Korean Journal of Food Science and Technology (한국식품과학회지)

Korean Society of Food Science and Technology (한국식품과학회)
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Application of Electronic Nose in Discrimination of the Habitat for Black Rice

전자코를 이용한 검정현미의 산지판별

  • Cho, Yon-Soo (Department of Food and Microbial Technology, Seoul Women's University) ;
  • Han, Kee-Young (Department of Food and Microbial Technology, Seoul Women's University) ;
  • Kim, Jung-Ho (Department of Culinary Art, Seoul Health College) ;
  • Kim, Su-Jeong (National Agricultural Products Quality Management Service) ;
  • Noh, Bong-Soo (Department of Food and Microbial Technology, Seoul Women's University)
  • 조연수 (서울여자 대학교 식품.미생물공학과) ;
  • 한기영 (서울여자 대학교 식품.미생물공학과) ;
  • 김정호 (서울보건대학 조리예술과) ;
  • 김수정 (국립 농산물 품질관리원) ;
  • 노봉수 (서울여자 대학교 식품.미생물공학과)
  • Published : 2002.02.01
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Abstract

The discrimination of the agricultural origin, especially locally produced of imported products such as black rices was investigated by using electronic nose. Volatile components from these products were discriminated by six metal oxide sensors without pretreatment. Pattern recognition was carried out. Principal component analysis showed the differences between imported and locally produced ones. The number of 57 from 69 species of black rices were recognized as locally produced one (83.33%) and 11 from 13 species one (imported black rices) was correctly discriminated. Unknown habitat of black rice could be identified by artificial neural network system whether the imported or not. Also commercial electronic nose (E-nose 5000) that was combined with metal oxide sensor and conducting polymer sensor showed 92.75% (locally produced black rices) and 92.31% (imported one) of discrimination.

검정현미에 내포한 특이한 향기성분을 토대로 수입산 또는 국내산인지의 여부를 전자코로 분석하였다. 주성분 분석 결과 전반적으로 수입산과 국내산의 판별이 뚜렷하게 구별 가능하였다. 또한 인공신경망 분석 프로그램을 이용하여 학습시켜 원산지를 모르는 시료를 분석한 결과 국내산 검정현미가 수입산인지 국내산인지를 구별할 수 있었다. E-Nose 5000을 이용한 결과는 69종의 국내산 검정현미를 국내산으로 판별한 경우가 64종으로 92.75%이었고, 13종의 수입산 검정현미를 수입산으로 판별한 경우는 11종으로 92.31%의 높을 확률로 metal oxide sensor로만 구성된 전자코의 판별정도보다 더 정확하게 구별할 수 있었다.

Keywords

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