食品科学 ›› 2019, Vol. 40 ›› Issue (1): 313-318.doi: 10.7506/spkx1002-6630-20171221-258

• 专题论述 • 上一篇    下一篇

食源性致病菌生长延滞期建模的研究进展

岳思远1,苏 亮2,任鹏程2,刘阳泰1,王 翔1,刘 箐1,董庆利1,*   

  1. 1.上海理工大学医疗器械与食品学院,上海 200093;2.国家食品安全风险评估中心,北京 100022
  • 出版日期:2019-01-15 发布日期:2019-01-22
  • 基金资助:
    “十二五”国家科技支撑计划项目(2015BAK36B04)

Progress in Modeling of Foodborne Pathogen Growth at Lag Phase

YUE Siyuan1, SU Liang2, REN Pengcheng2, LIU Yangtai1, WANG Xiang1, LIU Qing1, DONG Qingli1,*   

  1. 1. School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China; 2. China National Center for Food Safety Risk Assessment, Beijing 100022, China
  • Online:2019-01-15 Published:2019-01-22

摘要: 基于预测微生物学理论,准确预测食源性致病菌的数量及生长对降低食品安全风险具有重大意义。本文针对近年来国内外食源性致病菌生长延滞期的建模工作,从食源性致病菌延滞期的测定方法和建模方法两方面进行综述。通过分析现有延滞期建模的相关研究,指出目前延滞期建模研究中存在的问题。建议未来应基于微生物生长机理明确延滞期定义,进一步根据延滞期定义改进、创新延滞期测定方法及建模方法,同时量化分析延滞期影响因素并整合延滞期建模。

关键词: 食源性致病菌, 预测微生物, 延滞期

Abstract: Predicting accurately the number and growth of foodborne pathogens based on predictive microbiology is of great significance for reducing food safety risks. The review deals with recent progress in the modeling of foodborne pathogen growth at the lag phase. We present a summary of the commonly used techniques for lag period determination and modelling approaches. After reviewing the previous studies on lag phase modeling, we point out the limitations and we suggest that the lag phase should be redefined based on the microbial growth mechanism. In the future, improved and innovative enumeration techniques and modeling methods will be developed according to the new definition of lag phase. Quantitative analysis and integration into lag phase modeling of the factors influencing the lag phase remain to be conducted.

Key words: foodborne pathogen, predictive microbiology, lag phase

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