Abstract
Medicinal plants have a very complex composition with hundreds of chemical components[1]. With the ever-growing market of herbal medicines, the quality control and safety of these products have become an important issue. The currently used analytical methods provided by pharmacopeias can’t provide a comprehensive chemical description of herbal medicines, so recently a chemical profiling method has gained attention[2].
The aim of this study was to determine the opportunities and challenges of chemical profiling of herbal extracts using high-performance liquid chromatography (HPLC) and thin layer chromatography (TLC). Herbal extracts were made from commercially available dried tea samples from four different medicinal plants. Multivariate and similarity analyses were performed both on raw data and data with adjusted retention times.
The main challenge that emerged with HPLC analysis was chromatographic peak shifting, which can be solved by adjusting retention times during data analysis. On average Pearson’s correlation coefficient value grew by about 50% for data with adjusted retention times in comparison with raw data. Also, the quality of principal component analysis (PCA) models was significantly better for chromatograms with adjusted retention times.
Chemical profiling is a promising new method for the analysis of herbal extracts. Future research should be conducted with other chromatographic methods to gain a deeper knowledge of the chemical composition of herbal extracts.
The aim of this study was to determine the opportunities and challenges of chemical profiling of herbal extracts using high-performance liquid chromatography (HPLC) and thin layer chromatography (TLC). Herbal extracts were made from commercially available dried tea samples from four different medicinal plants. Multivariate and similarity analyses were performed both on raw data and data with adjusted retention times.
The main challenge that emerged with HPLC analysis was chromatographic peak shifting, which can be solved by adjusting retention times during data analysis. On average Pearson’s correlation coefficient value grew by about 50% for data with adjusted retention times in comparison with raw data. Also, the quality of principal component analysis (PCA) models was significantly better for chromatograms with adjusted retention times.
Chemical profiling is a promising new method for the analysis of herbal extracts. Future research should be conducted with other chromatographic methods to gain a deeper knowledge of the chemical composition of herbal extracts.
| Original language | English |
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| Pages | 3-4 |
| Publication status | Published - 11 Feb 2022 |
| Event | 80th International Scientific Conference of the University of Latvia - University of Latvia, Riga, Latvia Duration: 11 Feb 2022 → 26 Apr 2022 Conference number: 80 https://www.konference80.lu.lv/lv/ https://www.ergonomika.lv/2022/01/27/latvijas-universitates-80-zinatniska-konference-sekcija-ergonomika-un-darba-vide-industriala-inzenierija/ https://dspace.lu.lv/dspace/handle/7/57012 https://www.konference80.lu.lv/en/ https://www.mf.lu.lv/lv/petnieciba/konferences/international-scientific-conference-on-medicine/ https://medicina.lsmuni.lt/abstracts-of-the-international-scientific-conference-on-medicine-organized-within-the-frame-of-the-80th-international-scientific-conference-of-the-university-of-latvia/ |
Conference
| Conference | 80th International Scientific Conference of the University of Latvia |
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| Abbreviated title | LU |
| Country/Territory | Latvia |
| City | Riga |
| Period | 11/02/22 → 26/04/22 |
| Other | Latvijas Universitātes 80. Starptautiskā zinātniskā konference Sekcija "Molekulārā bioloģija/Molecular biology" 18.02.2022. Sekcija „Ergonomika un darba vide, industriālā inženierija” 18.02.2022. Sekcija “Kritiskās domāšanas iespējas un robežas mūsdienu Latvijā” 03.03.2022. |
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Field of Science*
- 1.4 Chemical sciences
- 3.1 Basic medicine
Publication Type*
- 3.4. Other publications in conference proceedings (including local)