Fast GC-FID based metabolic fingerprinting of Japanese green tea leaf for its quality ranking prediction

Kanokwan Jumtee, Takeshi Bamba, Eiichiro Fukusaki

Research output: Contribution to journalArticle

37 Citations (Scopus)

Abstract

There is a need of reliable, rapid, and cost-effective analysis technique to evaluate food and crop compositions, which are important to improve their qualities and quantities. Prior to fast GC-FID development, metabolic fingerprints, and predictive models obtained from a conventional GC-FID were evaluated by comparison to those derived from GC-TOF-MS. A similar chromatographic pattern with higher sensitivity of polyphenol compounds including epicatechin gallate (ECg) and epigallocatechin gallate (EGCg) had been achieved by using conventional GC-FID. Fast gas chromatograph coupled with flame ionization detector (GC-FID) has been carried out with 10 m × 0.18 mm id × 0.20 μm df capillary column. The analysis time per sample was reduced to less than 14 min compared to those of a conventional GC-FID (38 min) and GC-TOF-MS (28 min). The fast GC-FID also offered reliable retention time reproducibility without significant loss of peak resolution. Projections to latent structures by means of partial least squares (PLS) with orthogonal signal correction filtering (OSC) was applied to the fast GC-FID data. The predictive model showed good model fit and predictability with RMSEP of 3.464, suggesting that fast GC-FID based metabolic fingerprinting could be an alternative method for the prediction of Japanese green tea quality.

Original languageEnglish
Pages (from-to)2296-2304
Number of pages9
JournalJournal of Separation Science
Volume32
Issue number13
DOIs
Publication statusPublished - Sep 22 2009
Externally publishedYes

Fingerprint

Ionization
Gases
Detectors
Tea
Polyphenols
Crops
Chemical analysis
Costs

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry
  • Filtration and Separation

Cite this

Fast GC-FID based metabolic fingerprinting of Japanese green tea leaf for its quality ranking prediction. / Jumtee, Kanokwan; Bamba, Takeshi; Fukusaki, Eiichiro.

In: Journal of Separation Science, Vol. 32, No. 13, 22.09.2009, p. 2296-2304.

Research output: Contribution to journalArticle

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