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

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 x 0.18 mm id x 0.20 microm 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.