摘要
为优化罗伊氏乳杆菌(Lactobacillus reuteri)的富硒发酵条件,采用反向传播人工神经网络结合遗传算法(back propagation artificial neural network combined with genetic algorithm,BPANN-GA)来优化罗伊氏乳杆菌的富硒发酵参数。选取培养温度、培养基pH值、硒质量浓度和加入硒的时间为输入变量,以菌体干重为输出变量建立神经网络模型,该模型的拟合优度达到了99.27%。模型建好以后,通过遗传算法对最佳培养参数寻优,选取符合设备条件的近似值进行实验验证,最终确定以菌体干重为目标的最佳培养参数是:温度为36.74℃、培养基pH值为6.56、硒质量浓度为1.43μg/mL、加入硒的时间为培养开始后的5.58 h,在该条件下获得的菌体干重为(13.15±0.03)g/L,其硒转化率为(20.23±0.39)%。且该条件下培养的罗伊氏乳杆菌在模拟胃液中3 h后的存活率为(89.40±0.42)%,在模拟肠液中3、6 h的存活率分别为(96.70±0.39)%、(95.80±0.25)%,具有较高的耐受性。该方法能够实现罗伊氏乳杆菌的富硒发酵条件优化,为相关研究提供理论基础。
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,a biomass dry weight 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.
作者
侯英健
周毅峰
HOU Yingjian;ZHOU Yifeng(College of Biological and Food Engineering,Hubei Minzu University,Enshi 445000,China;Hubei Key Laboratory of Biological Resources Protection and Utilization,Enshi 445000,China)
出处
《湖北民族大学学报(自然科学版)》
CAS
2024年第3期337-342,共6页
Journal of Hubei Minzu University:Natural Science Edition
基金
国家自然科学基金项目(32260070)
湖北省高校优秀青年科技创新团队项目(T2020020)。
关键词
硒
罗伊氏乳杆菌
神经网络
发酵条件优化
遗传算法
selenium
Lactobacillus reuteri
neural network
optimization of fermentation conditions
genetic algorithm
作者简介
第一作者:侯英健(1998-),男,硕士研究生,主要从事富硒微生物资源利用的研究;通信作者:周毅峰(1978-),男,博士,副教授,主要从事植物硒代谢及富硒食品的研究。
