董庆利,刘阳泰,苏 亮,王 忻,刘 箐,丁 甜.食源性致病菌单细胞观测与预测的研究进展[J].农业机械学报,2015,46(11):221-229.
Dong Qingli,Liu Yangtai,Su Liang,Wang Xin,Liu Qing,Ding Tian.Progress of Observation and Prediction for Foodborne Pathogen Single Cell[J].Transactions of the Chinese Society for Agricultural Machinery,2015,46(11):221-229.
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食源性致病菌单细胞观测与预测的研究进展   [下载全文]
Progress of Observation and Prediction for Foodborne Pathogen Single Cell   [Download Pdf][in English]
投稿时间:2015-10-10  
DOI:10.6041/j.issn.1000-1298.2015.11.030
中文关键词:  单细胞 食品预测微生物学 随机模型 个体建模方法 风险评估
基金项目:国家自然科学基金资助项目(31271896、31401608)、上海市科委重点支撑资助项目(13430502400)、上海市科委长三角科技联合攻关领域项目(15395810900)和国家食品安全风险评估中心2015年委托项目
作者单位
董庆利 上海理工大学 
刘阳泰 上海理工大学 
苏 亮 国家食品安全风险评估中心 
王 忻 上海理工大学 
刘 箐 上海理工大学 
丁 甜 浙江大学 
中文摘要:微生物在单细胞水平下的生长普遍具有随机性和变异性,同时低菌量污染食品所造成的危害风险亦不可忽视,因此食源性致病菌单细胞的生长观测及预测研究逐渐成为食品预测微生物学及食源性致病菌风险评估的研究热点。在分析现有相关文献的基础上,将目前主要的食源性致病菌单细胞生长观测研究分为间接推断和直接观测两类方法;同时对食源性致病菌单细胞生长预测的模型参数与建模过程进行概述,比较了传统预测微生物的决定模型与微生物单细胞的随机模型二者之间的区别,强调了单细胞生长模型需在随机建模的基础上开展,并通过个体建模方法进一步联系其与所在食品环境之间的关系。最后,分析了食源性致病菌单细胞生长观测与预测的现状,并展望了其未来与食品安全风险评估相结合的发展趋势。
Dong Qingli  Liu Yangtai  Su Liang  Wang Xin  Liu Qing  Ding Tian
University of Shanghai for Science and Technology,University of Shanghai for Science and Technology,China National Center for Food Safety Risk Assessment,University of Shanghai for Science and Technology,University of Shanghai for Science and Technology and Zhejiang University
Key Words:Single cell Food predictive microbiology Stochastic model Individual based method Risk assessments
Abstract:The research on the growth of the foodborne pathogen in the single cell level is popular and necessary for its random and variability, which is different from it in the population level. Based on the related research literatures, the observation methods of the pathogen single cell are summarized as indirect and direct methods. The indirect method is based on the turbidity method and theoretical hypothesis, meanwhile,the direct method is using the optical devices to record the division process of the cells. For the character of the growth in single cell level, the single cell growth prediction model should be built on the stochastic model rather than the deterministic model used in the traditional predictive microbiology. Modelling the stochastic division process by the individual based method makes it possible to explain the relations between the single cell and its living environments. The observation and prediction for foodborne pathogen single cell is the foundation to control the risk of the food with low contamination. Analysis indicates that the pathogen single cell growth prediction tends to be combined with food risk assessment.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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