A voltammetric electronic tongue (VE-tongue) was self-developed to monitor the fermentation, post ripeness and storage processes of set yogurt. Multifrequency rectangular pulse voltammetry (MRPV) and multifrequency staircase pulse voltammetry (MSPV) were applied as potential waveforms, and the 'area method' was applied to extract feature data from the original responses. The ANOVA analysis was performed to evaluate the effects of electrodes and potential waveforms on the electrochemical responses, and the visualization of the Pearson Correlation Coefficient was performed to analyze the correlations among each combination of electrode and potential waveform. Discriminant function analysis worked better than principal component analysis based on the fusion data of MRPV- and MSPV-area data in classifying set yogurts in the stages of fermentation, post-ripeness and storage, respectively. VE-tongue with support vector machine (SVM) worked efficiently and stably in predicting the fermentation time, pH and viscosity of samples during the fermentation process; while the use of VE-tongue and partial least squares regression (PLSR) should be the first choice for the prediction work during the post-ripeness and storage processes. According to the classification and prediction results, the VE-tongue with different potential waveforms was proved a promising tool for monitoring the fermentation, post-ripeness and storage processes of set yogurt. (C) 2017 Elsevier Ltd. All rights reserved.