Planta Med 2013; 79 - P122
DOI: 10.1055/s-0033-1336564

Analytical Investigation of German, Roman and Chinese Chamomile Plant, Oil and Commercial Samples

M Wang 1, B Avula 1, YH Wang 1, J Zhao 1, C Avonto 1, V Raman 1, JF Parcher 1, IA Khan 1, 2, J Zweigenbaum 3
  • 1National Center for Natural Products Research
  • 2Department of Pharmacognosy, School of Pharmacy, University of Mississippi, University, MS 38677, USA
  • 3Agilent Technologies, Inc. Wilmington, DE 19808, USA

Chamomile is generally classified as a member of the Asteraceae family and has been used in a wide variety of products as an important medicinal plant. The three most common types observed in commercial products are German (M. recutita), Roman (A. nobilis) and Chinese (C. morifolium). The present study is based on a GC/MS method in combination with a multivariate statistical analysis to classify different chamomiles. The objective is to ascertain and address the problems of botanical classification and adulteration of chamomiles used in commercial products and dietary supplements. The n-Hexane extracts of these three types of chamomile plant samples showed different chemical profiles (Fig. 1). The major marker compounds identified in German chamomile were seaquiterpenes, their alcohols and oxides, chamazulene, and cis-enyne dicycloether. The principle components of Roman chamomile were esters of butenoic acids (tiglate and angelate) and terpenes. The dominant components in Chinese chamomile were seaquiterpenes. A total of 78 German, Roman and Chinese chamomile samples including authenticated plant samples, oils, teas, commercial products and dietary supplements were analyzed. The GC/MS data were exported to Agilent Mass Profiler Professional (MPP) software, and the spectral data were statistically processed through PCA analysis. Three clusters were observed for German, Roman and Chinese chamomile authenticated samples. A four component model was constructed based on the targeted authenticated plant samples, and all the untargeted commercial products were then evaluated using the developed model. It is concluded that conventional GC/MS combined with multivariate statistical analysis may bring more appropriate results aimed as characterization and may assist the standardization and authentication of traditional medicinal plants.

Acknowledgements: This research was supported by Food and Drug Administration grant numbers 5U01FD004246 and the United States Department of Agriculture, Agricultural Research Service, Specific Cooperative Agreement No. 58 – 6408 – 02 – 1-612. The GC/MS instrumentation for this research was graciously supplied by Agilent Technologies.