响应面法优化啤酒有害菌检测培养基

Optimization of medium for detection of beer spoilage bacteria by response surface analysis

为了提高啤酒有害菌的检出率和检测的灵敏性,采用Plackett-Burman设计法和响应面分析法(Response Surface Analysis)对CNFF-A培养基组分和配比进行优化。先用Plackett-Burman设计从7个因子中筛选出对菌落数有显著影响的因素,再用最陡爬坡试验及Box-Behnken设计进一步优化。结果表明,蜂蜜、叶酸和乙酸钠是影响菌落数的显著因素,优化后的培养基配方为:蜂蜜0.1g/L、牛肉浸粉7.0g/L、酵母浸出物5.0g/L、精氨酸1.0g/L、叶酸2.0g/L和乙酸钠1.5g/L。此条件下,培养基对啤酒有害菌的检出率大大提高,且检测时间缩短了24h。

In order to enhance the detection limit of beer spoilage bacteria and the sensitivity of the medium,Plackett-Burman method and response surface analysis are used to optimize the ingredient and ratio of the medium.Seven factors were choosed and the significant elements were screened by Plackett-Burman design.The results indicated that honey,folic acid and sodium acetate were significant factors influencing the number of colonies.The optimized formula of the medium was as follows： honey 0.1g/L,beef powder 7.0g/L,yeast extract 5.0g/L,L-arginine 1.0g/L,folic acid 2.0g/L and sodium acetate 1.5g/L.On these conditions,detection limit of beer spoilage bacteria and the sensitivity of the medium were greatly enhanced,and the testing time was shorten.