Near-infrared spectroscopy as a potential method for identification of anatomically similar Japanese diploxylons
Near-infrared spectroscopy as a potential method for identification of anatomically similar Japanese diploxylons
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DOI：
10.1007/s10086-015-1462-2
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发表时间：
2015-06-01
影响因子：
2.9
通讯作者：
Sugiyama, Junji
中科院分区：
文献类型：
--
作者：
Horikawa, Yoshiki;Mizuno-Tazuru, Suyako;Sugiyama, Junji
采用近红外（NIR）光谱与多变量分析相结合的方法，设计了一种可靠的解剖结构相似的松、松和松的鉴别方法。从京都大学木木林中选取了24块木块，其中一半为密植木块，其余为通氏木块，并对其进行了仔细研究，以建立一个可接受的模型来区分这两个物种。仅用心材构建预测模型，在二阶导数谱波数为7300 ~ 4000 cm（-1）时，预测效果最好。为了将该模型应用于从历史木结构建筑中获得的实际材料，对12个老化木样进行了微观鉴定分析和比较。出乎意料的是，物种之间的光谱差异小于老化引起的光谱差异，预测误差约为50%。老化样品的光谱在吸收水分的特定区域特征（5220 cm(-1)）上非常明显；主成分分析清楚地证明了这一点。因此，为了使所提出的模型适用于实际应用，有必要进一步研究老化木材样品和相应的光谱数据，以了解老化对光谱数据的影响。
A reliable technique for distinguishing anatomically similar diploxylons, Pinus densiflora and P. thunbergii, was designed by employing near-infrared (NIR) spectroscopy in combination with multivariate analysis. In total, 24 wood blocks, with half of them being of P. densiflora and the rest of P. thunbergii, were selected from the collections of the Kyoto University xylarium and scrutinized to build an acceptable model for discriminating between the two species. The prediction model was constructed only from heartwood, and the best performance was obtained for wavenumbers of 7,300-4,000 cm(-1) in the second derivative spectra. To apply this model to actual materials obtained from historical wooden buildings, 12 aging wood samples were analyzed and compared by microscopic identification. Unexpectedly, the spectral differences between the species were smaller than those caused by aging, and the prediction error was approximately 50 %. The spectra of the aging samples were quite distinct in the specific region characteristic of absorbed water (5,220 cm(-1)); this was demonstrated clearly by principal component analysis. Therefore, for the proposed model to be suitable for use in practical applications, further investigations of aging wood samples and the corresponding spectroscopic data are necessary to understand the effects of aging on the spectral data.