金属氧化物传感器型电子鼻检测猪肉储藏时间
An investigation was conducted to evaluate the capacity of an electronic metal oxidesemiconductor (MOS)-type nose (e-nose) to classify pork samples with different storagetimes (0–6 d). The effects of the headspace-generation time and pork sample mass onthe response of the e-nose were studied using multivariate analysis of variance and onewayanalysis of variance, respectively. The results showed that the pork sample masshad the most significant effect on the e-nose sensor response, followed by the headspacegenerationtime. The optimum parameters were 10 g of sample mass with 5 min ofheadspace-generation time in a 500 mL vial. After either principal component analysisor linear discriminant analysis, the results showed that the e-nose with the optimumparameters can accurately classify the pork samples stored for 0–6 d. A method using aback propagation neural network was also performed, and 91.43% of the prediction set (with92.86% of the training set) was classified correctly using this model.