Abstract

AbstractA potentiometric electronic tongue (E‐tongue) has been used to determine orange beverages of different brands to assess its recognition ability in beverage detection. Physicochemical indexes related to sensory quality have been measured to find correlation between electrochemical signals and physicochemical indexes of orange beverages. Analysis of variance, correlation analysis and principal component analysis (PCA) have been applied in such data processing. The sensor response signals have been analyzed by canonical discriminant analysis (CDA), cluster analysis (CA), and soft independent modeling of class analogy (SIMCA), and their classification effects have been compared. The results indicate that the E‐tongue has good capability to discriminate different brands of orange beverages based on contents of their taste compounds. The correlation between electrochemical signals and physicochemical indexes is significant, and physicochemical indexes may be applied to explain the results of PCA, CDA, CA and SIMCA. CDA has a better classification effect in three methods.Practical ApplicationsThe detection and control of food quality are important parts in the food industry. Electronic tongue (E‐tongue), as a promising technology, which can provide a simple, rapid and objective determination of food taste quality, is becoming popular in food analysis. This paper focuses on the application of an E‐tongue in the recognition of different brands of beverages and finding the correlation between signals of the E‐tongue and physicochemical indexes of beverages. The feasibility of E‐tongue detection in food analysis is also concerned in our studies. The results presented confirm that the E‐tongue has global discrimination ability, and that there is significant correlation between electrochemical signals and physicochemical indexes of orange beverages. All these results indicate that the E‐tongue may be a potential analysis tool to be applied in food analysis.

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