Skip to main content
Log in

Discrimination of doenjang samples using a mass spectrometry-based electronic nose and human sensory preference testing

  • Research Article
  • Published:
Food Science and Biotechnology Aims and scope Submit manuscript

Abstract

Doenjang samples were discriminated using a mass spectrometry-based electronic nose (MS-E-nose) and discriminant function analysis (DFA). Human sensory preference testing was performed using the same samples. DFA plots indicated classification of doenjang samples into 3 groups. Samples with high discriminate function (DF) 1 and low DF2 scores contained fewer volatile compounds. Grouping results using the MS-E-nose and human sensory preference testing were compared. Fully mashed doenjang samples with more diverse and intense volatile compounds showed low DF1 and high preference scores. DF2 scores for selected samples showed positive correlations to the amount of sample. The MS-E-nose was a useful tool for discrimination of the aroma of doenjang samples and for confirmation of changes in the aroma intensities of doenjang samples.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Næs T, Solheim R. Detection and interpretation of variation within and between assessors in sensory profiling. J. Sens. Stud. 6: 159–177 (1991)

    Article  Google Scholar 

  2. Buldini PL, Ricci L, Sharma JL. Recent applications of sample preparation techniques in food analysis. J. Chromatogr. A 975: 47–70 (2002)

    Article  CAS  Google Scholar 

  3. Delahunty CM, Eyres G, Dufour JP. Gas chromatography-olfactometry. J. Sep. Sci. 29: 2107–2125 (2006)

    Article  CAS  Google Scholar 

  4. Noh BS. Application of electronic nose for quality control of the high quality and functional components. Korean J. Crop. Sci. 51: 40–54 (2006)

    Google Scholar 

  5. Wilson AD. Diverse applications of electronic-nose technologies in agriculture and forestry. Sensors (Basel) 13: 2295–2348 (2013)

    Article  CAS  Google Scholar 

  6. Marsili RT. SPME-MS-MVA as an electronic nose for the study of off-flavors in milk. J. Agr. Food Chem. 47: 648–654 (1999)

    Article  CAS  Google Scholar 

  7. Pavon JLP, Sanchez MN, Pinto CG, Laespada MF, Cordero BM, Pena AG. Strategies for qualitative and quantitative analyses with mass spectrometry based electronic nose. Trends Anal. Chem. 25: 257–266 (2006)

    Article  Google Scholar 

  8. Drake MA, Gerard PD, Kleinhenz JP, Harper WJ. Application of an electronic nose to correlate with descriptive sensory analysis of aged Cheddar cheese. Lebensm.-Wiss. Technol. 36: 13–20 (2003)

    Article  CAS  Google Scholar 

  9. Bartlett PN, Elliott JM, Gardner JW. Electronic nose and their application in the food industry. Food Technol. 51: 44–48 (1997)

    Google Scholar 

  10. Schaller E, Bosset JO, Escher F. Electronic noses and their application to food. Lebensm.-Wiss. Technol. 31: 305–316 (1998)

    Article  CAS  Google Scholar 

  11. Son HJ, Hong EJ, Ko SH, Choi JY, Noh BS. Identification of vegetable oil-added sesame oil by a mass spectrometer-based electronic nose. Food Eng. Prog. 13: 275–281 (2009)

    Google Scholar 

  12. Hong EJ, Park SJ, Choi JY, Noh BS. Discrimination of palm olein oil and palm stearin oil mixtures using a mass spectrometry based electronic nose. Food Sci. Biotechnol. 20: 809–816 (2011)

    Article  CAS  Google Scholar 

  13. Hong HK, Park HS, Yun DH, Shin HW, Kwon CH, Lee KC. Technical trend of electronic nose system. J. Korean Inst. Electric. Electron. Material Eng. 8: 509–516 (1995)

    Google Scholar 

  14. Lee SJ, Ahn B. Comparison of volatile components in fermented soybean pastes using simultaneous distillation and extraction (SDE) with sensory characterization. Food Chem. 114: 600–609 (2009)

    Article  CAS  Google Scholar 

  15. Chung HY, Fung PK, Kim JS. Aroma impact components in commercial plain sufu. J. Agr. Food Chem. 53: 1684–1691 (2005)

    Article  CAS  Google Scholar 

  16. Hong Y, Jung HJ, Kim HY. Aroma characteristics of fermented Korean soybean paste (doenjang) produced by Bacillus amyloliquefaciens. Food Sci. Biotechnol. 21: 1163–1172 (2012)

    Article  CAS  Google Scholar 

  17. Chang M, Chang HC. Characteristics of bacterial-koji and doenjang (soybean paste) made by using Bacillus subtilis DJI. Korean J. Microbiol. Biotechnol. 35: 325–333 (2012)

    Google Scholar 

  18. Noh BS, Yang YM, Lee TS, Hong HK, Kwon CH, Sung YK. Prediction of fermentation time of Korean style soybean paste by using the portable electronic nose. Korean J. Food Sci. Technol. 30: 356–362 (1998)

    Google Scholar 

  19. Shin JA, Choi SW, Lee KT. Prediction of kimchi aging using electronic nose system. Korean J. Food Preserv. 12: 613–616 (2005)

    Google Scholar 

  20. Ku KH, Kim YJ, Koo YJ, Choi IU. Effect of pre-treated sub-ingredients and deodorization materials on the kimchi smell during fermentation. Korean J. Food Sci. Technol. 31: 1549–1556 (1999)

    Google Scholar 

  21. Lawless HT, Heymann H. Sensory Evaluation of Food, Principles, and Practices. Springer Science Inc., New York, NY, USA. pp. 358–368 (1998)

    Google Scholar 

  22. Lawless HT, Heymann H. Sensory Evaluation of Food, Principles, and Practices. Springer Science Inc., New York, NY, USA. pp. 702–707 (1998)

    Google Scholar 

  23. Yong HU, Lee TS, Kim JS, Baek HH, Noh BS, Lee SJ, Park JT, Shim JH, Li D, Hong IH, Nguyen DHD, Tran PL, Nguyen TLH, Oktavina EF, Kim JW, Kang HK, Park KH. Flavor characteristics of rice-grape wine with starch-hydrolyzing enzymes. Food Sci. Biotechnol. 22: 937–943 (2013)

    Article  CAS  Google Scholar 

  24. Noh BS. Determination of Mixing Ratios in Palm Oleic Triglyceride and Palm Stearic Triglyceride Mixtures Using a Mass Spectrometry Based Electronic Nose. Final Report for the Basic Research Program of the Nongshim’s Youlchon Foundation. Seoul, Korea. pp. 57–80 (2011)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hae-Yeong Kim.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hong, Y., Noh, BS. & Kim, HY. Discrimination of doenjang samples using a mass spectrometry-based electronic nose and human sensory preference testing. Food Sci Biotechnol 24, 31–36 (2015). https://doi.org/10.1007/s10068-015-0005-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10068-015-0005-3

Keywords

Navigation