Chemometrics Approach For Species Identification of Pinus densiflora Sieb. et Zucc. and Pinus densiflora for. erecta Uyeki - Species Classification Using Near-Infrared Spectroscopy in combination with Multivariate Analysis -

소나무와 금강송의 수종식별을 위한 화학계량학적 접근 - 근적외선 분광법과 다변량분석을 이용한 수종 분류 -

Hwang, Sung-Wook;Lee, Won-Hee;Horikawa, Yoshiki;Sugiyama, Junji

  • Received : 2015.06.03
  • Accepted : 2015.07.16
  • Published : 2015.11.25


A model was designed to identify wood species between Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc. using the near-infrared (NIR) spectroscopy in combination with principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). In the PCA using all of the spectra, Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc. could not be classified. In the PCA using the spectrum that has been measured in sapwood, however, Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc. could be identified. In particular, it was clearly classified by sapwood in radial section. And more, these two species could be perfectly identified using PLS-DA prediction model. The best performance in species identification was obtained when the second derivative spectra was used; the prediction accuracy was 100%. For prediction model, the $R_p{^2}$ value was 0.86 and the RMSEP was 0.38 in second derivative spectra. It was verified that the model designed by NIR spectroscopy with PLS-DA is suitable for species identification between Pinus densiflora for. erecta Uyeki and Pinus densiflora Sieb. et Zucc.


wood identification;near-infrared spectroscopy;principal component analysis;partial least square discriminant analysis;Pinus densiflora for. erecta Uyeki;Pinus densiflora Sieb. et Zucc.


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