摘要
为了尽可能提高在有限营养组分和培养条件下罗伊氏乳杆菌LTR1318的活菌数,本文利用单因素试验、Plackett-Burman试验和最陡爬坡试验筛选出了限制LTR1318生长的三种关键营养组分,以试验得到的活菌数值作为训练样本对RBF径向基人工神经网络进行训练,并结合遗传算法对三种组分和含量进行优化,再将其用于5 L发酵罐,对接种量、温度、初始pH和转速四种条件下的使用效果进行检测。结果表明,低聚果糖,胰蛋白胨和L-半胱氨酸对LTR1318的活菌数起关键作用,最佳添加量分别为10.16 g/L,12.07 g/L和0.65 g/L。此条件下摇瓶培养的最大活菌数为60.33×10^9 CFU/mL。另外,5 L发酵罐上的最佳工艺条件为:接种量4%,温度37℃,初始pH 7.0,转速100 r/min。综合培养组分优化和发酵条件优化下发酵罐培养的活菌数达到91.33×10^9 CFU/mL,比未进行优化时提高了12.69倍。上述结果与目前有关罗伊氏乳杆菌活菌数优化的研究报道对比认为,本成果具有一定的优势,5 L发酵罐培养的活菌数也达到国内外先进水平。该成果对这类益生菌菌株的工业化生产和制品后续开发具有一定的指导作用。
In order to improve the viable cell count of Lactobacillus reuteri LTR1318 under limited nutrient components and culture conditions,single factor experiment,Plackett-Burman design and steepest ascent experience were used to screen out three key nutrient components that limit the growth of LTR1318.Box-Behnken design was used with these three components as factors.The radial basis function(RBF)was trained with the obtained viable cell count samples.The three components and their contents were optimized with genetic algorithm in this work.Furthermore,the four fermentation conditions of inoculum concentration,temperature,initial pH and speed were investigated.The results showed that fructooligosaccharide,tryptone and L-cysteine played a key role in the viable cell count of LTR1318.The optimal addition amounts were 10.16 g/L,12.07 g/Land 0.65 g/L,respectively.Under these conditions,the maximum viable cell count was 60.33×109 CFU/mL.In addition,the optimum technological conditions on the 5 L fermentor were obtained as follows:inoculum concentration of 4%,temperature of 37℃,initial pH of 7.0 and speed of 100 r/min.The number of viable cell reached 91.33×109 CFU/mL under comprehensive optimization of culture components and fermentation conditions,which was 12.69 times higher than that of origin culture.The above results were compared with the current domestic researches on the optimization of the viable count of L.reuteri.It was found that the culture components optimized by RBF artificial neural network coupled with genetic algorithm in this work had better proliferation effect on LTR1318.The culture conditions of the 5 L fermenter showed the superiority of the viable count of L.reuteri as compared with domestic,and high density culture of the strain was realized.The results will provide a certain guideline for the industrial production of related probiotic strains and the subsequent development of products.
作者
潘海博
覃璐琪
梅丽华
饶川艳
聂梦琳
莫明规
李全阳
PAN Hai-bo;QIN Lu-qi;MEI Li-hua;RAO Chuan-yan;NIE Meng-lin;MO Ming-gui;LI Quan-yang(College of Light Industry and Food Engineering,Guangxi University,Nanning 530004,China;Liuzhou Kangxiaole Dairy CO.,Ltd,Liuzhou 545006,China)
出处
《现代食品科技》
EI
CAS
北大核心
2020年第10期59-67,314,共10页
Modern Food Science and Technology
基金
国家自然科学基金项目(31871802)
广西重点研发计划项目(桂科AB18221065)。
关键词
人工神经网络
遗传算法
高密度培养
发酵罐
工艺优化
artificial neural network
genetic algorithms
high cell density
fermentor
optimizationtechnical