1. Characterization and classification of three common Bambusoideae species in Korea by an HPLC-based analytical platform coupled with multivariate statistical analysis
- Author
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Jong Seong Kang, Yan-Yan Zhao, Yan Zhao, and Yuan Du
- Subjects
0106 biological sciences ,Multivariate analysis ,Chromatography ,biology ,010405 organic chemistry ,Selected reaction monitoring ,biology.organism_classification ,01 natural sciences ,High-performance liquid chromatography ,0104 chemical sciences ,Triple quadrupole mass spectrometer ,Chemotaxonomy ,Chromatography detector ,Phyllostachys nigra ,Pseudosasa japonica ,Agronomy and Crop Science ,010606 plant biology & botany - Abstract
PhyllostacShys bambusoides, Phyllostachys nigra var. henonis, and Pseudosasa japonica are Bambusoideae species widely cultivated in Korea. They are used in herbal medicines due to their potent bioactivities. However, the various chemical compositions of the different Bambusoideae species have not been documented; on the market, all are typically being labeled as bamboo, without species discrimination. Therefore, the present study aimed to evaluate the differences between these three Bambusoideae species based on simultaneous quantitative determination of several compounds. An analysis platform, consisting of ultrasound-assisted liquid-liquid extraction combined with high-performance liquid chromatography equipped with a diode array detector (HPLC-DAD) and a triple quadrupole mass spectrometer in multiple reaction monitoring mode (HPLC-MRM/MS), was developed and validated to analyze the biochemical compounds in these three Bambusoideae species. Multivariate statistical analysis was applied to discriminate samples, data visualization, and identification of sample clustering. As a result, nine compounds were identified as marker compounds for species differentiation. This study demonstrated that the chemotaxonomic application of three common Bambusoideae species could be achieved using our analytical platform coupled with appropriate multivariate statistical analysis. These abilities will help prevent possible side effects and unexpected biological activity resulting from incorrect species identification.
- Published
- 2019
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