ISSN (print) 0914-4935
ISSN (online) 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語


 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.

MYU Research

(proofreading and recording)

(translation service)

The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Copyright(C) MYU K.K.

Beer Taste Detection Based on Electronic Tongue

Hongmei Zhang, Guangyu Zou, Wanru Liu, and Zheng Zhou

(Received November 15, 2019; Accepted April 1, 2020)

Keywords: electronic tongue, beer, principal component analysis (PCA), linear discriminant analysis (LDA), BP neural network

We attempted to detect the five tastes in four different commercially available brands of beer using an electronic tongue and conducted a statistical analysis on their alcohol contents, original wort concentrations, and pH values. Statistical methods, including principal component analysis (PCA), linear discriminant analysis (LDA), and a backpropagation (BP) neural network, were used to identify and classify the four beer brands. According to PCA, in the five taste indicators of the four brands of beer, the contribution rates of the first and second principal components were 56.73 and 34.46% respectively; the beer was oxidized to a certain extent with increasing detection time. The results of LDA confirmed the high sensitivity of the electronic tongue sensors to beer tastes as the four brands were effectively identified by distinguishing the taste differences among them. The results of the BP neural network suggested that its predictive accuracy for the five tastes in the four brands can achieve 100% subject to the conformity between the measured and predicted values. The stepwise regression model established in our study could be effective for accurately predicting the original wort concentration of beer. The determination coefficients of the original wort concentration modeling set and the validation set were 0.99 and 0.96, and the root-mean-square errors were 0.06 and 0.41, respectively. As demonstrated by its high sensitivity in analyzing the tastes of four different beer brands, the electronic tongue can effectively distinguish the taste differences among different beers.

Corresponding author: Hongmei Zhang

Forthcoming Regular Issues

Forthcoming Special Issues

Special Issue on Advanced Materials on Electronic and Mechanical Devices and their Application on Sensors (5)
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)

Special Issue on Advances in Shape Memory Materials
Guest editor, Ryosuke Matsui (Aichi Institute of Technology) and Hiroyuki Miki (Tohoku University)

Special Issue on Sensing Technologies and Their Applications (1)
Guest editor, Rey-Chue Hwang (I-Shou University)
Call for paper

Special Issue on Perceptual Deep Learning in Computer Vision and its Application
Guest editor, Chih-Hsien Hsia (National Ilan University)

Special Issue on Materials, Devices, Circuits, and Analytical Methods for Various Sensors (3)
Guest editor, Chien-Jung Huang (National University of Kaohsiung), Cheng-Hsing Hsu (National United University), Ja-Hao Chen (Feng Chia University), and Wei-Ling Hsu (Huaiyin Normal University)
Conference website

Special Issue on New Trends in Smart Sensor Systems
Guest editor, Takahiro Hayashi (Kansai University)
Call for paper

Copyright(C) MYU K.K. All Rights Reserved.