Discriminant analysis of wood-based materials using near-infrared spectroscopy
Discriminant analysis of wood-based materials using near-infrared spectroscopy
复制标题
使用近红外光谱对木质材料进行判别分析
DOI：
10.1007/s10086-002-0471-0
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发表时间：
2003
影响因子：
2.9
通讯作者：
Kinuyo Inoue
中科院分区：
文献类型：
--
作者：
S. Tsuchikawa;K. Yamato;Kinuyo Inoue
本文探讨了近红外光谱法和几种化学计量学分析方法在木质材料鉴别中的应用。Mahalanobis的广义距离的概念，K近邻（KNN）和软独立建模类类比（SIMCA）进行了评估，以确定最佳的分析程序。详细考察了分光光度计分类准确性的差异、波长范围作为解释变量以及样品的曝光条件。在近红外光谱在样品类别内变化很大的情况下，很难将Mahalanobis的广义距离应用于木质材料的分类。KNN在NIR区域（800-2500 nm）的性能（实验室中使用的装置用于该区域）表现出与样品的光暴露条件无关的高验证正确答案率（>98%）。当采用现场使用的设备时，KNN和SIMCA在550-1010 nm的波长下均显示了正确的验证答案（>88%）。这些结果表明，近红外光谱的适用性，在工厂和工作现场的合理分类使用的木材。
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.