Korean journal of food and cookery science (한국식품조리과학회지)

Korean Society of Food and Cookery Science (한국식품조리과학회)
권호 표지

Application of GC-SAW(Surface Acoustic Wave) Electronic Nose to Classification of Origins and Blended Commercial Brands in Roasted Ground Coffee Beans

GC-SAW(Surface Acoustic Wave) 전자코를 활용한 볶은 커피의 원산지 및 배합 커피의 상품별 분류

  • Seo, Han-Seok (Department of Food and Nutrition,Research Institute of Human Ecology, Seoul National University) ;
  • Kang, Hee-Jin (Department of Food and Nutrition,Research Institute of Human Ecology, Seoul National University) ;
  • Jung, Eun-Hee (Department of Food and Nutrition,Research Institute of Human Ecology, Seoul National University) ;
  • Hwang, In-Kyeong (Department of Food and Nutrition,Research Institute of Human Ecology, Seoul National University)
  • 서한석 (서울대학교 식품영양학과,생활과학연구소) ;
  • 강희진 (서울대학교 식품영양학과,생활과학연구소) ;
  • 정은희 (서울대학교 식품영양학과,생활과학연구소) ;
  • 황인경 (서울대학교 식품영양학과,생활과학연구소)
  • Published : 2006.06.30
Download PDF
⟨ Previous Next ⟩

Abstract

The numerous varieties of coffee beans contain a wide range prices and qualities. While the varieties of green coffee beans can generally be distinguished by their appearance, this visual criterion is impossible after the roasting process. Therefore, we need to develop a classification method or device. In this study, the potential of a new type of electronic nose, fast gas chromatography based on a surface acoustic wave sensor(SAW), was evaluated for the classification of origins and blended commercial brands in roasted coffee beans. Eight blended commercial brands and the origins of four similarly roasted ground coffee beans(with no significant difference of color) were rapidly(90 sec/sample) classified. The reproductive results were easily understandable over the aroma image pattern by $VaporPrint^{TM}$. In conclusion, GC-SAW electronic nose can be applied to the classification of origins and commercial brands in roasted ground coffee beans and to e evaluation of the similarities and differences of volatile pattern between samples.

Keywords

References

  1. Aishima T. 1991. Aroma discrimination by pattern recognition analysis of responses from semiconductor gas sensor array. J. Agric. Food Chem 39 : 752-756 https://doi.org/10.1021/jf00004a027
  2. Anderson KA, Smith BW. 2002. Chemical profiling to differentiate geographic growing origins of coffee. J. Agric. Food Chem 50 : 2068-2075 https://doi.org/10.1021/jf011056v
  3. Bicchi CP, Binello AE, Legovich MM, Pellegrino GM, Vanni AC. 1993. Characterization of roasted coffee by S-HSGC and HPLC-UV and principal component analysis. J. Agric. Food Chem 41 : 2324-2328 https://doi.org/10.1021/jf00036a020
  4. Bicchi CP, Ombretta MP, Pellegrino G, Vanni AC. 1997. Characterization of roasted coffee and coffee beverage by solid phase microextraction-gas chromatography and principal component analysis. J. Agric. Food Chem 45 : 4680-4686 https://doi.org/10.1021/jf9704827
  5. Cho YS, Noh BS. 2002. Quality evaluation of dried laver (Porphyra yezoensis Ueda) using electronic nose based on metal oxide sensor or GC with SAW sensor during storage. Korean J. Food Sci. Technol 34(6) : 947-953
  6. Flament I. 1989. Coffee, cacao, and tea. Food Rev. Int 5 : 317-414 https://doi.org/10.1080/87559128909540857
  7. Gardner JW, Shurmer HV, Tan TT. 1992. Application of an electronic nose to the discrimination of coffees. Sensors and Actuators B 6 : 71-75 https://doi.org/10.1016/0925-4005(92)80033-T
  8. Gonzalez AG, Pablos F, Martin MJ, Leon-Camacho M, Valdenebro MS. 2001. HPLC analysis of tocopherols and triglycerides in coffee and their use as authentication parameters. Food Chemistry 73 93-101 https://doi.org/10.1016/S0308-8146(00)00282-X
  9. Illy A, Viani R. 1995. Espresso coffee: The chemistry of quality. Academic Press Inc. San Diego, CA. U.S.A. P 79
  10. Kemsley EK, Ruault S, Wilson RH. 1995. Discrimination between Coffea arabica and Coffea canephora variant robusta beans using infrared spectroscopy. Food Chemistry 54 : 321-326 https://doi.org/10.1016/0308-8146(95)00030-M
  11. Kim G, Lee KJ, Choi KH, Choi DS, Son JR, Kang S, Chang YC. 2004. Odor analysis for beef freshness estimation with electronic nose. J. of Biosystems Eng 29(4) : 317-322 https://doi.org/10.5307/JBE.2004.29.4.317
  12. Kim G, Lee MW, Lee KJ, Choi CH, Noh KM, Kang S, Chang YC. 2005. Identification of salmonella pathogen using electronic nose. J. of Biosystems Eng 30(2) : 121-126 https://doi.org/10.5307/JBE.2005.30.2.121
  13. Kunert M, Biedermann A, Koch T, Boland W. 2002. Ultrafast sampling and analysis of dfvolatiles by a handheld miniaturised GC with pre-concentration unit. J. Sep. Sci 25 : 677-684 https://doi.org/10.1002/1615-9314(20020701)25:10/11<677::AID-JSSC677>3.0.CO;2-5
  14. Lammertyn J, Veraverbeke EA, Irudayaraj J. 2004. zNose technology for the classification of honey based on rapid aroma profiling. Sensors and Actuators B 98 : 54-62 https://doi.org/10.1016/j.snb.2003.09.012
  15. Marcone MF. 2004. Composition and properties of Indonesian palm civet coffee(Kopi Luwak) and Ethiopian civet coffee. Food Research International 37 : 901-912 https://doi.org/10.1016/j.foodres.2004.05.008
  16. Martin MJ, Pablos F, Gonzalez AG. 1998a. Characterization of arabica and robusta roasted coffee varieties and mixture resolution according to their metal content. Food Chemistry 66 : 365-370 https://doi.org/10.1016/S0308-8146(99)00092-8
  17. Martin MJ, Pablos F, Gonzalez AG. 1998b. Discrimination between arabica and robusta roasted coffee varieties according to their chemical composition. Talanta 46 : 1259-1264 https://doi.org/10.1016/S0039-9140(97)00409-8
  18. Martin MJ, Pablos F, Gonzalez AG, Valdenebro MS, Leon-Camacho M. 2001. Fatty acid profiles as discriminant parameters for coffee varieties differentiation. Talanta 54 : 291-297 https://doi.org/10.1016/S0039-9140(00)00647-0
  19. Mayer F, Czerny M, Grosch W. 1999. Influence of provenance and roast degree on the composition of potent odorants in Arabica coffees. Eur Food Res Technol 209(3-4) : 242-250 https://doi.org/10.1007/s002170050487
  20. Nehlig A. 1999. Are we dependent upon coffee and caffeine? A review on human and animal data. Neuroscience & Biobehavioral Reviews 23 : 563-576 https://doi.org/10.1016/S0149-7634(98)00050-5
  21. Nijssen LM, Visscher CA, Maarse H, Willemsens LC, Boelens MH. 1996. Volatile compounds in food qualitative and quantitative data. TNO Nutrition and Food Research Institute. Zeist, Netherlands. p 72
  22. Noh BS, Oh SY, Kim SJ. 2003. Pattern analysis of volatile components for domestic and imported Angelica gigas Nakai using GC based on SAW sensor. Korean J. Food Sci. Technol 35(1) : 144-148
  23. Noh BS. 2005. Analysis of volatile compounds using electronic nose and its application in food industry. Korean J. Food Sci. Technol 37(6) : 1048-1064
  24. Oh SY, Noh BS. 2003. Pattern analysis of volatile components for domestic and imported Cnidium officinale using GC based on SAW sensor, Korean J. Food Sci. Technol 35(5) : 994-997
  25. Pardo M, Niederjaufner G, Benussi G, Comini E, Faglia G, Sberveglieri G, Holmberg M, Lundstrom, I. 2000. Data preprocessing enhances the classification of different brands of espresso coffee with an electronic nose. Sensors and Actuators B 69 : 397-403 https://doi.org/10.1016/S0925-4005(00)00499-8
  26. Schaller E, Basset JO, Escher F. 1998. 'Electronic Noses' and their application to food. Lebensm.-Wiss. u.-Technol 31 : 305-316 https://doi.org/10.1006/fstl.1998.0376
  27. Schenker S, Handschin S, Frey B, Perren R, Escher F. 2000. Pore structure of coffee beans affected by roasting conditions. J Food Sci 65(3) : 452-457 https://doi.org/10.1111/j.1365-2621.2000.tb16026.x
  28. Schenker S, Heinemann C, Huber M, Pompizzi R, Perren R, Escher F. 2002. Impact of roasting conditions on the formation of aroma compounds in coffee beans. J Food Sci 67(1) : 60-66 https://doi.org/10.1111/j.1365-2621.2002.tb11359.x
  29. Schilter B, Cavin C, Tritscher A, Constable A. 2001. Chapter 8 Health effects and safety considerations. pp 165-166. In : Coffee Recent Developments. Clarke RJ, Vitzthum OG (ed). Blackwell Science KK. Tokyo. Japan
  30. Shilbayeh NF, Iskandarani MZ. 2004. Quality control of coffee using an electronic nose system. American J. Appl. Sci 1(2) : 129-135 https://doi.org/10.3844/ajassp.2004.129.135
  31. Staples EJ. 2000. Detecting 2,4,6 TCA in corks and wine using the $zNOSE^{TM}$. Available from: http://www.estcal.com/TechPapers/TCA_in_ Wine.pdf. Accessed September 14, 2000
  32. Staples EJ. 2002. The chemistry of black tea aroma. EST Internal Report. April, 2000
  33. Veraverbeke EA, lrudayaraj J, Lammertyn J. 2005. Fast aroma profiling to detect invert sugar adulteration with $zNOSE^{TM}$. J Sci Food Agric 85 : 243-250 https://doi.org/10.1002/jsfa.1961
  34. Youn AR, Han KY, Oh SY, Noh BS. 2005. Prediction of rancidity for the heated rapeseed oil using the electronic nose. Food Engineering Progress 9(4) : 309-319