Automatic Evaluation of Sensory Information for Beer at a Fuzzy Level Using Electronic Tongue and Electronic Nose

Abstract

Keywords: electronic tongue, electronic nose, sensory evaluation of beer, cloud model, fuzzy neural networkThe flavor of beer is an important means of evaluating its quality. Beer flavor is the integrated embodiment of beer smell and taste information. In this work, the automatic evaluation of beer aroma, taste, and overall flavor sensory information was realized by a smell and taste sensor coupling array. First, a cloud model was used to realize the conversion between the descriptive language and the corresponding quantitative numbers in the process of beer sensory evaluation. Next, an electronic nose and an electronic tongue were used to test the quality of beer in terms of smell and taste. Finally, a fuzzy neural network was trained with the characteristic information collected by the sensor coupling array as the input, with a characteristic value generated from the conversion of the cloud model of sensory evaluation as the output. The results from this system are excellent, as the error rate in the overall fuzzy information evaluation of flavor was between 0.0048 and 0.0394.