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KMID : 1007520020110030245
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Food Science and Biotechnology
2002 Volume.11 No. 3 p.245 ~ p.251
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Prediction of Shelf Life for Soybean Curd by the Electronic Nose and Artificial Neural Network System
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Park, Eun Young
Noh, Bong Soo/Ko, Sang Hoon
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Abstract
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Quality of soybean curd was evaluated using an electronic nose and artificial neural network system. Soybean curd was stored at 5, 15, and 25℃ for 14 days. The freshness of soybean curd was measured by the electronic nose during storage as a sensitivity (R_gas/R_air), which was compared to pH, titratable acidity and total cell counts of soybean curd. As storage time increased, sensitivities of six sensors decreased depending upon storage temperature. The result of the electronic nose showed significant changes in volatile profiles from soybean curds stored for a given period. Correlations between the changes in sensitivity by the electronic nose, pH and titratable acidity were observed. The proportion of first principal component in principal component analysis was very high (0.847-0.971) in soybean curd. The first principal component is correlated with the degree of freshness. 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). The correct probability, which predicted the shelf life of unknown soybean curd samples by artificial neural network analysis were 87.5, 94.0, and 78.0, percents at 5, 15, and 25, respectively. Quality evaluation of soybean product was possible using the electronic nose and artificial neural network system.
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