基于光谱三级鉴别和GC-MS指纹特征的濒危珍贵木材精准判别方法研究

Accurate discrimination of rare and endangered species wood is very important for the performance of CITES convention, reduce trade risk, and reasonably protect and use of precious wood. The research, the redwoods in CITES convention as objects, employ dynamic infrared spectroscopy under different temperatures, two-dimensional infrared correlation spectroscopy(2D-IR) with higher resolution, and GC-MS to precisely character chemical composition and distribution of extractives, and get characteristic infrared spectra and chromatographic fingerprint acquisition, where the feature components identification of extractives could promote the correct identification for the functional groups characteristic of infrared spectrum. According to the different degree of wood spectral differences, the three-step identification was formed based on the infrared spectra, two derivative IR spectra and two-dimensional correlation infrared spectroscopy. Meanwhile, the common substance and proprietary components of rare and endangered wood were characterized using the GC-MS advantage in separation, extraction and identification. The three-step identification and GC-MS, combined with quantitative method of principal component analysis, specific analysis of the components and similarity comparison, were used to achieve qualitative and quantitative analysis on chemical properties of wood extractives. On this basis, referring to the traditional wet chemical analysis results, wood species identification system based on the three-step identification and chromatographic fingerprint characteristic could be build, which can provide a scientific evidence for wood trade and the performance of CITES convention.

精准判别濒危珍贵木材树种对履行CITES公约，减少贸易风险，合理保护和利用木材具有十分重要的意义。本研究以列入CITES公约的红木木材为对象，借助于不同温度下的动态红外光谱和分辨率更高的二维相关红外光谱以及GC-MS对抽提物化学组成与分布特征的精确表征，获取木材红外特征光谱和色谱指纹图谱，抽提物特征成分鉴定又促进红外光谱官能团特征峰的正确指认。针对木材光谱差异程度的不同，建立基于一维红外光谱、二阶导数红外光谱和二维相关红外光谱的三级鉴别方法；同时，利用GC-MS在分离、提取和鉴定化合物方面的优势，对濒危珍贵木材的共性物质和专有成分进行表征，结合化学计量学中主成分分析、特定成分解析和相似度比对等量化方法，实现对木材抽提物化学性质的定性和定量分析；在此基础上，参考传统湿化学分析结果，构建基于红外光谱三级鉴别和色谱指纹特性的木材树种精准判别系统，为木材贸易和履行CITES公约提供科学依据。

珍贵硬阔叶材具有材性优良、色彩迷人、花纹漂亮的特点，是高端家具、地板和工艺品的重要材料，也是我国木材进口和加工利用的重要原材料。我国是濒危野生动植物种国际贸易公约（简称CITES公约）缔约国，对珍贵木材及其制品的进出口十分重视。因此，精准判别珍贵木材树种对于履行CITES公约，减少贸易纠纷，合理保护和正确利用珍贵木材具有十分重要的意义。本项目以降香黄檀、伯利兹黄檀、印度黄檀、刀状黑黄檀、阔叶黄檀、东非黑黄檀、微凹黄檀、交趾黄檀和中美洲黄檀等CITES公约管制珍贵木材和相似木材为研究对象，采用一维红外光谱、二阶导数红外光谱、动态红外光谱二维相关红外光谱和GC-MS先进研究手段，研究了25种珍贵木材及部分树种抽提物的化学特性、光谱特性和色谱特性，重点研究了颜色等外观相似易混淆树种、同属木材（黄檀属）、同类木材（红酸枝和黑酸枝、花梨木等）以及油漆前后木材的光谱特性，确定了不同官能团对温度的敏感程度，分组对比确定了不同属红木材的共有的化合物和特征成分；建立了包括130种木材的一维红外光谱、25种珍贵木材的二维相关红外光谱的数据库，构建基于一维红外光谱、二阶导数红外光谱和二维相关红外光谱等木材树种光谱三级鉴别和GC-MS指纹图谱特征信息的木材树种精准判别系统；结合化学计量学方法，利用一维红外光谱、二阶导数红外光谱和二维相关红外光谱对木材及抽提物成分的官能团进行表征，利用GC-MS技术对抽提物的主要成分和特征成分进行定性定量表征，抽提物的主要成分和特征成分鉴定又促进红外光谱官能团特征峰的正确指认。本研究发表文章10篇，被SCI收录9篇，出版专著一部，申请国家发明专利4件，培养研究生6名，本研究得出的方法和实践为木材贸易、木材利用和履行CITES公约提供了科学依据和技术支撑。