Abstract
SummaryThe adulteration of minced mutton was studied by an electronic taste system with cross‐sensitive sensor array, providing a global liquid and taste perception to soluble flavour compounds in meat. The responses of taste sensors to adulterated mutton were collected, and analysed by multivariate data analysis methods. For discrimination of meat species and adulterated mutton with different content of pork/chicken, canonical discriminant analysis (CDA) and bayes discriminant analysis (BDA) and principle component analysis (PCA) were employed. The PCA and CDA results showed that meat of different species could be distinguished by E‐tongue responses. The CDA and BDA results showed effective classification results. For prediction of pork/chicken content in adulterated mutton, Multiple linear regression (MLR), Partial least square analysis (PLS) and Least Squares Support Vector Machines (LS‐SVM) were used, and the results were compared, finding that LS‐SVM was proved to be the most effective method for the prediction of pork/chicken content.
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