An optimized industry processing technology of peanut tofu and the novel prediction model for suitable peanut varieties

Abstract

Peanut protein is easily digested and absorbed by the human body, and peanut tofu does not contain flatulence factors and beany flour. However, at present, there is no industrial preparation process of peanut tofu, whereas the quality of tofu prepared by different peanut varieties is quite different. This study established an industrial feasible production process of peanut tofu and optimized the key process that regulates its quality. Compared with the existing method, the production time is reduced by 53.80%, therefore the daily production output is increased by 183.33%. The chemical properties of 26 peanut varieties and the quality characteristics of tofu prepared from these 26 varieties were determined. The peanut varieties were classified based on the quality characteristics of tofu using the hierarchical cluster analysis (HCA) method, out of which 7 varieties were screened out which were suitable for preparing peanut tofu. An evaluation standard was founded based on peanut tofu qualities. Six chemical trait indexes were correlated with peanut tofu qualities (P<0.05). A logistic regressive model was developed to predict suitable peanut varieties and this prediction model was verified. This study may help broaden the peanut protein utilization, and provide guidance for breeding experts to select certain varieties for product specific cultivation of peanut.

Keywords

• peanut tofu
• process
• quality
• peanut variety selection
• evaluation standard
• prediction model