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In order to explore the feasibility of using electronic nose substitute for physicochemical indexes to detect the quality information change of fruit, the physicochemical indexes identification method and electronic nose identification method were used for litchi samplings, which were in six different maturing stages (p1, p2, p3, p4, p5 and p6). The physicochemical indexes sampling results showed that fruit diameter, kernel diameter and fruit weight were increased as the fruit matured continuously. During stages of p1—p4, the green and yellow of fruits were continuously deepening, the brightness degree was continuously increasing. During stages of p4—p6, the brightness degree of fruit was increased at first and then decreased, the color was obviously gone red, the yellow was first deepened and then became shallow. After extracting the feature values, the principal component analysis (PCA), linear discriminant analysis (LDA), back propagation neural network (BPNN), simple correlation analysis (SCA) and canonical correlation analysis (CCA) were used for data process. Both results of physicochemical indexes identification method combined with PCA and LDA showed that litchi’s maturing stage can be well identified, and both of their accuracies were 100%. But the distance between stages of p1, p2 and p3 were close when using PCA for analysis, which may be confused in practical classification and identification. However, litchi’s maturing stage cannot be identified when using electronic nose combined with PCA or LDA for identification. When using electronic nose combined with BPNN for classification, the accuracies of train set and test set were 100% and 92%, respectively. SCA results showed that physicochemical indexes had significant correlation with electronic nose sensors’ response except L * value during litchi’s maturing process. CCA results showed that there was significant correlation between the whole physicochemical index set and the whole electronic nose sensors’ response set. Part of physicochemical indexes had significant correlation with the whole electronic nose sensors’ response set. The results proved the feasibility of using physicochemical index identification method and electronic nose identification method for detection of quality information change of fruit. It also provided reference for using electronic nose substitute for physicochemical indexes to detect the quality information change of fruit.