NATURAL PRODUCT RESEARCH AND DEVELOPMENT ›› 2023, Vol. 35 ›› Issue (2): 271-280.doi: 10.16333/j.1001-6880.2023.2.011

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Optimization of alcohol precipitation process for Glycyrrhiza uralensis polysaccharides based on improved entropy weight method combined with TOPSIS model and BPNN model

HE Bao-feng1,MA Xin-huan2*,MA Zhong-xiang3,WANG Bao-cai3,XU Zhi-wei3,MA Fang-xiong1,YANG Tian-yan1,LI Rong-kun1   

  1. 1Gansu University of Chinese Medicine;2Second Provincial People′s Hospital of Gansu,Lanzhou 730000,China;3Gansu Provincial Hospital of Traditional Chinese Medicine,Lanzhou 730050,China
  • Online:2023-02-28 Published:2023-03-02

Abstract:

Based on the improved entropy weight method combined with TOPSIS model and BPNN modeling,to seek the optimum alcohol precipitation process of Glycyrrhiza uralensis polysaccharides.On the basis of single factor experiment,with concentration ratio,ethanol volume fraction and alcohol precipitation time as influencing factors,saccharides,total polysaccharide,polysaccharide content and extracted amount of G. uralensis polysaccharides as evaluation indexes,using orthogonal design to determine the weight of evaluation index by improved entropy weight method.TOPSIS method and comprehensive scoring method were used to deal with the orthogonal results.The results showed that the data error obtained by TOPSIS method was smaller.The optimum alcohol precipitation process was as follows:concentration ratio was 2.5 mL/g,ethanol volume fraction was 70%,and alcohol precipitation time was 20 h.The comprehensive score obtained by orthogonal design was simulated and optimized by BPNN modeling,the optimal alcohol precipitation process was as follows :the water extract was concentrated to 2 mL/g,the volume fraction of ethanol was adjusted to 67%,and the alcohol precipitation was 24 h.The optimal process verification results show that the comprehensive score error obtained by BPNN modeling was smaller and the process was more stable.The optimal alcohol precipitation process optimized by this method was stable and feasible,which could provide objective basis and new ideas for the further development and utilization of G. uralensis polysaccharides.

Key words: Glycyrrhiza uralensis polysaccharides, orthogonal design, improved entropy weight method, TOPSIS model, BP neural network

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