문화기술의 융합 (The Journal of the Convergence on Culture Technology)

  • 제8권4호
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  • Pages.355-360
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  • 2022
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  • 2384-0358(pISSN)
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  • 2384-0366(eISSN)
국제문화기술진흥원 (The International Promotion Agency of Culture Technology)
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머신러닝 기반 고춧가루 원산지 판별기법

Detection of Red Pepper Powders Origin based on Machine Learning

  • 유성민 (서울여자대학교 데이터과학전공) ;
  • 박민서 (서울여자대학교 데이터사이언스학과)
  • 투고 : 2022.05.26
  • 심사 : 2022.07.02
  • 발행 : 2022.07.31
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초록

최근 국내산 고추의 생산 비용 상승과 수입산 고추의 도입으로 고춧가루 원산지 허위표기 등의 피해사례가 속출하고 있다. 이에 따라 원산지를 신속하고 정확하게 판별하는 문제가 대두되었다. 기존의 고춧가루 원산지 판별법의 경우 무기 및 유기성분을 실험적으로 대조 및 분석하여 비용과 시간이 많이 든다는 한계가 있다. 이를 보완하기 위해, 본 연구는 머신러닝을 도입하여 국내산, 수입산 고춧가루 분류를 제안한다. 고춧가루에 포함된 53가지 성분에 대하여 머신러닝 모델을 설계하고 검증하였다. 본 연구를 통해 어떠한 성분이 원산지 판별 시 중요하게 활용되는지 파악 할 수 있었다. 추후 고춧가루뿐만 아니라 다양한 식품으로 확장하여 원산지 판별에 드는 비용을 보다 줄일 수 있을 것으로 기대된다.

As the increase cost of domestic red pepper and the increase of imported red pepper, damage cases such as false labeling of the origin of red pepper powder are issued. Accordingly we need to determine quickly and accurately for the origin of red pepper powder. The used method for presently determining the origin has the limitation in that it requires a lot of cost and time by experimentally comparing and analyzing the components of red pepper powder. To resolve the issues, this study proposes machine learning algorithm to classifiy domestic and imported red pepper powder. We have built machine learning model with 53 components contained in red pepper powder and validated. Through the proposed model, it was possible to identify which ingredients are importantly used in determining the origin. In the near future, it is expected that the cost of determining the origin can be further reduced by expanding to various foods as well as red pepper powder.

키워드

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