Optimization of Selenium-enriched Fermentation Conditions for Lactobacillus reuteri Based on BPANN-GA Algorithm
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.
seleniumLactobacillus reuterineural networkoptimization of fermentation conditionsgenetic algorithm
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