Metabolite profiling of soy sauce using gas chromatography with time-of-flight mass spectrometry and analysis of correlation with quantitative descriptive analysis

Journal of Bioscience and Bioengineering

Volumn 114, Issue 2, 2012, Pages 170-175

  Yamamoto, Shinya ^a   Bamba, Takeshi ^a   Sano, Atsushi ^b   Kodama, Yukako ^b   Imamura, Miho ^b   Obata, Akio ^b   Fukusaki, Eiichiro ^a  

^a OSAKA UNIVERSITY   (Japan)

^b KIKKOMAN CORPORATION   (Japan)

Author keywords

Gas chromatography with time of flightmass spectrometry (GC TOFMS); Multivariate analysis; Projection to latent structure; Quantitative descriptive analysis; Sensory analysis; Soy sauce

Indexed keywords

MULTI VARIATE ANALYSIS; PROJECTION TO LATENT STRUCTURES; QUANTITATIVE DESCRIPTIVE ANALYSIS; SENSORY ANALYSIS; SOY SAUCE;

BIOMOLECULES; MASS SPECTROMETRY; METABOLITES; SUGARS;

GAS CHROMATOGRAPHY;

SOY SAUCE; SOYBEAN OIL; UNCLASSIFIED DRUG;

ACCURACY; ARTICLE; CORRELATION ANALYSIS; EXPLANATORY VARIABLE; FOOD ANALYSIS; GAS CHROMATOGRAPHY; HYDROPHILICITY; METABOLITE; MOLECULAR WEIGHT; QUANTITATIVE ANALYSIS; RESPONSE VARIABLE; SENSORY ANALYSIS; SOYBEAN; TIME OF FLIGHT MASS SPECTROMETRY;

FOOD ANALYSIS; GAS CHROMATOGRAPHY-MASS SPECTROMETRY; HUMANS; SOY FOODS; SOYBEANS; TASTE;

EID: 84863204130     PISSN: 13891723     EISSN: 13474421     Source Type: Journal    
DOI: 10.1016/j.jbiosc.2012.03.023     Document Type: Article

References (20)

1. Roling W.F.M., Timotius K.H., Prasetyo A.B., Stouthamer A.H., Vereveld H.W.V. Changes in microflora and biochemical composition during the baceman stage of traditional Indonesian kecap (soy sauce) production. J. Ferment. Bioeng. 1994, 77:62-70.
2. Fukushima D. Soy proteins for foods centering around soy sauce and tofu. J. Am. Oil Chem. Soc. 1981, 58:346-354.
3. Yokotsuka T. Soy sauces. Handbook of indigenous fermented foods 1983, vol. 9:437-451. Marcel Dekker, New York.
4. Koseko, S., Hisamatsu, M., and Yamada, T.: Studies on soy-sauce production by bioreactor: Part 2. Studies on fermentation condition with koji hydrolyzate, The bulletin of the faculty of bioresources, Mie University, 4, 187-196 (1990) (in Japanese).
5. Yoshida H., Mizukoshi T., Hirayama K., Miyano H. Comprehensive analytical method for the determination of hydrophilic metabolites by high-performance liquid chromatography and mass spectrometry. J. Agric. Food Chem. 2007, 55:551-560.
6. Lioe H.N., Apriyantono A., Takara K., Wada K., Yasuda M. Umami taste enhancement of MSG/NaCl mixtures by subthreshold l-α-aromatic amino acids. J. Food Sci. 2005, 70:401-405.
7. Imamura M., Sato T., Hatamoto O. Objective evaluation of the 'mildness' in the soy sauce made of whole soybeans. Jpn. J. Taste Smell Res. 2009, 16:447-450. (in Japanese).
8. Gao X., Cui C., Ren J., Zhao H., Zhao Q., Zhao M. Changes in the chemical composition of traditional Chinese-type soy sauce at different stages of manufacture and its relation to taste. J. Food Sci. Technol. 2011, 46:243-249.
9. Pongsuwan W., Fukusaki E., Bamba T., Yonetani T., Yamahara T., Kobayashi A. Prediction of Japanese green tea ranking by gas chromatography/mass spectrometry-based hydrophilic metabolite fingerprinting. J. Agric. Food Chem. 2007, 55:231-236.
10. Tianniam S., Tarachiwin L., Bamba T., Kobayashi A., Fukusaki E. Metabolic profiling of Angelica acutiloba roots utilizing gas chromatography-time-of-flight-mass spectrometry for quality assessment based on cultivation area and cultivar via multivariate pattern recognition. J. Biosci. Bioeng. 2008, 105:655-659.
11. Hashimoto H., Kobayashi K., Iizuka K., Okada T. Application of near infrared spectroscopy for soy sauce quality control. J. Japan Soy Sauce Res. Ins. 1994, 20:205-212. (in Japanese).
12. Ritthiruangdej P., Suwonsichon T. Relationships between NIR spectra and sensory attributes of Thai commercial fish sauces. Anal. Sci. 2007, 23:809-814.
13. Tsugawa H., Tsujimoto Y., Arita M., Bamba T., Fukusaki E. GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA). BMC Bioinformatics 2011, 12:131.
14. Lommen A. MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing. Anal. Chem. 2009, 81:3079-3086.
15. Williams P.C. Variables affecting near-infrared reflectance spectroscopic analysis. Near infrared technology in the agricultural and food industries 1987, 143-167. American Association of Cereal Chemists, MN. P. Williams, K. Norris (Eds.).
16. Eriksson L., Johansson E. Multi- and megavariate data analysis principles and applications, p. 4370 2001, Umetrics AB, Umeå.
17. Nishimura T., Kato H. Taste of free amino acids and peptides. Food Rev. Int. 1988, 4:175-194.
18. Zittan L. Enzymatic hydrolysis of inulin - an alternative way to fructose production. Starch 1981, 33:373-377.
19. Takagi S., Toko K., Wada K., Yamada H., Toyoshima K. Detection of suppression of bitterness by sweet substance using a multichannel taste sensor. J. Pharm. Sci. 1998, 87:552-555.
20. Maria C.Z., Maria C.G., Mara V.G. Sourness-sweetness interactions in different media: White wine, ethanol and water. J. Sens. Stud. 2006, 21:601-611.