|Table of Contents|

Optimization of Polysaccharide Extraction From Ganoderma lucidum of Solid-state Fermentation in Burdock by Genetic Neural Network

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2020年22
Page:
103-108
Research Field:
Publishing date:

Info

Title:
Optimization of Polysaccharide Extraction From Ganoderma lucidum of Solid-state Fermentation in Burdock by Genetic Neural Network
Author(s):
ZHU Huixia1; DONG Yuwei2
(1.College of Management,Liaoning University of Technology,Jinzhou,Liaoning 121001;2.College of Food (Biology) Engineering,Xuzhou Institute of Technology,Xuzhou,Jiangsu 221018)
Keywords:
adaptive genetic neural network algorithm; burdock; Ganoderma lucidum; polysaccharide; regression analysis
PACS:
-
DOI:
10.11937/bfyy.20200663
Abstract:
Burdock and Ganoderma lucidum were used as test materials,a new adaptive genetic neural network algorithm was used to study the optimal process of extracting polysaccharides from Ganoderma lucidum of solid-state fermentation in burdock.The test data of polysaccharide content were used to fit the predictive data of the adaptive genetic neural network algorithm,and the predictive data of the adaptive genetic neural network algorithm were compared with that of the regression analysis method.The results showed that prediction and optimization of the adaptive genetic neural network algorithm was higher than that of the regression analysis method.The optimal theoretical parameters for the polysaccharides extracting from Ganoderma lucidum of solid-state fermentation in burdock by this method was follow,liquid-solid ratio 0.32 mL·g-1,the filling volume 0.18 g·mL-1,the degree of crushing 6.19 mesh sieve,and the maximum of polysaccharide content was 25.13 mg·g-1,which was better than the polysaccharide content of 25.07 mg·g-1 obtained by the regression method.

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Last Update: 2021-02-07