Plant-based meat substitutes by high-moisture extrusion:Visualizing the whole process in data systematically from raw material to the products

High-moisture extrusion technology should be considered one of the best choices for producing plant-based meat substitutes with the rich fibrous structure offered by real animal meat products.Unfortunately,the extrusion process has been seen as a“black box”with limited information about what occurs inside,causing serious obstacles in developing meat substitutes.This study designed a high-moisture extrusion process and developed 10 new plant-based meat substitutes comparable to the fibrous structure of real animal meat.The study used the Feature-Augmented Principal Component Analysis(FA-PCA)method to visualize and understand the whole extrusion process in three ways systematically and accurately.It established six sets of mathematical models of the high-moisture extrusion process based on 8000 pieces of data,including five types of parameters.The FA-PCA method improved the R^(2) values significantly compared with the PCA method.The Way 3 was the best to predict product quality(Z),demonstrating that the gradually molecular conformational changes(Y^(n'))were critical in controlling the final quality of the plant-based meat substitutes.Moreover,the first visualization platform software for the high-moisture extrusion process has been established to clearly show the“black box”by combining the virtual simulation technology.Through the software,some practice work such as equipment installation,parameter adjustment,equipment disassembly,and data prediction can be easily achieved.

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

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.