基于BPNN和GA的油脂酵母ZW-25发酵木薯水解液产油脂培养基优化研究

Optimization of medium in fermented cassava hydrolysate by ZW-25 grease yeast based on BPNN and GA

在均匀设计试验的基础上,将BP神经网络和遗传算法结合对油脂酵母ZW-25发酵木薯水解液产油脂的培养基进行了优化,得到的最优培养基配方为:木薯水解液稀释倍数1.0倍,蛋白胨0.6129g/L,NaNO_3 1.8687g/L,KH_2PO_4 1.1406g/L,MgSO_4·7H_2O 0.6379g/L。利用此培养基,在pH 7.0、接种量10%、培养温度25℃、摇床转速100 r/min的条件下将油脂酵母ZW-25振荡培养120h,生物量可达16.18g/L,油脂产量可达3.91g/L,菌株平均油脂含量可达24.17%。试验结果表明,将BP神经网络和遗传算法结合应用于培养基配方的优化是可行的。

On the basis of uniform design experiment,BP neural network and genetic algorithm were combined to optimize the grease medium produced by cassava hydrolysate fermentation using ZW-25. The optimum culture medium formula was ：cassava hydrolysate diluted 1.0 times,peptone 0.6129 g/L,NaNO_3 1.8687 g/L,KH_2PO_4 1.1406 g/L,MgSO_4·7H_2O 0.6379 g/L. ZW-25 was shaken for 120 hours at the speed of 100 r/min,the culture medium was cultured at pH7.0,inoculum 10%,at 25℃ and its biomass could reach to 16.18 g/L,grease production could reach to 3.91 g/L,grease content could reach to 24.17%. The experiment results showed that BP neural network combined with genetic algorithm could be used to optimize culture medium.