식품과학과 산업 (Food Science and Industry)

한국식품과학회 (Korean Society of Food Science and Technology)
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스마트-해섭(Smart-HACCP) 적용을 위한 식품안전 검시기술 동향

Current status of food safety detection methods for Smart-HACCP system

  • 임민철 (한국식품연구원 소비안전연구단) ;
  • 우민아 (한국식품연구원 소비안전연구단) ;
  • 최성욱 (한국식품연구원 소비안전연구단)
  • Lim, Min-Cheol (Research Group of Consumer Safety, Korea Food Research Institute) ;
  • Woo, Min-Ah (Research Group of Consumer Safety, Korea Food Research Institute) ;
  • Choi, Sung-Wook (Research Group of Consumer Safety, Korea Food Research Institute)
  • 투고 : 2021.09.10
  • 심사 : 2021.09.25
  • 발행 : 2021.12.31
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초록

식품안전사고는 2009년 이후 해마다 5천건 이상 매년 2%씩 증가하고 있는 추세이며 환경오염 및 농수산물 원산지표시 위반 등이 증가하고 있어 먹거리 안전에 대한 국민 불안은 가중되고 있는 실정이다. 식품안전사고를 예방할 수 있는 가장 좋은 방법은 빨리 검사하는 방법이라고 대부분 알고 있지만 식품생산 및 유통 현장에 분석 비전문가 수준에서 활용할 수 있는 검사기술이 부족한 실정이다. 최근 현장진단기술 중 시료에서 검사까지 가능한 STA 기술을 중심으로 유전자 기반 식중독균을 검사하는 방법에 대해 소개하였다. 사람이 아닌 원격지 무인으로 식품위해인자를 직접적으로 검사하여 식품안전정보를 위변조 없이 생성할 수 있다면 현재의 빅데이터와 인공지능 기술로부터 보다 정확한 위험을 예측할 수 있어 오염원을 관리할 수 있다. 이러한 정보 처리는 현재 클라우드 기술을 이용하여 스마트폰에서도 활용 가능한 수준이기 때문에 영세사업장이나 공공 단체급식 등에 활용 가능할 것으로 판단된다.

Food safety accidents have been increasing by 2% over 5,000 cases every year since 2009. Most people know that the best method to prevent food safety accidents is a quick inspection, but there is a lack of inspection technology that can be used at the non-analytic level to food production and distribution sites. Among the recent on-site diagnostic technologies, the methods for testing gene-based food poisoning bacteria were introduced with the STA technology, which can range from sample to detection. If food safety information can be generated without forgery by directly inspecting food hazard factors by remote, unmanned, not human, pollution sources can be managed by predicting risks more accurately from current big-data and artificial intelligence technology. Since this information processing can be used on smartphones using the current cloud technology, it is judged that it can be used for food safety to small food businesses or catering services.

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참고문헌

  1. KT경제경영연구소, (2017), 한국형 4차산업혁명의 매래, 한스미드어.
  2. Min-Cheol Lim, Sung-Wook Choi, Min-Ah Woo(2020), Sample-toAnswer Technology for On-site Automatic Detection of Food Poisoning Bacteria, Safe food, 15(3), 40-49.
  3. K. Tsougeni, A.S. Kastania, G.D. Kaprou, Michael Eck, Gerhard Jobst, P.S. Petrou & A. Tserepi (2019). A modular integrated lab-on-a-chip platform for fast and highly efficient sample preparation for foodborne pathogen screening. Sensors & Actuators: B. Chemical, 288, 171-179.
  4. Yin, J., Zou, Z., Hu, Z., Zhang, S., Zhang, F., Wang, B. & Mu, Y. (2020). A "sample-in-multiplex-digital-answer-out" chip for fast detection of pathogens. Lab Chip, 20, 979-986. https://doi.org/10.1039/c9lc01143a
  5. Mark, D., Haeberle, S., Roth, G., Von Stetten, F., & Zengerle, R. (2010). Microfluidic lab-on-a-chip platforms: requirements, characteristics and applications. Chem. Soc. Rev., 39, 1153-1182. https://doi.org/10.1039/b820557b
  6. Zhou, Q. J., Wang, L., Chen, J., Wang, R. N., Shi, Y. H., Li, C. H., ... & Zhang, Y. J. (2014). Development and evaluation of a real-time fluorogenic loop-mediated isothermal amplification assay integrated on a microfluidic disc chip (on-chip LAMP) for rapid and simultaneous detection of ten pathogenic bacteria in aquatic animals. Journal of Microbiological Methods, 104, 26-35. https://doi.org/10.1016/j.mimet.2014.06.008
  7. Oh, S. J., Park, B. H., Choi, G., Seo, J. H., Jung, J. H., Choi, J. S., ... & Seo, T. S. (2016). Fully automated and colorimetric foodborne pathogen detection on an integrated centrifugal microfluidic device. Lab Chip, 16, 1917-1926. https://doi.org/10.1039/C6LC00326E
  8. Kim, T. H., Park, J., Kim, C. J., & Cho, Y. K. (2014). Fully Integrated Lab-on-a-Disc for Nucleic Acid Analysis of FoodBorne Pathogens. Anal. Chem., 86, 3841-3848. https://doi.org/10.1021/ac403971h
  9. Sayad, A., Ibrahim, F., Mukim Uddin, S., Cho, J., Madou, M., & Thong, K. L. (2018). A microdevice for rapid, monoplex and colorimetric detection of foodborne pathogens using a centrifugal microfluidic platform. Biosensors and Bioelectronics, 100, 96-104. https://doi.org/10.1016/j.bios.2017.08.060
  10. Trinh, T. N. D. & Lee, N. Y. (2019). A foldable isothermal amplification microdevice for fuchsin-based colorimetric detection of multiple foodborne pathogens. Lab Chip, 19, 1397-1405. https://doi.org/10.1039/c8lc01389f
  11. Sun, Y., Chang, Y., Zhang, Q., & Liu, M. (2019). An Origami Paper-Based Device Printed with DNAzyme-Containing DNA Superstructures for Escherichia coli Detection. Micromachines, 10(8), 531. https://doi.org/10.3390/mi10080531
  12. Fu, Y., Zho, X., & Xing, Da. (2018). Integrated paper-based detection chip with nucleic acid extraction and amplification for automatic and sensitive pathogen detection. Sensors and Actuators B, 261, 288-296. https://doi.org/10.1016/j.snb.2018.01.165
  13. Trinh, K. T. L., Trinh, T. N. D., & Lee, N. Y. (2019). Fully integrated and slidable paper-embedded plastic microdevice for point-of-care testing of multiple foodborne pathogens. Biosensors and Bioelectronics, 135, 120-128. https://doi.org/10.1016/j.bios.2019.04.011
  14. Lim, M. C., Park, J. Y., Park, K., Ok, G., Jang, H. J., & Choi, S. W. (2017). An automated system for separation and concentration of foodborne pathogens using immunomagnetic separation. Food Control, 73, 1541-1547. https://doi.org/10.1016/j.foodcont.2016.11.021
  15. Chen, J., & Park, B. (2018). Effect of immunomagnetic bead size on recovery of foodborne pathogenic bacteria. International Journal of Food Microbiology, 267, 1-8. https://doi.org/10.1016/j.ijfoodmicro.2017.11.022
  16. Park, J. Y., Lim, M. C., Park, K., Ok, G., Chang, H. J., Lee, N., & Choi, S. W. (2020). Detection of E. coli O157: H7 in food using automated immunomagnetic separation combined with real-time PCR. Processes, 8(8), 908. https://doi.org/10.3390/pr8080908
  17. Can D., Richard B., Estefania C-R., Maria Teresa F-A., Arben M., Andreas M., Gerald A. U., & Firat G. (2019). Disposable sensors in diagnostics, food, and environmental monitoring. Advanced Materials, 31, 1806739 https://doi.org/10.1002/adma.201806739