diffuse reflection spectra in the near-infrared region, as well as key parameters sufficient for the classification procedure are determined. The obtained LDA-models showed high predictive capability. The overall average classification accuracy reached 97,6%. Based on the results obtained, it can be stated that the NIR spectroscopy is suitable for solving tasks related to the identification of the timber species; it has proven to be an effective tool for distinguishing wood species.