Discriminant analysis of wood-based materials using near-infrared spectroscopy |
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| Authors: | Satoru Tsuchikawa Kaori Yamato Kinuyo Inoue |
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| Institution: | (1) Graduate School of Bioagricultural Sciences, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8601, Japan Tel. +81-52-789-4158; Fax +81-52-789-4155 e-mail: st3842@agr.nagoya-u.ac.jp, JP |
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| Abstract: | This study deals with the suitable discriminant techniques of wood-based materials by means of near-infrared spectroscopy
(NIRS) and several chemometric analyses. The concept of Mahalanobis' generalized distance, K nearest neighbors (KNN), and
soft independent modeling of class analogy (SIMCA) were evaluated to determine the best analytical procedure. The difference
in the accuracy of classification with the spectrophotometer, the wavelength range as the explanatory variables, and the light-exposure
condition of the sample were examined in detail. It was difficult to apply Mahalanobis' generalized distances to the classification
of wood-based materials where NIR spectra varied widely within the sample category. The performance of KNN in the NIR region
(800–2500 nm), for which the device used in the laboratory was employed, exhibited a high rate of correct answers of validation
(>98%) independent of the light-exposure conditions of the sample. When employing the device used in the field, both KNN and
SIMCA revealed correct answers of validation (>88%) at wavelengths of 550–1010 nm. These results suggest the applicability
of NIRS to a reasonable classification of used wood at the factory and at job sites.
Received: March 13, 2002 / Accepted: July 19, 2002
Acknowledgments The authors thank Gifu Prefectural Human Life Technology Research Institute and Kubota Co. for their support. We also thank
Professor Dr. Shiro Kimura and Dr. Hideyuki Yokochi for their constructive discussions about the research. |
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| Keywords: | Near-infrared spectroscopy Wood-based material Mahalanobis' generalized distance KNN SIMCA |
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