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Abstract Herbal medicinal products gain increasing popularity. The growing demand for herbal medicine along with a lack of regulation render herbal products subject to intentional adulteration. The substitution of costly ingredients with unlabelled plant-based fillers of inferior quality has been widely reported. Such fraudulent practices erode consumer trust, but can also pose serious health risks. In this work, 71 herbal medicinal products were randomly purchased from Greek markets and analysed using ITS2 metabarcoding for species identification. The aim was to investigate possible adulterations and assess the efficacy of metabarcoding in plant-based product authentication. Of the 131 detected species in our analyses, 87 were not listed on the product labels. This indicates a high level of adulteration and/or contamination during processing and distribution. Two toxic species, Chelidonium majus and Nicotiana tabacum, were also detected as major ingredients of two herbal mixtures for medicinal purposes. Furthermore, the detection of wheat in eight samples raises concerns for people with gluten intolerance. This study stresses the need for stricter quality control of herbal products. In addition, to overcome the limitations of metabarcoding and augment the approach we used Bar-HRM for the first time as a verification tool. The combination of metabarcoding with species-specific Bar-HRM analysis can enhance the reliability of the results.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 21 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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