Application of Potential Type Electronic Tongue on Milk Discrimination

Four brands of milk based on the potential type electronic tongue are tested by using the principal component analysis (PCA), fuzzy c-means clustering (FCM) algorithm for clustering analysis. Support vector machine (SVM) algorithm is used to forecast category for any brand of milk data, which are extracted from all the data randomly. The results show that potential type electronic tongue can distinguish four brands of milk perfectly, and the forecasting accuracy rate can reach to 100%. Potential type electronic tongue has potential application value in the identification of milk.