湖北民族大学学报（自然科学版）2024，Vol.42Issue(3)：337-342,6.DOI:10.13501/j.cnki.42-1908/n.2024.06.022
基于BPANN-GA算法的罗伊氏乳杆菌富硒发酵条件优化
Optimization of Selenium-enriched Fermentation Conditions for Lactobacillus reuteri Based on BPANN-GA Algorithm
摘要
Abstract
To optimize the selenium-enriched fermentation conditions for Lactobacillus reuteri,a model was established by using back propagation artificial neural network combined with genetic algorithm(BPANN-GA)to optimize the cultivation parameters.The model was established by selecting cultivation temperature,pH value of the culture medium,selenium concentration,and the time of selenium addition as the input variables with the dry weight of the bacterial cells obtained after drying as the output variable,which achieved a goodness of fit of 99.27%.Subsequently,genetic algorithm was employed for the optimal cultivation parameters.Approximate values that adhere to the equipment specifications were selected for experimental validation.Ultimately,the optimal cultivation parameters,with the objective of achieving maximum biomass dry weight,was determined as follows:a temperature of 36.74℃,a culture medium pH value of 6.56,a selenium concentration of 1.43μg/mL,and the time of selenium addition of 5.58 hours after the initiation of cultivation.Under these specified conditions,abiomassdryweight of(13.15±0.03)g/L was obtained.Its selenium conversion rate was(20.23±0.39)%.Moreover,the Lactobacillus reuteri cultivated under these conditions exhibited a survival rate of(89.40±0.42)%in simulated gastric fluid after 3 hours,and(96.70±0.39)%and(95.80±0.25)%in simulated intestinal fluid after 3 and 6 hours,respectively,demonstrating high tolerance.This method effectively achieves the optimization of selenium-enriched fermentation conditions for Lactobacillus reuteri,providing a theoretical basis for further research on this strain.关键词
硒/罗伊氏乳杆菌/神经网络/发酵条件优化/遗传算法Key words
selenium/Lactobacillus reuteri/neural network/optimization of fermentation conditions/genetic algorithm分类
轻工纺织引用本文复制引用
侯英健,周毅峰..基于BPANN-GA算法的罗伊氏乳杆菌富硒发酵条件优化[J].湖北民族大学学报（自然科学版）,2024,42(3):337-342,6.基金项目
国家自然科学基金项目(32260070) （32260070）
湖北省高校优秀青年科技创新团队项目(T2020020). （T2020020）
