Abstract
The lack of stringent regulations regarding raw materials for herbal supplements used for medicinal purposes has been a constant challenge in the industry. Ginkgo biloba L. leaf extracts attract consumers because of the supposed positive effect on mental performance and memory. Supplements are produced using dried leaf materials and standardized leaf extracts such as EGb 761. Adulteration of Ginkgo biloba L. plants and extracts are becoming more and more common practice due to economically driven motivation from increasing demand in the market and the high cost of raw materials and production. Reinforcement in quality control (QC) to avoid adulterations is necessary to ensure the efficacy of the supplements. In this study, liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was used with principal component analysis (PCA) as an unsupervised exploratory method to analyze, identify, and evaluate the adulterated Ginkgo biloba L. plant materials and dried leaf extracts using the PCA scores and loadings obtained and compound identification.





Similar content being viewed by others
References
van Beek TA. Volume 12: Ginkgo biloba. In: Hardman R, editor. Medicinal and aromatic plants - industrial profiles. Amsterdam: Harwood Academic Publishers; 2006. p. 1–523.
van Beek TA, Montoro P. Chemical analysis and quality control of Ginkgo biloba leaves, extracts, and phytopharmaceuticals. J Chromatogr A. 2009;1216:2002–32.
Demirezer LÖ, Büyükkaya A, Uçaktürk E, Kuruüzüm-Uz A, Güvenalp Z, Palaska E. Adulteration determining of pharmaceutical forms of Ginkgo biloba extracts from different international manufacturers. Rec Nat Prod. 2014;8(4):394–400.
Liu XG, Wu SQ, Li P, Yang H. Advancement in the chemical analysis and quality control of flavonoid in Ginkgo biloba. J Pharm Biomed Anal. 2015;113:212–25.
Rimmer CA, et al. Characterization of a suite of ginkgo-containing standard reference materials. Anal Bioanal Chem. 2007;389(1):179–96.
Ding XP, Qi J, Chang YX, Mu LL, Zhu DN, Yu BY. Quality control of flavonoids in Ginkgo biloba leaves by high-performance liquid chromatography with diode array detection and on-line radical scavenging activity detection. J Chromatogr A. 2009;1216(11):2204–10.
López-Gutiérrez N, Romero-González R, Vidal JLM, Frenich AG. Quality control evaluation of nutraceutical products from Ginkgo biloba using liquid chromatography coupled to high resolution mass spectrometry. J Pharm Biomed Anal. 2016;121:151–60.
Gafner S. Adulteration of Ginkgo biloba leaf extract. Bot Adulterants Bull. 2018:1–8.
Chandra A, et al. Qualitative categorization of supplement grade Ginkgo biloba leaf extracts for authenticity. J Funct Foods. 2011;3(2):107–14.
Ma YC, et al. An effective identification and quantification method for Ginkgo biloba flavonol glycosides with targeted evaluation of adulterated products. Phytomedicine. 2016;23(4):377–87.
Wohlmuth H, Savage K, Dowell A, Mouatt P. Adulteration of Ginkgo biloba products and a simple method to improve its detection. Phytomedicine. 2014;21(6):912–8.
Tokalıoglu S. Determination of trace elements in commonly consumed medicinal herbs by ICP-MS and multivariate analysis. Food Chem. 2012;134:2504–8.
Zhao L, et al. Determination of total flavonoids contents and antioxidant activity of Ginkgo biloba leaf by near-infrared reflectance method. Int J Anal Chem. 2018;2018:1–7.
Harnly JM, Luthria D, Chen P. Detection of adulterated ginkgo biloba supplements using chromatographic and spectral fingerprints. J AOAC Int. 2012;95(6):1579–87.
Li C-Y, Lin C-H, Wu C-C, Lee K-H, Wu T-S. Efficient 1 H nuclear magnetic resonance method for improved quality control analyses of Ginkgo constituents. J Agric Food Chem. 2004;52:3721–5.
Agnolet S, Jaroszewski JW, Verpoorte R, et al. 1H NMR-based metabolomics combined with HPLC-PDA-MS-SPE-NMR for investigation of standardized Ginkgo biloba preparations. Metabolomics. 2010;6:292–302.
Commiso M, Strazzer P, Toffali K, Stocchero M, Guzzo F. Untargeted metabolomics: an emerging approach to determine the composition of herbal products. Comput Struct Biotechnol J. 2013;4(5):1–7.
Katajamaa M, Miettinen J, Orešič M. Processing methods for differential analysis of LC/MS profile data. BMC Bioinforma. 2006;22(5):634–6.
Pluskal T, Castillo S, Villar-Briones A, Orešič M. MZmine 2: modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data. BMC Bioinforma. 2010;11:395.
Myers OD, Sumner SJ, Li S, Barnes S, Du X. One step forward for reducing false positive and false negative compound identifications from mass spectrometry metabolomics data: new algorithms for constructing extracted ion chromatograms and detecting chromatographic peaks. Anal Chem. 2017;89:2.
MZmine Development Team. MZmine 2.3 Manual. 2005–2011. http://mzmine.sourceforge.net/manual.pdf. Accessed 28 Nov 2019
R Core Development Team. R: A language and environment for statistical computing. In: R Foundation for Statistical Computing, Vienna, Austria. 2013. http://www.R-project.org/. Accessed 30 Jul 2019
Cruz MB. Determination of the authenticity of Ginkgo biloba L. plant part materials and dry leaf extracts using different analytical methods and chemometric techniques [master’s thesis]. Gdansk: Gdansk University of Technology; 2019.
Wang F, Jiang K, Li Z. Purification and identification of Genistein in Ginkgo biloba leaf extract. Chin J Chromatogr. 2007;25(4):509–13.
Pandey R, Chandra P, Arya KR, Kumar B. Development and validation of an ultra high performance liquid chromatography electrospray ionization tandem mass spectrometry method for the simultaneous determination of selected flavonoids in Ginkgo biloba. J Sep Sci. 2014;37(24):3610–8.
Yao JB, et al. Seasonal variability of genistein and 6-hydroxykynurenic acid contents in Ginkgo biloba leaves from different areas of China. Nat Prod Commun. 2017;12(8):1241–4.
van den Berg RA, Hoefsloot H-CJ, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics. 2006;7:142.
Eigenvector Research Documentation. Advanced Preprocessing: Variable Centering - Eigenvector Documentation Wiki. http://wiki.eigenvector.com/index.php?title=Advanced_Preprocessing:_Variable_Centering. Accessed 18 Apr 2019
Acknowledgments
This project was part of a research master thesis supported by the Education, Audiovisual, and Culture Executive Agency (EACEA) under the program Erasmus Mundus Masters in Quality in Analytical Laboratories (EMQAL 10th edition), Gdansk University of Technology (GUT), and its collaboration with the National Institute of Standards and Technology (NIST Gaithersburg, USA) and the National Institute of Metrology, Quality and Technology (INMETRO Brazil). This project would not be possible without the help and overwhelming support of NIST and GUT supervisors, colleagues, and program coordinators.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Certain commercial equipment, instruments, or materials may be identified in this report to adequately specify the experimental procedure. Such identification does not imply recommendation or endorsement by the National Institute of Standards and Technology, nor does it imply that the materials or equipment identified are necessarily the best available for the purpose.
To obtain up-to-date official values for NIST reference materials, consult the NIST Standard Reference Material web site at https://www.nist.gov/srm.
Electronic supplementary material
ESM 1
(PDF 523 kb)
Rights and permissions
About this article
Cite this article
Cruz, M.B., Place, B.J., Wood, L.J. et al. A nontargeted approach to determine the authenticity of Ginkgo biloba L. plant materials and dried leaf extracts by liquid chromatography-high-resolution mass spectrometry (LC-HRMS) and chemometrics. Anal Bioanal Chem 412, 6969–6982 (2020). https://doi.org/10.1007/s00216-020-02830-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00216-020-02830-2


