Recognition of Different Parts of Wild Cordyceps Sinensis Based on Infrared Spectrum
CHEN Tao1, GUO Hui1, YUAN Man1, TAN Fu-yuan3*, LI Yi-zhou2*, LI Meng-long1
1. College of Chemistry, Sichuan University, Chengdu 610064, China
2. School of Cyber Science and Engineering, Sichuan University, Chengdu 610064, China
3. Biological Process Science and Technology Co., Ltd., Chengdu 610093, China
Abstract：Cordyceps Sinensis, a famous Chinese medicinal material, is favored due to its good medicinal value. Recently, investigations have focused on the study of its active ingredient content and pharmacological effects. However, scarce studies were reported on the identification of different parts of wild Cordyceps. This study is based on infrared spectroscopy data, combined with the analytical preponderance of chemometrics in multi-dimensional complex systems to classify and identify different parts of Cordyceps Sinensis. First, preprocessing methods, standard normal variation (SNV) and multiplicative scatter correction (MSC) were used on a total of 808 spectral data of five different parts of wild Cordyceps, including head of stroma(HS), middle of stroma(MS), head(HD), the middle larva body(ML) and the end larva body(EL). Then, competitive adaptive reweighted sampling (CARS) and variable combination population analysis (VCPA) were hired to select characteristic variables with representative significance. Ultimately, partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were engaged for modeling and predictive analysis. Ten-fold cross-validation was used on the training set, and accuracy (Acc) was employedas the evaluation index. The results showed that the prediction accuracies of the PLS-DA model on the 10-fold cross-validation and independent test set on this data were 90.1% and 92.0%, respectively, while using the LDA model, the prediction accuracies reduced to 86.7% and 85.8%, respectively. In addition, the dimensions of the features can be effectively reduced from 3 601 to 669 and 420, respectively, when using CARS and VCPA feature selection methods, but keeping the prediction accuracies equivalent to that of all features. The selected wavenumbers 630, 625, 1 024, 1 028, 1 084, and 1 089 cm-1were related to mannitol in cordyceps, and 879 and 874 cm-1 were related polysaccharides in cordyceps. The Wilcoxon rank-sum test on the selected wavenumbers further showed significant differences between the five parts of Cordyceps. This study showed that chemometric methods combined with infrared spectroscopy could effectively identify different parts of Cordyceps Sinensis, thereby deepening the understanding of the formation of Cordyceps at the molecular level and providing a reference for the efficient use of different parts of Cordyceps.
陈 逃，郭 慧，袁 满，谭福元，李益洲，李梦龙. 基于红外光谱对野生冬虫夏草不同部位的识别[J]. 光谱学与光谱分析, 2021, 41(12): 3727-3732.
CHEN Tao, GUO Hui, YUAN Man, TAN Fu-yuan, LI Yi-zhou, LI Meng-long. Recognition of Different Parts of Wild Cordyceps Sinensis Based on Infrared Spectrum. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2021, 41(12): 3727-3732.
[1] Lo H C, Hsieh C, Lin F Y, et al. Journal of Traditional & Complementary Medicine, 2013, 3(1): 16.
[2] Li S P, Yang F Q, Tsim K W K. Journal of Pharmaceutical & Biomedical Analysis, 2006, 41 (5): 1571.
[3] Li S P, Li P, Dong T T X, et al. Electrophoresis, 2001, 22(1): 144.
[4] Yang F Q, Ge L, Yong J W H, et al. Journal of Pharmaceutical and Biomedical Analysis, 2009, 50(3): 307.
[5] Zhao H Q, Wang X, Li H M, et al. Molecules, 2013, 18: 9788.
[6] Hu H, Xiao L, Zheng B, et al. Analytical and Bioanalytical Chemistry, 2015, 407(26): 8059.
[7] Wang P, Zhang H, Yang H, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 137: 1403.
[8] Xie C, Xu N, Shao Y, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2015, 149: 971.
[9] Chen H, Lin Z, Tan C. Journal of Pharmaceutical and Biomedical Analysis, 2018, 161: 239.
[10] Yu Y, Yu H, Guo L, et al. Analytical Methods, 2018, 10(26): 3224.
[11] Xu S, Zhao Y, Wang M, et al. CATENA, 2017, 157: 12.
[12] Yun Y H, Wang W T, Deng B C, et al. Analytica Chimica Acta, 2015, 862: 14.
[13] Alladio E, Giacomelli L, Biosa G, et al. Forensic Science International, 2018, 282: 221.
[14] Szabó é, Gergely S, Salgó A. Journal of Chemometrics, 2018, 32(4): e3005.s
[15] Yang P, Song P, Sun S Q, et al. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 2009, 74(4): 983.
