Optimization of Sensor Array for Detection of Abalone Freshness Based on Electronic Tongue

Abstract

Considering the shortcomings of traditional detection methods of abalone freshness, such as cumbersome operation and low accuracy, this study established a rapid detection method of abalone freshness by using an electronic tongue. A sensor array consisting of eight inert metal electrodes (Au, Pd, Pt, Ag, Ti, Al, Ni, W) was used for detection. However, the detection data of redundant sensors will affect the efficiency and accuracy of detection, so the sensor array needs to be optimized. The original sensor array consisting of eight inert metal electrodes was used to detect four kinds of abalone meat (refrigerated at 4℃ for 1 day, 4 days, 7 days and 10 days) with different freshness. The detection data were analyzed by one-way analysis of variance. According to the analysis results, Al and Pt electrodes with poor stability and differentiation were eliminated. Multiple comparative analysis of variance was used to conduct a significant analysis of the data of the remaining six electrodes. According to the significant difference, the electrodes without significant difference were divided into different groups to obtain four combinations. By combining principal component analysis and support vector classification, the performance of the original array composed of eight electrodes and the four groups of sensor arrays obtained after grouping were analyzed, and the most suitable sensor array for abalone freshness detection was selected. The results showed that the group III sensor array composed of Ag, Pd and Ti electrodes had the best effect on the freshness identification of abalone.