Gas chromatography/mass spectrometry based component profiling and quality prediction for Japanese sake

• Published in: Journal of bioscience and bioengineering Vol. 118; no. 4; pp. 406 - 414
• Main Authors: MIMURA, Natsuki, ISOGAI, Atsuko, IWASHITA, Kazuhiro, BAMBA, Takeshi, FUKUSAKI, Eiichiro
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier 01.10.2014
• Subjects: Alcoholic Beverages - analysis; Alcoholic Beverages - microbiology; Aspergillus oryzae - physiology; Biological and medical sciences; Biotechnology; Fermentation; Food Analysis - methods; Fundamental and applied biological sciences. Psychology; Gas Chromatography-Mass Spectrometry - methods; Humans; Odorants - analysis; Oryza - chemistry; Oryza - microbiology; Principal Component Analysis; Saccharomyces cerevisiae - physiology; Taste - physiology; Gas chromatography; Metabolomics; Gas chromatography/mass spectrometry; Quality; Prediction; Japanese sake; Structure; Variable importance on projection; Mass spectrometry; Orthogonal projections to latent structures; Sake
• ISSN: 1389-1723; 1347-4421
• DOI: 10.1016/j.jbiosc.2014.04.006

Sake is a Japanese traditional alcoholic beverage, which is produced by simultaneous saccharification and alcohol fermentation of polished and steamed rice by Aspergillus oryzae and Saccharomyces cerevisiae. About 300 compounds have been identified in sake, and the contribution of individual components to the sake flavor has been examined at the same time. However, only a few compounds could explain the characteristics alone and most of the attributes still remain unclear. The purpose of this study was to examine the relationship between the component profile and the attributes of sake. Gas chromatography coupled with mass spectrometry (GC/MS)-based non-targeted analysis was employed to obtain the low molecular weight component profile of Japanese sake including both nonvolatile and volatile compounds. Sake attributes and overall quality were assessed by analytical descriptive sensory test and the prediction model of the sensory score from the component profile was constructed by means of orthogonal projections to latent structures (OPLS) regression analysis. Our results showed that 12 sake attributes [ginjo-ka (aroma of premium ginjo sake), grassy/aldehydic odor, sweet aroma/caramel/burnt odor, sulfury odor, sour taste, umami, bitter taste, body, amakara (dryness), aftertaste, pungent/smoothness and appearance] and overall quality were accurately explained by component profiles. In addition, we were able to select statistically significant components according to variable importance on projection (VIP). Our methodology clarified the correlation between sake attribute and 200 low molecular components and presented the importance of each component thus, providing new insights to the flavor study of sake.