Howard, Caroline, Socratous, Eleni, Williams, Sarah, Graham, Eleanor, Fowler, Mark, Scott, Nigel, Bremner, Paul and Slater, Adrian (2012) PlantID – DNA-based identification of multiple medicinal plants in complex mixtures. Chinese Medicine, 7 (1). p. 18. ISSN 1749-8546
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Abstract
Background
An efficient method for the identification of medicinal plant products is now a priority as the global demand increases. This study aims to develop a DNA-based method for the identification and authentication of plant species that can be implemented in the industry to aid compliance with regulations, based upon the economically important Hypericum perforatum L. (St John’s Wort or Guan ye Lian Qiao).
Methods
The ITS regions of several Hypericum species were analysed to identify the most divergent regions and PCR primers were designed to anneal specifically to these regions in the different Hypericum species. Candidate primers were selected such that the amplicon produced by each species-specific reaction differed in size. The use of fluorescently labelled primers enabled these products to be resolved by capillary electrophoresis.
Results
Four closely related Hypericum species were detected simultaneously and independently in one reaction. Each species could be identified individually and in any combination. The introduction of three more closely related species to the test had no effect on the results. Highly processed commercial plant material was identified, despite the potential complications of DNA degradation in such samples.
Conclusion
This technique can detect the presence of an expected plant material and adulterant materials in one reaction. The method could be simply applied to other medicinal plants and their problem adulterants.
Item Type: | Article |
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Subjects: | B300 Complementary Medicine |
Department: | Faculties > Health and Life Sciences > Applied Sciences |
Depositing User: | Ellen Cole |
Date Deposited: | 14 Dec 2012 11:03 |
Last Modified: | 17 Dec 2023 14:03 |
URI: | https://nrl.northumbria.ac.uk/id/eprint/10775 |
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