Objective: To study and establish a method based on gas chromatography and chemometrics techniques for distinguishing Artemisiae Argyi Folium and its adulterants Artemisiae Mongolica Folium. Methods: Gas chromatography method was established with Agilent HP-5 19091J (30 m×0.32 mm, 0.25 μm) as chromatographic column, and hydrogen flame ion detector (FID) as detector. After the chemical composition of 21 chromatographic peaks in the chromatogram were identified, and the peak area data of the 21 chromatographic peaks in 29 batches of samples were determined. Similarity analysis, correlation analysis, cluster analysis, principal component analysis and orthogonal partial least squares-discriminant analysis were applied to analyze the chromatographic data. Results: The results of chemometric analysis indicated that tpeak 20 (chamazulene), peak 3 (1,8-cineole) and peak 19((1S,8aα)-decahydro-1,4aβ-dimethyl-7β-isopropenyl-1-naphthol) were the differential characteristic chromatographic peaks between Artemisiae Argyi Folium and its adulterants Artemisiae Mongolica Folium. The ratios of the peak areas of peak 3 to peak 20 were in the ranges of 54.50-348.39 and 0.16-0.87 respectively, and the ratios of the peak areas of peak 19 to peak 20 were in the ranges of 18.55-128.46 and 0.01-0.14 respectively. These significant differences could be used for the identification of Artemisiae Argyi Folium and its adulterant Artemisiae Mongolica Folium. Conclusion: The research findings can be used for the identification of Artemisiae Argyi Folium and its adulterant Artemisiae Mongolica Folium, and these have certain reference significance for the research and analysis of Artemisiae Argyi Folium and related drugs.
ZHANG Wen-jing, LI Hai-yan, WANG Xiao-wei, WANG Hai-bo, LI Xiang-yang, LI Gui-ben, ZHANG Hong-wei, GENG Yi-wei, YANG Yuan, SHI Yan
. Identification of Artemisiae Argyi Folium and Artemisiae Mongolica Folium based on gas chromatography and chemometric techniques*[J]. Chinese Journal of Pharmaceutical Analysis, 2024
, 44(4)
: 649
-662
.
DOI: 10.16155/j.0254-1793.2024.04.12
[1] 南京中医药大学. 中药大辞典[M]. 上海: 上海科学技术出版社, 2005: 801
Nanjing University of Chinese Medicine. Dictionary of Traditional Chinese Medicine[M]. Shanghai: Shanghai Scientific and Technical Publishers, 2005: 801
[2] 聂韡, 刘畅, 单承莺. 艾草的本草考证及资源分布[J]. 中国野生植物资源, 2019, 38(4):93
NIE W, LIU C, SHAN CY. Textual research and resources distribution of wormwood[J]. Chin Wild Plant Res, 2019, 38(4):93
[3] 中华人民共和国药典2020年版. 一部[S]. 2020: 91
ChP 2020. Vol Ⅰ[S]. 2020: 91
[4] 兰晓燕, 张元, 朱龙波, 等. 艾叶化学成分、药理作用及质量研究进展[J]. 中国中药杂志, 2020, 45(17):4017
LAN XY, ZHANG Y, ZHU LB, et al. Research progress on chemical constituents from Artemisiae Argyi Folium and their pharmacological activities and quality control[J]. China J Chin Mater Med, 2020, 45(17):4017
[5] 袁林祥, 吴航宇, 邱彩玲. 艾叶的药物活性成分、药理作用及临床应用浅析[J]. 当代医药论丛, 2020, 18(2):171
YUAN LX, WU HY, QIU CL. A brief analysis of pharmaceutical active ingredients, pharmacological action and clinical application of Artemisia argyi[J]. Contemp Med Forum, 2020, 18(2):171
[6] 张雪琳, 陈新旺, 吴毅明. 近10年来艾叶挥发油的化学成分及药理活性研究进展[J]. 中华中医药学刊, 2021, 39(5):111
ZHANG XL, CHEN XW, WU YM. Research progress on chemical constituents and pharmacological activities of volatile oil of Aiye(Artemisia argyi)[J]. Chin Arch Tradit Chin Med, 2021, 39(5):111
[7] 中国科学院中国植物志编辑委员会. 中国植物志.第76卷. 第二分册[M]. 北京: 科学出版社, 1991: 2,111
Editorial Committee of Flora of China. Flora of China. Vol 76(2)[M]. Beijing: Science Press, 1991: 2,111
[8] 其乐木格, 包文强, 何祥, 等. 气质联用技术对蒙古蒿挥发油化学组成的鉴定[J]. 内蒙古民族大学学报(自然科学版), 2021, 36(2):140
QI LMG, BAO WQ, HE X, et al. Identification of the chemical composition of the volatile oil from Artemisia mongolica by GC-MS[J]. J Inner Mongolia Minzu Univ (Nat Sci), 2021, 36(2):140
[9] 董岩, 祁伟, 肖传勇. 蒙古蒿挥发油化学成分及其抑菌活性分析[J]. 中国药学杂志, 2013, 48(16):1359
DONG Y, QI W, XIAO CY. Analysis of chemical constituents of volatile oils from Artemisia mongolica and their antimicrobial activities[J]. Chin Pharm J, 2013, 48(16):1359
[10] 李欣, 隋秀竹. 艾叶及其伪品蒙古蒿叶的鉴别[J]. 中国中药杂志, 1991, 16(8):458
LI X, SUI XZ. Identification of Artemisia argyi leaf and its counterfeit Artemisia mongolica leaf[J]. China J Chin Mater Med, 1991, 16(8):458
[11] 李恩波, 孙稚颖. 艾叶及其常见混伪品的分子鉴定[J]. 中国药房, 2013, 24(43):4037
LI EB, SUN ZY. Molecular identification of Artemisia argyi and its adulterants[J]. China Pharm, 2013, 24(43):4037
[12] 熊婧, 李慧勇, 李广生, 等. 化学计量学在中药色谱分析中的应用探讨[J]. 药物分析杂志, 2021, 41(10):1681
XIONG J, LI HY, LI GS, et al. Discussion on the application of chemometrics in chromatographic analysis of traditional Chinese medicine[J]. Chin J Pharm Anal, 2021, 41(10):1681
[13] 彭琴, 邹福贤, 许少华, 等. 基于化学计量学的指纹图谱法鉴别金线莲及其混伪品[J].药学研究, 2021, 40(3):149
PENG Q, ZHOU FX, XU SH, et al. Identification of Anoectochilus roxburghii and its adulterants using HPLC fingerprints based on chemometrics[J]. J Pharm Res, 2021, 40(3):149
[14] 曹秀楠, 张蒙蒙, 王维, 等. 基于UPLC指纹图谱的防己及其混伪品鉴别研究[J]. 中药材, 2022, 45(11):2671
CAO XN, ZHANG MM, WANG W, et al. Identification of Stephaniae Tetrandrae Radix and adulterants based on UPLC fingerprint[J]. J Chin Med Mater, 2022, 45(11):2671
[15] 张蒙, 于丹, 崔磊, 等. 艾叶挥发油化学成分研究进展[J]. 现代生物医学进展, 2019, 19(4):777
ZHANG M, YU D, CUI L, et al. Research progress of chemical constituents of volatile oil from Artemisia argyi[J]. Prog Mod Biomed, 2019, 19(4):777
[16] SANDUSKY P, RAFTERY D. Use of semiselective TOCSY and the pearson correlation for the metabonomic analysis of biofluid mixtures: application to urine[J]. Anal Chem, 2005, 77(23):7717
[17] WANG Z, LUO P, CHENG L, et al. Hapten-antibody recognition studies in competitive immunoassay of α-zearalanol analogs by computational chemistry and pearson correlation analysis[J]. J Mol Recognit, 2011, 24(5):815
[18] WOLD S, ANTTI H, LINDGREN F, et al. Orthogonal signal correction of near-infrared spectra[J]. Chemometr Intell Lab, 1998, 44(1):175
[19] TRYGG J, WOLD S. Orthogonal projections to latent structures (O-PLS)[J]. J Chemom, 2002, 16(3):119
[20] BIAGIONI JD, ASTLING PD, GRAF P, et al. Orthogonal projection to latent structures solution properties for chemometrics and systems biology data[J]. J Chemom, 2011, 25(9):514
[21] YIN S, WANG G, GAO H. Data-driven process monitoring based on modified orthogonal projections to latent structures[J]. IEEE Trans Control Syst Technol, 2016, 24(4):1480
