药用植物川东獐牙菜红外光谱分析与鉴别

doi:10.3964/j.issn.1000-0593(2016)02-0388-06

Abstract
References
Related Citation (15)

Download: PDF (3812 KB)
Export: BibTeX | EndNote (RIS)

Abstract Fourier transform infrared spectroscopy combined with partial least squares discriminate analysis (PLS-DA) and hierarchical cluster analysis (HCA) were used to rapidly discriminate the Swertia davidi Franch which collected from different origins. The original infrared spectra data of different parts of all the 70 samples which collected from four different regions were preprocessed by automatic calibration, automatic smoothing, the first derivative and the second derivative. Then the processed data were imported into OMNIC 8.2 and the absorption peaks were compared; PLS-DA was performed by SIMCA-P⁺ 10.0 and the effect of discrimination of different origins was compared by 3D score plot of the first three principal components; the infrared spectral data were imported into SPSS 19.0 for HCA to compare classification results of different parts by the dendrogram. The results showed that: (1) There were differences among the spectra of the roots of different origins in the spectral peaks in 1 739, 1 647, 1 614, 1 503, 1 271, 1 243, 1 072 cm^-1. The spectra of the stems of different origins showed differentiation in the wavelength in 1 503, 1 270, 1 246 cm^-1; (2) The characteristic peaks of different parts of the same origin were different; (3) PLS-DA indicated that the data which were processed by automatic correction, automatic smoothing and second derivative have showed the best classification. In addition, the discrimination of roots which collected from different origins could be the best; (4) Tree diagram of HCA showed that the accuracy rate of cluster in roots, stems and leaves were 83%, 56%, and 70%, respectively. In conclusion: FTIR combined with PLS-DA and HCA can rapidly and accurately differentiate S. davidi that collected from different origins, the origin discrimination effect of different parts was clearly different that the classification of roots is the best, the second derivative could enhance the specificity of the samples, the classification in 3D score plot could be visualized and obvious.

Key words：Infrared spectroscopy;Origin discrimination;Swertia davidi Franch;Hierarchical cluster analysis;Partial least squares discriminant analysis

Received: 2014-09-28 Accepted: 2015-01-18

ZTFLH:

O657.3

Corresponding Authors: WANG Yuan-zhong, LI Li1 E-mail: yzwang1981@126.com; lilyjsu@126.com

Cite this article:

DI Zhun,ZHAO Yan-li,ZUO Zhi-tian, et al. Analysis and Discrimination of the Medicinal Plants Swertia Davidi Franch Based on Infrared Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2016, 36(02): 388-393.

URL:

https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2016)02-0388-06 OR https://www.gpxygpfx.com/EN/Y2016/V36/I02/388

[1] Editorial Committee of Flora China Nica of the Academy of Sciences of China(中国科学院中国植物志编辑委员会). Flora of China(中国植物志). Beijing: Science Press(北京: 科学出版社), 1988. 371.
[2] Li L, Huang H Y. Bulletin of Botanical Reseach, 2006, 24(6): 452.
[3] Sirish Kumar I, Paul B N, Asthana R, et al. ImmunoPharmacology and Immunotoxicology, 2003, 25(4): 573.
[4] HUANG Lu-qi, GUO Lan-ping(黄璐琦, 郭兰萍). China Journal of Chinese Materia Medica(中国中药杂志), 2007, 32(04): 277.
[5] Abdulmanea K, Prokudina E A, Lanková P, et al. Biochemical Systematics and Ecology, 2012, 45: 237.
[6] Cheng H, Qin Z H, Guo X F, et al. Food Research International, 2013, 51(2): 813.
[7] Zhang C, Su J. Acta Pharmaceutica Sinica B, 2014, 4(3): 182.
[8] FENG Shan-shan, ZHENG Si-hao, LI Ya-kang, et al(冯杉杉, 郑司浩, 李亚康, 等). Acta Pharmaceutica Sinica(药学学报), 2014, 49(2): 260.
[9] Tarantilis P A, Troianou V E, Pappas C S, et al. Food Chemistry, 2008, 111(1): 192.
[10] Zhao Yanli, Zhang Ji, Yuan Tianjun, et al. Plos One, 2014, 9(2): e89100.
[11] Li J R, Sun S Q, Wang X X, et al. Journal of Molecular Structure, 2014, 1069: 229.
[12] Fan Q M, Chen C Y, Lin Y P, et al. Journal of Molecular Structure, 2013, 1051: 66.
[13] Negi J S. Natural Product Research, 2012, 26(1): 72.
[14] Wang Y L, Xiao Z Q, Liu S, et al. Journal of Ethnopharmacology, 2013, 150(2): 536.
[15] Wan L S, Chen C P, Xiao Z Q, et al. Journal of Ethnopharmacology, 2013, 147(3): 622.
[16] Pandey D K, Basu S, Jha T B. Asian Pacific Journal of Tropical Biomedicine, 2012, 2(3): S1450.
[17] Tao H, Jing X, Lina Y, et al. American Journal of Plant Sciences, 2012, 3(7): 904.
[18] Gok S, Severcan M, Goormaghtigh E, et al. Food Chemistry, 2014.
[19] NI Zhen, HU Chang-qin, FENG Fang(尼珍, 胡昌勤, 冯芳). Chinese Journal of Pharmaceutical Analysis(药物分析杂志), 2008, 28(5): 824.
[20] Kniggendorf A K, Gaul T W, Meinhardt-Wollweber M. Applied Spectroscopy, 2011, 65(2): 165.