Taste Analog Perception System Based on Impedance Spectrum Sensor Array and Human-Like Fuzzy Evaluation Cloud Model

The taste of food affects consumers’ preferences, and the detection and analysis of food with complex ingredients are mostly based on artificial sensory evaluation. To avoid the subjectivity of artificial sensory evaluation, it is very effective to develop a taste analog perception system that can complete the detection, analysis, and evaluation of food with complex ingredients. The system includes the data acquisition part and the data processing part. For the data acquisition part, rGO and its composites were selected to modify the screen-printed electrodes to construct a sensor array for obtaining the overall information on the taste characteristics of the tested samples, providing a basis for subsequent comprehensive analysis. For the data processing part, a sensory evaluation model of food taste based on the cloud model is established, and a feature matrix is introduced to realize the taste evaluation of single measurement data. To verify the effectiveness of the developed system for the detection and evaluation of food with complex ingredients, a Chinese liquor with a mature sensory evaluation system was selected as the sample. The evaluation results of the taste analog perception system for Chinese liquor significantly correlate with the artificial sensory evaluation, which indicated that the system can be very close to human perception and the effectiveness for the evaluation of food with complex ingredients. At the same time, the system also showed good stability and repeatability. The taste analog perception system is low cost, miniaturized, and convenient to operate and provides an effective method for simulating the field of human perception.