Pork Freshness Detection Using Optimized Electronic Nose Sensor Array
WANG Zhining1, ZHENG Limin1,2,*, FANG Xiongwu1, YANG Lu1
1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China;
2. Beijing Laboratory of Food Quality and Safety, China Agricultural University, Beijing 100083, China
Abstract：When electronic nose is used for detecting pork freshness, sensor array optimization has a great influence on improving the accuracy by eliminating the negative effects brought about by the redundant information. The initial sensor array was determined by the odor released from pork. Then the sensors with poor repeatability and differentiation were excluded by analysis of variance (ANOVA). By coefficient of variation, minimum cumulation of absolute correlation coefficient and the second principal component of principal component analysis (PCA), an optimized sensor array was selected for the detection of pork freshness. This study adopted stepwise discriminant analysis to optimize features and compare the data before and after optimization by using Bayes discriminant method. Results showed that by sensor optimization and feature optimization, the accuracy was increased from 86.8% to 98.9%. This study indicates that sensor array optimization and feature optimization can greatly improve the detection accuracy of pork freshness.
