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

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.

Keywords

electronic nose;black rice;principal component analysis;artificial neural network

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