Partial least squares discriminant analysis (PLS?DA) of?fourier transform infrared spectroscopy (FT?IR) metabolic fingerprinting data of?ginseng enables to?differentiate ginseng cultivars, cultivation age of?cultivated/ex vitro and?in?vitro cultured samples

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dc.contributor.authorJ D Lee-
dc.contributor.authorT T Ho-
dc.contributor.authorM S Ahn-
dc.contributor.authorSuk Weon Kim-
dc.contributor.authorH N Murthy-
dc.contributor.authorS Y Park-
dc.date.accessioned2025-05-13T16:32:24Z-
dc.date.available2025-05-13T16:32:24Z-
dc.date.issued2025-
dc.identifier.issn1863-5466-
dc.identifier.urihttps://oak.kribb.re.kr/handle/201005/38096-
dc.description.abstractGinseng (Panax species), are significant medicinal plants, have been utilized worldwide for their nutritional and therapeutic properties throughout history. While traditional cultivated ginseng is typically harvested after 6 years, and harvesting earlier than 6 years possess lower levels of ginsenosides. Recent technological advances have increased the use of in vitro techniques for production of ginseng biomass and ginsenosides via cell and/or adventitious root culture. Here, the metabolic profiles of a range of ginseng samples systems of cultivation ages, cultivars, and culture systems of in vitro-cultured and field cultivated ginseng were examined to determine whether Fourier-transform infrared (FT-IR) spectra combined with multivariate analysis of whole-cell ginseng extracts could be used for high-throughput sample discrimination. In total, 26 ginseng samples belonging to four categories were analyzed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). Dendrograms based on hierarchical cluster analysis (HCA) of the ginseng sample spectral patterns showed that cultivation ages and culture systems were readily clustered into two subgroups in a polysaccharide spectrum-dependent manner. The sample group containing in vitro cell and organ samples was segregated into four subgroups in a nucleic acid spectrum-dependent manner. These results indicated that FT-IR spectroscopy combined with multivariate statistical analysis of in vitro and ex vitro ginseng could be used as an alternative method for metabolite discrimination. Consequently, PLD-DA analysis of FT-IR metabolic fingerprinting data could serve as a valuable tool for screening bioactive compounds and exploring metagenomic relationships in ginseng research.-
dc.publisherSpringer-
dc.titlePartial least squares discriminant analysis (PLS?DA) of?fourier transform infrared spectroscopy (FT?IR) metabolic fingerprinting data of?ginseng enables to?differentiate ginseng cultivars, cultivation age of?cultivated/ex vitro and?in?vitro cultured samples-
dc.title.alternativePartial least squares discriminant analysis (PLS?DA) of?fourier transform infrared spectroscopy (FT?IR) metabolic fingerprinting data of?ginseng enables to?differentiate ginseng cultivars, cultivation age of?cultivated/ex vitro and?in?vitro cultured samples-
dc.typeArticle-
dc.citation.titlePlant Biotechnology Reports-
dc.citation.number2-
dc.citation.endPage166-
dc.citation.startPage157-
dc.citation.volume19-
dc.contributor.affiliatedAuthorSuk Weon Kim-
dc.contributor.alternativeName이종두-
dc.contributor.alternativeNameHo-
dc.contributor.alternativeName안명숙-
dc.contributor.alternativeName김석원-
dc.contributor.alternativeNameMurthy-
dc.contributor.alternativeName박소영-
dc.identifier.bibliographicCitationPlant Biotechnology Reports, vol. 19, no. 2, pp. 157-166-
dc.identifier.doi10.1007/s11816-025-00965-1-
dc.subject.keywordAdventitious root-
dc.subject.keywordDendrogram-
dc.subject.keywordPanax ginseng-
dc.subject.keywordPanax quinquefolius-
dc.subject.keywordPrincipal component analysis-
dc.subject.localAdventitious root-
dc.subject.localadventitious root-
dc.subject.localdendrogram-
dc.subject.localDendrogram-
dc.subject.localPanax ginseng-
dc.subject.localpanax ginseng-
dc.subject.localPrincipal component analysis-
dc.subject.localPrincipal component analysis (PCA)-
dc.subject.localprincipal component analysis-
dc.subject.localprincipal component analysis (PCA)-
dc.subject.localprincipal components analysis-
dc.subject.localPrincipal Component Analysis-
dc.description.journalClassY-
Appears in Collections:
Jeonbuk Branch Institute > Biological Resource Center > 1. Journal Articles
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