Skip to main navigation Skip to search Skip to main content

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis

  • Young Hae Choi
  • , Sarah Sertic
  • , Hye Kyong Kim
  • , Erica G. Wilson
  • , Filippos Michopoulos
  • , Alfons W.M. Lefeber
  • , Cornelis Erkelens
  • , Sergio D.Prat Kricun
  • , Robert Verpoorte

Research output: Contribution to journalArticlepeer-review

105 Citations (Scopus)

Abstract

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosa var. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the 1H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina, I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

Original languageEnglish
Pages (from-to)1237-1245
Number of pages9
JournalJournal of Agricultural and Food Chemistry
Volume53
Issue number4
DOIs
Publication statusPublished - 23 Feb 2005

Keywords

  • Arbutin
  • Classification
  • Ilex species
  • Metabolomic analysis
  • NMR
  • Phenylpropanoids
  • Principal component analysis

Fingerprint

Dive into the research topics of 'Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis'. Together they form a unique fingerprint.

Cite this