The present study investigated the use of the cyclic voltammetric electrochemical method and the electronic tongue (e-tongue) method for detecting of adulteration in lime juice. Since the measurement of the citric acid content in lime juice is an accepted indicator of the adulteration of lime juice in laboratories, it was first tried to determine its concentration using a potentiostat device and the cyclic voltammetry method for which various electrodes including glassy carbon, graphite, gold, and carbon nanotube and gold nanoparticle-modified glassy carbon electrodes, were used. Different conditions were considered by testing citric acid at multiple concentrations in buffers with different pHs. The results showed that the electrochemical behavior of citric acid was weak, so conventional electrochemical methods could not be used to check its behavior. The second part, evaluated a portable electronic tongue system (e-tongue). Eight samples of adulteration levels (from 5% up to 95%) were created in lemon juice (0, 5, 10, 20, 40, 70, 95, and 100% impurity). Unsupervised models including Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA) and supervised models, including Multilayer Perceptron (MLP) neural networks and Support Vector Machine (SVM) were used. Based on the results, the PCA fingerprint showed good discrimination between adulteration levels. HCA further confirmed this. The results of the analysis of supervised methods showed that the MLP model outperformed the SVM model in predicting fraud levels with a success rate of 99.33% and high correlation coefficients (R2=0.9973 and the RMSE= 0.09). These results show that the proposed system can separate different levels of adulteration in lemon juice and can be used as a taste quality control system.

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