文献类型：期刊文献

中文题名：低温贮藏凡纳滨对虾中单增李斯特菌生长预测模型的建立

英文题名：Predicting model of Listeria monocytogenes in Litopenaeus Vannameiat at low temperature

作者：张雪梅[1];张瀛[1];吴雅茜[1];孙力军[1];房志家[1];刘颖[1]

机构：[1]广东海洋大学食品科技学院,广东省水产品加工与安全重点实验室,广东湛江524088

年份：2017

卷号：38

期号：15

起止页码：285

中文期刊名：食品工业科技

外文期刊名：Science and Technology of Food Industry

收录：CSTPCD、、北大核心2014、CSCD_E2017_2018、北大核心、CSCD

基金：广东省科技计划项目(2014A020217018;2014B020205006);国家自然科学基金(31371777;31171634)

语种：中文

中文关键词：低温贮藏;凡纳滨对虾;单增李斯特菌;生长预测模型

外文关键词：low-temperature storage ; Litopenaeus Vannamei ; Listeria monocytogenes ; predictive model

中文摘要：建立低温(-20、0、2、4、6℃)贮藏下凡纳滨对虾中李斯特菌的生长预测模型,为冷藏对虾生产过程中该菌的有效控制提供理论依据。通过origin8.5和DMFit软件分别拟合Logisitic、Sweibull、Gompertz和Baranyi模型,分析R2得出最优一级模型。通过计算得到最大比生长速率(μm)和迟滞期(λ),再分别用Arrhenius方程和回归方程拟合对应的二级模型。结果表明修正的Logisitic模型在5个实验温度下R2均0.98,能够描述低温贮藏下LM的生长动态。采用Arrhenius方程和回归方程构建的二级模型R2分别为0.9903和0.9997,方差分析均为p<0.001,表明温度对最大比生长速率(μm)和迟滞期(λ)均呈现良好的线性关系。在5℃条件下对模型进行验证,得到偏差度Bf=1.0152、准确度Af=1.0798,均在可接受范围,说明建立的生长预测模型有效可靠。

外文摘要：To establish growth predictive model of Listeria monocytogenes in Litopenaeus Vannamei at low temperature of-20,0, 2,4,6 ℃ and to provide the theory basis for the effective control of Listeria monocytogenes at low temperature.The curves were fitted by Logisitic, Sweibull, Gompertz and Baranyi function as primary model by origin8.5 and DMFit software.Then the optimal primary model was determined by the analysis of R^2.The Arrhenius and regression equation were used to fit the the relationship between temperature and the calculated growth rate （μm） and lag- time （k） as secondary model. The results showed that the model of Logisitic was determined as the optimal primary model due to the R2 was higher than 0.98, which can describe the growth dynamic of Listeria monocytogenes at low temperature.The results that the R^2 of Arrhenius was 0.9903 and of regression equation was 0.9997, and the p was lower than 0.001, it showed that the corresponding second order kinetic model of L.monocytogenes was also effective.The prediction model was verified when temperature was 5 ℃ .The bias factor and accuracy factor of prediction model were 1.0152 and 1.0798, respectively.These results proved that the prediction model were valid and reliable.