TY - JOUR
T1 - Quality prediction of Japanese green tea using pyrolyzer coupled GC/MS based metabolic fingerprinting
AU - Pongsuwan, Wipawee
AU - Bamba, Takeshi
AU - Yonetani, Tsutomu
AU - Kobayashi, Akio
AU - Fukusaki, Eiichiro
PY - 2008/2/13
Y1 - 2008/2/13
N2 - A couple between pyrolyzer and gas chromatography/mass spectrometry (GC/MS) has allowed a fast, simple, and low-cost approach to evaluate a quality of Japanese green tea without any sample preparation or derivatization techniques. Using our method, errors from sample preparation could be avoided since raw samples were directly extracted through the extreme heat of the pyrolyzer. In addition, undesired reactions from expensive derivatizing agents, which are commonly needed to treat the samples before analyzing with GC/MS, could be omitted. In order to illustrate the efficiency of this technique, a set of green tea samples from the Tea contest in 2005 in the Kansai area were used. Projection to latent structure by means of partial least squares (PLS) along with orthogonal signal correction (OSC) was selected to explain the relation between green tea's metabolite profiling and its quality. The quality of the model was validated by testing and comparing the predictive ability to the respective model.
AB - A couple between pyrolyzer and gas chromatography/mass spectrometry (GC/MS) has allowed a fast, simple, and low-cost approach to evaluate a quality of Japanese green tea without any sample preparation or derivatization techniques. Using our method, errors from sample preparation could be avoided since raw samples were directly extracted through the extreme heat of the pyrolyzer. In addition, undesired reactions from expensive derivatizing agents, which are commonly needed to treat the samples before analyzing with GC/MS, could be omitted. In order to illustrate the efficiency of this technique, a set of green tea samples from the Tea contest in 2005 in the Kansai area were used. Projection to latent structure by means of partial least squares (PLS) along with orthogonal signal correction (OSC) was selected to explain the relation between green tea's metabolite profiling and its quality. The quality of the model was validated by testing and comparing the predictive ability to the respective model.
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U2 - 10.1021/jf072791v
DO - 10.1021/jf072791v
M3 - Article
C2 - 18181573
AN - SCOPUS:80051859570
VL - 56
SP - 744
EP - 750
JO - Journal of Agricultural and Food Chemistry
JF - Journal of Agricultural and Food Chemistry
SN - 0021-8561
IS - 3
ER -