Journal of Food Hygiene and Safety (한국식품위생안전성학회지)

The Korean Society of Food Hygiene and Safety (한국식품위생안전성학회)
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Electronic Sensors and Multivariate Approaches for Taste and Odor in Korean Soups and Stews

전자센서와 다변량 분석을 이용한 국내 국·탕류의 향미 특성 분석

  • Boo, Chang Guk (Department of Food Science, Gyeongnam National University of Science and Technology) ;
  • Hong, Seong Jun (Department of Food Science, Gyeongnam National University of Science and Technology) ;
  • Cho, Jin-Ju (Department of Food Science, Gyeongnam National University of Science and Technology) ;
  • Shin, Eui-Cheol (Department of Food Science, Gyeongnam National University of Science and Technology)
  • 부창국 (경남과학기술대학교 식품과학부) ;
  • 홍성준 (경남과학기술대학교 식품과학부) ;
  • 조진주 (경남과학기술대학교 식품과학부) ;
  • 신의철 (경남과학기술대학교 식품과학부)
  • Received : 2020.07.17
  • Accepted : 2020.08.24
  • Published : 2020.10.30
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Abstract

This is an approach study on the sensory properties (taste and odor) of 15 types of Korean conventional soups and stews using electronic nose and tongue. The relative sensor intensity for the taste components of the samples using electronic tongue was demonstrated. By SRS (sourness) sensor, sogogi-baechuguk (beef and cabbage soup) had the highest rate of 9.0. The STS (saltiness) sensor showed the highest score of 8.2 for ojingeoguk (squid soup). For the UMS (umami) sensor, which identifies savoriness, the sogogi-baechuguk was the highest at 10.1. The SWS (sweetness) sensors showed relatively little difference, with sigeumchi-doenjangguk (spinach and bean paste soup) at the highest of 7.3. According to the BRS sensor, which tests for bitterness, the siraegi-doenjangguk (dried radish green and bean paste soup) was the highest at 7.8. By principal component analysis (PCA), we observed variances of 56.21% in principal component 1 (PC1) and 25.23% in PC2. For each flavor component, we observed -0.95 and -0.20 for factor loading of PC1 and PC2 for SRS sensors, 0.96 and 0.14 for STS sensors, and -0.94 and 0.22 for PC1 and PC2 for UMS sensors, and PC1 and 0.22 for PC1 and PC2 loading for SWS sensors. The similarity between the samples identified by clustering analysis was largely identified by 4 clusters. A total of 25 kinds of volatile compounds in 15 samples were identified, and the ones showing the highest relative content in all samples were identified as ethanol and 2-methylthiophhene. The main ingredient analysis confirmed variances of 28.54% in PC1 and 20.80% in PC2 as a result of the pattern for volatile compounds in 15 samples. In the cluster analysis, it was found to be largely classified into 3 clusters. The data in this study can be used for a sensory property database of conventional Korean soups and stews using electronic sensors.

본 연구는 전자코와 전자혀 시스템을 이용한 15가지 국내 식품에 대한 맛과 향에 대한 기본 접근 연구를 진행하였다. 먼저 전자혀 시스템을 이용한 샘플의 맛 성분에 대해 상대적인 센서 강도를 제시하였다. 신맛으로 대표되는 SRS 센서에서는 소고기배추국이 가장 높은 9.0을 나타내었고, 미역국에서 가장 낮은 3.7을 나타내었다. 짠맛으로 대표되는 STS 센서는 오징어국에서 가장 높은 8.2를 나타내었고, 소고기배추국이 가장 낮은 1.9를 나타내었다. 감칠맛으로 확인되는 UMS 센서의 경우 소고기배추국이 가장 높은 10.1을 보였고, 달걀국이 가장 낮은 3.3을 나타내었다. 단맛에 관여하는 SWS 센서에서는 비교적 큰차이를 보이지 않았는데, 시금치된장국이 가장 높은 7.3을 나타내었고, 달걀국이 가장 낮은 4.6을 나타내었다. 마지막으로 쓴맛에 기여하는 BRS 센서에서는 시래기 된장국이 가장 높은 7.8을 나타내었으며, 햄김치찌개에서 가장 낮은 4.4를 보였다. 주성분 분석을 통해 5가지 맛 성분과 15가지 샘플에 대한 패턴을 확인한 결과 PC1에서 56.21%의 variance를 확인하였고, PC2에서 25.23%의 variance를 확인할 수 있었다. 각 맛 성분의 경우 SRS 센서의 경우 PC1과 PC2의 factor loading의 경우 -0.95와 -0.20을 나타내었고, STS 센서의 경우 PC1과 PC2의 factor loading의 값이 0.96과 0.14, UMS 센서의 경우 PC1과 PC2의 factor loading의 값이 -0.94와 0.22, SWS 센서의 경우 PC1과 PC2의 factor loading의 값이 0.08과, 0.89, 그리고 BRS 센서의 경우 PC1과 PC2의 factor loading의 값이 0.32와 -0.60을 각각 나타내었다. 군집분석을 통해 확인된 샘플간의 유사도는 크게 4개의 cluster를 확인할 수 있었다. 15가지 샘플에서 확인된 향기성분은 총 25가지 성분이 확인되었고, 모든 샘플에서 상대적으로 가장 높은 함량을 보이는 향기성분은 ethanol과 2-methylthiophene으로 확인되었다. 주성분 분석을 통해 휘발성 향기 성분과 15가지 샘플에 대한 패턴을 확인한 결과 PC1에서 28.54%의 variance를 확인하였고, PC2에서 20.80%의 variance를 확인할 수 있었다. 군집분석의 경우 크게 3개의 cluster로 분류되는 것을 확인할 수 있었다. 이러한 맛과 향에 대한 연구를 통해서 국내 식품에 대한 표준 자료로써의 활용이 가능할 것으로 판단된다.

Keywords

References

  1. Shim, J.W., Molecular biological evaluation of taste. Food Ind. Nutr., 21(1), 1-4 (2016).
  2. Ryu, M.R., Gustation targeting sodium and sugar reduction. Food Sci. Ind., 50(4), 12-23 (2017).
  3. Kim, J.K., Flavors of processed food in heating. Food Ind. Nutr., 6(2), 20-26 (2001).
  4. Lee, J.H., Globalization of Korean food and sensory evaluation. Food Sci. Ind., 46(3), 29-39 (2013).
  5. Majchrzak, T., Wojnowski, W., Dymerski, T., Gebicki, J., Namiesnik, J., Electronic noses in classification and quality control of edible oils: A review. Food Chem., 246, 192-201 (2018). https://doi.org/10.1016/j.foodchem.2017.11.013
  6. Kim, J.S., Jung, H.Y., Park, E.Y., Noh, B.S., Flavor analysis of commercial Korean distilled spirits using an electronic nose and electronic tongue. Korean J. Food Sci. Technol. 48(2), 117-121 (2016). https://doi.org/10.9721/KJFST.2016.48.2.117
  7. Peris, M., Escuder-Gilabert, L., Electronic noses and tongues to assess food authenticity and adulteration. Trend Food Sci. Technol., 58, 40-54 (2016). https://doi.org/10.1016/j.tifs.2016.10.014
  8. Kim, K.H., Park, S.J., Kim, J.E., Dong, H.M., Park, I.S., Lee, J.H., Hyun S.Y., Noh, B.S., Assessment of physicochemical characteristics among different types of pale ale beer. Korean J. Food Sci. Technol., 45, 142-147 (2013). https://doi.org/10.9721/KJFST.2013.45.2.142
  9. Jeon, S.Y., Kim, J.S., Kim, G.C., Choi, S.Y., Kim, S.B., Kim, K.M., Analysis of electronic nose and electronic tongue and sensory characteristics of commercial seasonings. Korean J. Food Cook Sci., 33(5), 538-550 (2017). https://doi.org/10.9724/kfcs.2017.33.5.538
  10. Chung, S.J., Application of various multivariate statistical tools to understand sensory analysis data sets. Food Soc. Food Sci. Tech., 38(1), 15-21 (2005).
  11. Foodsafetykorea, (2020. March 1). Foodsafetykorea. Retrieved from https://www.foodsafetykorea.go.kr
  12. Kim, D.S., Lee, J.T., Hong, S.J., Cho, J.J., Shin, E.C., Thermal coursed effect of comprehensive changes in the flavor/ taste of Cynanchi wilforfii. J. Food Sci., 84(10), 2831-2839 (2019). https://doi.org/10.1111/1750-3841.14797
  13. Hong, S.J., Cho, J.J., Boo, C.G., Youn, M.Y., Lee, S.M., Shin, E.C., Comparison of physicochemical and sensory properties of bean sprout and peanut sprout extracts, subsequent to roasting. J. Korean Soc. Food Sci. Nutr., 49(4), 356-369 (2020). https://doi.org/10.3746/jkfn.2020.49.4.356
  14. Jo, Y.H., Gu, S.Y., Chung, N.H., Gao, Y., Kim, H.J., Jeong, M.H., Jeong, Y.J., Kwon, J.H., Comparative analysis of sensory profiles of commercial cider vinegars from Korea, China, Japan, and US by SPME/GC/MS, E-nose, and Etongue. Korean J. Food Sci. Technol., 48(5), 430-436 (2016). https://doi.org/10.9721/KJFST.2016.48.5.430
  15. Dong, H,M., Moon, J.Y., Lee, S.H., Discrimination of geographical origins of raw ginseng using the electronic tongue. Korean J. Food Sci. Technol., 49(4), 349-354 (2017). https://doi.org/10.9721/KJFST.2017.49.4.349
  16. Park, C.J., Kim, S.D., Oh, S.K., Study on the flavor of garlic extract. Korean J. Food Sci. Technol., 25(6), 593-595 (1993).
  17. Aladalvar, C., Odabasi, A.Z., Demir, N., Balaban, M.O., Shahidi, F., Cadwallader, K.R., Volatiles and flavor of five Turkish hazelnut varieties as evaluated by descriptive sensory analysis, electronic nose, and dynamic headspace analysis/ gas chromatography-mass spectrometry. J. Food Sci., 69(3), SNQ99-SNQ106 (2004). https://doi.org/10.1111/j.1365-2621.2004.tb13382.x
  18. Hong, E.J., Son, H.J., Choi, J.Y., Noh, B.S., Authentication of rapeseed oil using an electronic nose based on mass spectrometry. Korean J. Food Sci. Technol., 43(1), 105-109 (2011). https://doi.org/10.9721/KJFST.2011.43.1.105
  19. Noh, B.S., Analysis of volatile compounds using electronic nose and its application in food industry. Korean J. Food Sci. Technol., 37(6), 1048-1064 (2005).