基于红外三级鉴定与聚类分析法的党参快速鉴别研究

doi:10.3964/j.issn.1000-0593(2017)10-3281-08

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摘要：红外光谱因具有快速、无损的优点，特别适合于不同中药的鉴别研究。基于红外光谱和聚类分析法对两类党参(共49个样本)进行鉴别。结果表明：在一维红外光谱中，两者红外光谱图非常相似，仅在1 738和935 cm^-1处有细微的差异，说明两者化学组分基本一致。在二阶导数红外光谱中，显示了更多的红外指纹特征，特别是1 747，1 515，1 468，1 368，1 264，1 163，1 147，1 108和936 cm^-1等峰的指纹特征更加明显。进一步采用高分辨率的二维相关红外光谱对两类党参(纹党参和白条党参)进行鉴别，在1 510~1 170 cm^-1范围内，纹党参的自动峰和交叉峰形成明显的3×3矩阵，在1 459，1 298和1209 cm^-1处有三个强自动峰，其中1 209 cm^-1的自动峰强度最大；而白条党参仅在1 450 cm^-1处有1个强自动峰，其余1 340, 1 260, 1 209 cm^-1等3个自动峰都极弱。此外，还采用K-means聚类分析技术对两类党参共49个样本进行快速分类研究，结果令人满意。因此，红外三级鉴定法结合K-means聚类分析技术在相似药物的鉴别中能起到重要的作用，且有利于确保药物临床治疗安全有效。

关键词：党参；红外光谱；二维相关红外光谱；K-means；聚类分析

Abstract：Middle-infrared (MIR) spectroscopy is a well-known, rapid and non-destructive technique suitable for analyses of many different herbal medicines. In this work, MIR combined with clustering analysis was used to develop a novel method for the analysis of two kinds of Codonopsis pilosula. Altogether 49 samples were collected and analyzed. Their entire FT-IR spectra in the range of 4 000~400 cm^-1 were generally similar except for small differences around 1 738 and 935 cm^-1, indicating that they had similar chemical components. In the second derivative spectra (SD-IR), more distinct fingerprint features were revealed, especially peaks at 1 747, 1 515, 1 468, 1 368, 1 264, 1 163, 1 147, 1 108 and 936 cm^-1. Furthermore, the 2D-IR spectra provided obvious differences of “Wen Dangshen” (WDS) and “Bai Tiao Dangshen” (BTDS). In the range of 1 510~1 170 cm^-1, WDS had a strong 3×3 peak cluster, including three auto-peaks at 1 459, 1 298 and 1 209 cm^-1, and the strongest auto-peak located in 1 209 cm^-1. Whereas BTDS had only one very strong auto-peak at 1 450 cm^-1 and three weak auto-peaks at 1 340, 1 260 and 1 209 cm^-1. Moreover, the two species (49 samples) has been objectively classified with K-means pattern recognition technique. In conclusion, the three-step infrared macro-fingerprint identification method combined with K-means pattern recognition technique is simple, rapid and non-destructive, which plays an important role in discriminating similar natural products to ensure safe and effective clinical treatments.

Key words：Codonopsis pilosula; FT-IR; 2D-IR correlation spectrum; K-means; Cluster analysis

收稿日期: 2016-06-28 修订日期: 2016-11-09

中图分类号:

O657.3

基金资助: the National Natural Science Foundational of China (21071099), the Innovation Projects of Department of Education of Guangdong Province (2014KTSCX169) and the Scientific Research project of Shaoguan University (S201501028)

作者简介: HUANG Dong-lan, (1983—), associate professor of Shaoguan University e-mail: lantern1227@163.com

引用本文:

黄冬兰，徐永群，陈小康，卢文贯. 基于红外三级鉴定与聚类分析法的党参快速鉴别研究[J]. 光谱学与光谱分析, 2017, 37(10): 3281-3288.
HUANG Dong-lan, XU Yong-qun, CHEN Xiao-kang, LU Wen-guan. Rapid Discrimination of Two Kinds of Codonopsis pilosula Using Three-Step Infrared Macro-Fingerprinting Combined with Clustering Analysis. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2017, 37(10): 3281-3288.

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[1] Editorial Committee of China Pharmacopoeia. China, Pharmacopoeia, Part Ⅰ. Beijing: China Chemical Industry Press, 2010. 264.
[2] Zong Z M. Zhao Z H, Zhou C P, et al. Guangzhou Medical Journal, 1999, 30: 49.
[3] Wang H, Xu Z, Liu G Z. Pharmacology and Clinics of Chinese Materia Medica, 1993, 9: 34.
[4] Guo Z Q, Zhu L Q, Zhang L P, et al. Journal of Beijing University of TCM, 1995, 18: 39.
[5] Zhao Z Z. All Illustrated Microscopic Identification of Chinese Materia Medica. Shenyang: Liaoning Science and Technology Publishing House, 2005. 123.
[6] Zhang J S, Guan J, Yang F Q, et al. Journal of Pharmaceutical Biomedical Anallysis, 2008, 48: 1024.
[7] Qiao C F, He Z D, Han Q B, et al. Journal of Food and Drug Analysis, 2007, 15: 258.
[8] Li B X, Wei Y H, Duan H G, et al. Vib. Spectroscopy, 2012, 62: 17.
[9] Wang Y, Xu CH, Wang P, et al. Spectrochimca Acta, 2011, 83: 265.
[10] Adib, A M, Jamaludin F, Kiong L S,et al. Journal of Pharmaceutical Biomedical Anallysis, 2014，96: 104.
[11] Wang Y, Wang P, Xu C H, et al. Journal of Molecular Structure, 2015, 1099: 68.
[12] Zhang Y L, Chen J B, Lei Y, et al. Journal of Molecular Structure, 2010, 974: 144.
[13] Guo X X, Hu W, Liu Y, et al. Journal of Molecular Structure, 2015，1099: 393.
[14] Zhang F D, Xu C H, Li M Y, et al. Journal of Molecular Structure, 2014, 1069: 89.
[15] Li M Y, Cheng S C, Li D, et al. Chinese Chemical Letters, 2015, 26: 221.
[16] Sun S Q, Li C W, Wei J P, et al. Journal of Molecular Structure, 2006, 799: 72.
[17] Chen J B, Zhou Q, Noda I, et al. Analytical Chimica Acta, 2009, 649: 106.
[18] Chen J B, Sun S Q, Yu J, et al. Journal of Molecular Structure, 2014, 1069: 112.
[19] Xu C H, Wang Y, Chen J B, et al. Journal of Pharmaceutical and Biomedical Analysis, 2013, 74: 298.
[20] Sun S Q, Zhou Q, Chen J B. Analysis of traditional Chinese Medicine by Infrared Spectroscopy. Beijing: China Chemical Industry Press, 2010.
[21] Sun S Q, Zhou Q, Chen J B. Infrared Spectroscopy for Complex Mixtures: Application in Food and Traditional Chinese Medicine. Beijing: China Chemical Industry Press, 2011.
[22] Noda I. Applied Spectroscopy, 1993, 47: 1329.
[23] Noda I, Dowrey A E, Marcott C, et al. Applied Spectroscopy, 2000, 54: 236.
[24] Lloyd S P. IEEE Transaction on Information Theory, 1982，28: 129.
[25] Xu Yongqun, Chen Xiaokang, Chen Yong, et al. Spectroscopy and Spectral Analysis, 2012, 32(8): 2131.
[26] Chen Zaoxin, XU Yongqun, CHEN Xiaokang, et al. Spectroscopy and Spectral Analysis, 2013，33(5): 1206.