Discrimination of preserved licorice apricot using electronic tongue

作者：Tian, Xiaojing; Wang, Jun^*; Zhang, Xi

来源：Mathematical and Computer Modelling, 2013, 58(3-4): 737-745.

DOI：10.1016/j.mcm.2012.12.034

• Electronic tongue
• Pattern recognition
• Physicochemical parameter
• Preserved licorice apricot

Fast recognition and characterization of preserved licorice apricot were studied by electronic tongue. The E-tongue signals were analyzed by pattern recognition techniques. Five brands of preserved licorice apricot were discriminated with strong convergence by pattern recognition techniques, Principal Component Analysis, Canonical discriminant Analysis and Cluster Analysis. The characterization of the samples obtained by Back-Propagation Neural Network (BPNN) and Partial Least Squares regression (PLSR) were 100% accurate both for training and test set, and the highest correlation between observed and predicted values was obtained for aerobic plate count, (0.9943, 0.9951) followed by total sugar content (0.9941, 0.9853), content of sodium chloride (0.9926, 0.9902), sulfur dioxide residues (0.9894, 0.9928) with BPNN method. All pattern recognition methods performed for the characterization and classification showed the potential of E-tongue as a rapid tool in the analysis and characterization of preserved fruits.

• 出版日期2013-8
• 单位西北民族大学; 浙江大学