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响应面分析法优化大豆肽发酵培养基
引用本文:李善仁,陈济琛,蔡海松,胡开辉,林新坚. 响应面分析法优化大豆肽发酵培养基[J]. 生物数学学报, 2010, 0(2): 375-382
作者姓名:李善仁  陈济琛  蔡海松  胡开辉  林新坚
作者单位:[1]福建省农业科学院土壤肥料研究所,福建福州350013 [2]福建农林大学生命科学学院,福建福州350002
基金项目:福建省科技重点资助项目(200610009);福建省农业科学科技创新团队建设基金(STIF-Y01)
摘    要:采用响应面分析法对大豆肽发酵培养基进行优化,首先采用二水平Plackett-Burman设计对影响大豆肽发酵的8个因素进行筛选,获得影响最大的3个因素为料水比、MgSO_4、糖蜜.再利用响应面分析法对这3个因素进行优化,确定最佳培养基条件为料水比为1∶1.149、MgSO_4浓度为0.048%、糖蜜浓度为0.294%,在此条件下,优化后的大豆肽含量为21.74%,试验值与模型预测值只有1.21%的误差.

关 键 词:大豆肽  混菌发酵  Plackett-Burman设计  响应面分析法

Optimization of Fermentation Medium for Soybean Peptides by Response Surface Methodology
LI Shan-ren,CHEN Ji-chen,CAI Hai-song,HU Kai-hui,LIN Xin-jian. Optimization of Fermentation Medium for Soybean Peptides by Response Surface Methodology[J]. Journal of Biomathematics, 2010, 0(2): 375-382
Authors:LI Shan-ren  CHEN Ji-chen  CAI Hai-song  HU Kai-hui  LIN Xin-jian
Affiliation:1 The Soil and Fertilizer Institute, Fujian Academy of Agricultural Sciences, Fuzhou Fujian 350013 China) (2 College of Life Science, Fujian Agriculture and Forestry University, Fuzhou Fujian 350002 China)
Abstract:Response Surface Methodology(RSM) was used to study the optimal fermentation medium of soybean peptides. A Plackett-Burman design was undertaken to select 3 important factors from 8 impact factors which affected the content of soybean peptidcs. They were ratio of material to water, MgSO4, Molasses in culture medium.The optimum components obtained by the response surface raethodology were the ratio of material to water 1 : 1.149, MgSO4 0.048%, molasses 0.294%, respectively.Under these conditions,the yield of soybean peptides was 21.74% after the optimization,of which only 1.21% difference from the forecast by RSM.
Keywords:Soybean peptides  Mixed fermentation  Plackett-Burman design  Response surface methodology
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