Curr. Biotech. ›› 2013, Vol. 3 ›› Issue (2): 137-139.DOI: 10.3969/j.issn.2095-2341.2013.02.11

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Using BP Neural Network and Genetic Algorithm to Optimize the Fermentation Medium of Bacillus thuringiensis

GUO Hui-hui   

  1. Fujian Agriculture and Forestry University, Fuzhou 350002, China
  • Received:2013-02-20 Online:2013-03-25 Published:2013-03-15

基于BP神经网络与遗传算法的苏云金芽胞杆菌发酵优化

郭慧慧   

  1. 福建农林大学, 福州 350002
  • 作者简介:郭慧慧，硕士，主要从事生物农药研究，E-mail: pansyg12@163.com
  • 基金资助:

    国家863计划项目(2011AA10A203);福建省科技厅产学研重点项目(2011N5003);教育厅高校领军人才项目(k8012012a);福建省高校杰出青年科研人才培育计划项目(JA12092)资助。

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Abstract: BP neural network and genetic algorithms methods were used to optimize the fermentation medium of Bacillus thuringiensis. The best fermentation medium is 0.392 8% yeast extract, 0.492 8% corn meal, 2% defatted peanut flour, 0.035% MgSO4·7H2O, 0.025%KH2PO4, 0.049 6% CaCO3. The spore production was 6.3×108/mL under this condition,which was 7.7% higher than that by RSM method.

Key words: Bacillus thuringiensis, BP neural network, genetic algorithm, RSM

摘要： 本文应用BP神经网络与遗传算法优化苏云金芽胞杆菌BRC-ZQL3的发酵培养基,获得最佳发酵培养基配方为:酵母膏0.392 8%,玉米粉0.492 8%,黄豆饼粉2%,MgSO4·7H2O 0.035%,KH2PO4 0.025%,CaCO3 0.049 6%；用其培养的菌株产孢量为6.3×108/mL,与响应优化的结果相比提高了7.7%。

关键词: 苏云金芽胞杆菌, BP神经网络, 遗传算法, 响应面

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