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KMID : 1007520020110030320
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Food Science and Biotechnology
2002 Volume.11 No. 3 p.320 ~ p.323
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Application of the Electronic Nose and Artificial Neural Network System to Quality of the Stored Soymilk
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Park, Eun Young
Kim, Jung Ho/Noh, Bong Soo
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Abstract
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Soymilk was stored at 5, 20, 35, and 50 for 45 days. Quality of soymilk was measured by the electronic nose and its response was described in terms of a sensitivity
(R_gas/R_air). The results showed significant differences in volatile profiles when the soymilk was stored for a given time period. The proportion of the first principal component score in principal component analysis was very high (0.85-0.95) in soymilk. The first principal component score is correlated with the freshness of soymilk. As storage time increased, the principal component analysis plot extended from the right side (positive value of first principal component) through the middle to the left side (negative value). Analysis of soymilk quality was correctly recognized by the artificial neural network at 95.0, 90.0, 97.5, and 86.0% probability level at 5, 20, 35, and 50℃, respectively.
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