pp. 785-795
S&M1238 Research Paper https://doi.org/10.18494/SAM.2016.1312 Published: July 27, 2016 Automatic Evaluation of Sensory Information for Beer at a Fuzzy Level Using Electronic Tongue and Electronic Nose [PDF] Jingjing Liu, Jialin Yang, Wei Wang, Songlin Fu, Yan Shi, and Hong Men (Received December 13, 2015; Accepted March 1, 2016) Keywords: electronic tongue, electronic nose, sensory evaluation of beer, cloud model, fuzzy neural network
The 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.
Corresponding author: Hong MenCite this article Jingjing Liu, Jialin Yang, Wei Wang, Songlin Fu, Yan Shi, and Hong Men, Automatic Evaluation of Sensory Information for Beer at a Fuzzy Level Using Electronic Tongue and Electronic Nose, Sens. Mater., Vol. 28, No. 7, 2016, p. 785-795. |