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Application of Electronic Nose in Discrimination of the Habitat for Black Rice  

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)
Publication Information
Korean Journal of Food Science and Technology / v.34, no.1, 2002 , pp. 136-139 More about this Journal
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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