基于逐步判别分析与BP神经网络的电子鼻猪肉储藏时间预测.pdf

23 10 传 感 技 术 学 报 Vol． 23 No． 10 第 卷 第 期 20 10 10 CHINESE JOURNAL OF SENSORS AND ACTUATORS Oct． 20 10 年 月 * 23 Discrimination of Different Storage Time of Pork by Electronic Nose * HONG Xuezhen ，WANG Jun (Dep artment of Biosystems Engineering ，Zhej iang University ，Hangzhou 310029 ，China) Abstract :In this study ，a rapid detection method based on electronic nose for pork freshness was developed． An electronic nose (E-nose ，PEN 2)was employed to classify pork groups with different storage time (0 ～ 7 d)，42 sam- ples were tested everyday． The mass of each sample was 10 g ，and the headspace-generated time was 5 min． The 60th data from the response of the E-nose was extracted for further analysis． After employing the Linear Discriminant Analysis (LDA)，samples could be well classified according to their storage time． Stepwise Linear Discriminant A- nalysis (Step-LDA)and Back Propagation Neural Network (BPNN)were also employed to predict the storage time of the samples． The result showed that Step-LDA got 100% training accuracy with 97 ． 92% prediction accuracy ，and BPNN got 94 ． 17 % training accuracy with 93． 75% prediction accuracy． This study implied that electronic nose method could be expected to more wildly used on pork freshness detection． Key words :electronic nose ;detection ;Stepwise Linear Discriminant Analysis (Step-LDA);BPNN ;pork EEACC :7230J doi :10． 3969 /j ． issn． 1004 － 1699． 2010． 10． 002 BP 基于逐步判别分析和 神经网络的电子 鼻猪肉储藏时间预测* *