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| Discrimina ion of Storage Time for Pork Using Metal Oxide Semiconductor （MOS）-Type E-Nose | ||||||||||||
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An investigation was conducted to evaluate the capacity of an electronic metal oxide semiconductor （MOS）-type nose （e-nose） to classify pork samples with different storage times （0–6 d）. The effects of the headspace-generation time and pork sample mass on the response of the e-nose were studied using m*riate analysis of variance and oneway analysis of variance, respectively. The results showed that the pork sample mass had the most significant effect on the e-nose sensor response, followed by the headspacegeneration time. The optimum parameters were 10 g of sample mass with 5 min of headspace-generation time in a 500 mL vial. After either principal component analysis or linear discriminant analysis, the results showed that the e-nose with the optimum parameters can accuray classify the pork samples stored for 0–6 d. A method using a back propagation neural network was also performed, and 91.43% of the prediction set （with 92.86% of the training set） was classified correctly using this model. |
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