Quantitative and chemical fingerprint analysis for quality control of Zingiber zerumbet based on HPTLC combined with chemometric methods. (27th May 2021)

• Record Type: Journal Article
• Authors: Dash, Biswabhusan; Ray, Asit; Sahoo, Ambika; Jena, Sudipta; Singh, Subhashree; Kar, Basudeba; Patnaik, Jeetendranath; Panda, Pratap Chandra; Mohanty, Sujata; Nayak, Sanghamitra
• Is Part Of: Plant biosystems. Volume 155:Number 4(2021)
• Page Start: 711
• Page End: 720
• Publication Date: 2021-05-27
• Subjects: Chromatographic fingerprinting -- hierarchical clustering analysis -- principal component analysis -- zerumbone -- Zingiber zerumbet; Botany -- Periodicals; Biological systems -- Periodicals; Plants -- Periodicals; 581
• DOI: 10.1080/11263504.2020.1779840
• Languages: English
• ISSNs: 1126-3504

Abstract

Abstract: A simple, reliable high-performance thin-layer chromatography (HPTLC) method was developed for chemical fingerprinting of Zingiber zerumbet and quantitative estimation of zerumbone. Thirty-six batches of Z. zerumbet were collected from five eco-regions of eastern India. Zerumbone content varied from 52.4 to 214.6 mg/g (dry weight) in methanolic extract of Z. zerumbet rhizomes. Zerumbone content was in the following order: moist deciduous forests of the lower Gangetic plains > Brahmaputra valley evergreen forest > Odisha semi-evergreen forests > Sundarbans freshwater swamp forests > moist deciduous forest of the eastern highlands. Relative Standard Deviation (RSD) of the relative peak areas (RPA) and relative retention times (RRT) of eight characteristic peaks in repeatability and stability test were <3%, and the fingerprinting method was confirmed to be suitable for Z. zerumbet rhizomes. Chemometric approaches like hierarchical cluster analysis (HCA) and principal component analysis (PCA) were employed to classify Z. zerumbet samples based upon their eco-region. Consistent results were achieved showing Z. zerumbet samples could be effectively grouped according to their eco-region. The PCA loading plots identified three probable chemical markers, which might be useful in discriminating the samples. This combinative approach could be used for quality assessment of Z. zerumbet and for the formulations containing zerumbone.