Evaluation of Rice Tofu Quality Based on Correlation Analysis and Principal Component Analysis

Chemical constituents, texture and color indices of ten commercially available rice tofu samples were determined in this paper. Based on the sensory evaluation, the method combined correlation analysis (CA), principal component analysis (PCA) and hierarchical cluster analysis (HCA) were performed to analyze the correlation between indicators and screen out the indicators to evaluate the quality of rice tofu. These results indicated that chemical composition was not only related to texture of rice tofu, but also had a significant correlation with color. Therefore, the taste and appearance of rice tofu were determined by chemical composition. The PCA results screened out the seven quality indicators to replace the original sixteen indices. Seven quality indicators included the moisture content, starch content, protein content, pH, adhesiveness, chewiness and L^*. The PCA results showed that the accumulated contribution rate of principle components was 84.94%, which could reflect almost all the needed information of the quality on rice tofu. Meanwhile, HCA showed that the ten rice tofu samples were clustered into two categories including fresh varieties and cooking varieties. These methods and results provided the theoretical basis for the establishment of evaluation indices on rice tofu.