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作 者:刘雪飞[1] 李玉娇[1] 李秀霞[1] 李颖畅[1] 夏文水[2] 孙秀兰[2] 励建荣[1,2]
机构地区:[1]渤海大学食品科学研究院,辽宁省食品安全重点实验室,辽宁锦州121013 [2]江南大学食品学院,江苏无锡214122
出 处:《渤海大学学报(自然科学版)》2014年第4期385-393,共9页Journal of Bohai University:Natural Science Edition
基 金:国家自然科学基金面上项目(No:31471639);"十二五"国家科技支撑计划课题(No:2012BAD29B06);辽宁省食品安全重点实验室开放课题(No:LNSAKF2011031)
摘 要:副溶血性弧菌(Vibrio parahaemolyticus,Vp)是我国食源性疾病的首要致病因素,是海产品上市前的必检微生物.某种意义上讲,检测的增菌时间决定了海产品的质量安全性和市场价值.为缩短增菌时间,采用单因素试验和响应面分析法优化Vp培养条件和增菌培养基.单因素分析确定最适于Vp(ATCC 17802)生长的温度、氧浓度和培养方式分别为37℃、透气胶塞和摇床培养.以混合蛋白胨、牛肉膏、Na Cl为主要影响因素,利用Design-Expert 8.0软件的BoxBehnken设计进行增菌培养基优化,得到的二次回归方程具有很高的拟合性,优化的培养基配方为:酪蛋白胨6.75 g/L、胰蛋白胨3.25 g/L、牛肉膏4.76 g/L、Na Cl 36.75 g/L.利用优化培养基对模型进行验证,培养12 h的Vp菌体密度可达模型最大预测值的98.77%,说明获得的模型可以对ATCC17802的生长动态进行预测和分析.Vibrio parahaemolyticus is a primary causative factor of our country's reported foodborne diseases affecting consumers in food safety and the development of aquaculture seriously. In a sense,the enrichment time determined the shelf life of seafood,which can effect on the quality and market value of seafood. To reduce enrichment time,the single factor tests and response surface methodology was used to optimize culture conditions and enrichment medium of Vibrio parahaemolyticus. Through the single factor analysis,the optimum growth temperature,oxygen concentration and culture mode of Vibrio parahaemolyticus ATCC 17802 were 37°C,breathable rubber plug and shake cultivation respectively. The Vibrio parahaemolyticus enrichment medium was optimized using the Box- Behnken Design of Design- Expert 8. 0 software with mixed peptone,beef extract and Na Cl as the main influence factors. The results showed that the quadratic regression equation had a high fitting degree.The optimal medium formulations as follows: casein peptone 6. 75 g / L,tryptone 3. 25 g / L,beef paste 4. 76 g /L,Na Cl 36. 75 g / L. The optimized medium was used to verify the regression model. Vibrio parahaemolyticus cell density OD600value( 0. 4632) was equivalent to 98. 77% of the maximum predicted value( 0. 46895) of the model after incubation for 12 h. These results indicated that this regression model can be used for prediction and analysis of ATCC17802 growth dynamics.
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