H-NMR metabolomics-based classification of Japanese sake and comparative metabolome analysis by gas chromatography-mass spectrometry.

Six categories of Japanese sake have been established by the National Tax Agency of Japan. In this system, the rice polishing ratio and the addition of alcohol are the main criteria for classification. The most common nuclear magnetic resonance (NMR) spectrometry method is H-NMR, and has higher throughput than gas chromatography-mass spectrometry (GC-MS) or liquid chromatography-mass spectrometry (LC-MS) analysis due to its short measurement time, easy sample preparation, and high reproducibility. However, owing to the production of dominant ethanol signals, metabolome analyses have not been used for classifying Japanese sake using H-NMR. In this study, a technique to selectively suppress ethanol signals was used to classify Japanese sake by H-NMR, and a model was constructed to predict the rice polishing ratio. The results were compared to those obtained by GC-MS. The suppression of ethanol signals enabled the detection of trace components by H-NMR. In a principal component analysis (PCA) score plot of H-NMR spectra with ethanol signal suppression, PC1 was associated with both the addition of alcohol and the rice polishing ratio. Additionally, the separation of samples observed was similar when PCA score plots of H-NMR and GC-MS data were compared. Similarly, to predict the rice polishing ratio using partial least squares regression analysis, a model was constructed using H-NMR data, and showed nearly similar values for precision and predictive performance with the model constructed using GC-MS data. These results suggest that metabolomic analyses of Japanese sake based on H-NMR spectral patterns may be useful for classification.