文献类型：期刊文献

英文题名：Wood discrimination analyses of Pterocarpus tinctorius and endangered Pterocarpus santalinus using DART-FTICR-MS coupled with multivariate statistics

作者：Zhang, Maomao[1,2,3] Zhao, Guang Jie[2] Liu, Bo[1,3] He, Tuo[1,3] Gu, Juan[1,3] Jiang, Xiaomei[1,3] Yin, Yafang[1,3]

第一作者：Zhang, Maomao

通信作者：Yin, YF[1];Yin, YF[2]

机构：[1]Chinese Acad Forestry, Res Inst Wood Ind, Dept Wood Anat & Utilizat, Beijing 100091, Peoples R China;[2]Beijing Forestry Univ, Coll Mat Sci & Technol, Beijing 100083, Peoples R China;[3]Chinese Acad Forestry, Wood Collect WOODPEDLA, Beijing 100091, Peoples R China

年份：2019

卷号：40

期号：1

起止页码：58-74

外文期刊名：IAWA JOURNAL

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000460502000005)】；

基金：This work was financially supported by the Fundamental Research Funds for the Central Non-profit Research Institution of the Chinese Academy of Forestry (Project No. CAFint2015C06), the National High-level Talent for Special Support Program of China (the National "Ten Thousand" Talents Plan) (Grant No. W02020331). The authors wish to acknowledge Dr. Alex C. Wiedenhoeft of the Forest Products Laboratory, USA, and Mr. Di Xiao and Mr. Changyu Xu for their help in collecting the samples.

语种：英文

外文关键词：Mass spectrometry; wood identification; xylarium; wood extract; OPLS-DA models; machine learning methods

摘要：Pterocarpus santalinus, listed in CITES Appendix II, is an endangered timber species as a result of illegal harvesting due to its high value and commercial demand. The growing demand for P. santalinus and timbers with the morphologically similar Pterocarpus tinctorius has resulted in confusion as well as identification problems. Therefore, it is of vital importance to explore reliable ways to accurately discriminate between santalinus and P. tinctorius. In this study, the method of direct analysis in real time and fourier transform ion cyclotron resonance mass spectrometry (DART-FTICR-MS), combined with multivariate statistical analysis, was used to extract chemical information from xylarium wood specimens and to explore the feasibility of distinguishing these two species. Significant differences were observed in their DART-FTICR-MS spectra. Orthogonal partial least square-discriminant analysis (OPLS-DA) showed the highest prediction, with an accuracy of 100%. These findings demonstrate the feasibility of authenticating wood types using DART-FTICR-MS coupled with multivariate statistical analysis.