乙型副伤寒沙门氏菌在鲜切黄瓜中的生长行为及预测模型建立

赵新; 刘娜; 及华; 陈锐; 李洪涛; 朱珠; 李运朝; 兰璞; 王永; 兰青阔

doi:10.13386/j.issn1002-0306.2018.01.013

乙型副伤寒沙门氏菌在鲜切黄瓜中的生长行为及预测模型建立

赵新¹,
刘娜¹,
及华²,
陈锐¹,
李洪涛²,
朱珠¹,
李运朝²,
兰璞¹,
王永¹,
兰青阔^1, ,

1. 天津市农业质量标准与检测技术研究所, 天津 300381;
2. 河北省农林科学院遗传生理研究所, 河北石家庄 050051

基金项目:

天津市农业科技成果转化与推广项目(201703020)

国家农产品质量安全风险评估项目(GJFP201701304)

河北省财政专项(F17R11)。

详细信息

作者简介:
赵新(1983-),女,硕士,助理研究员,研究方向:主要从事农产品病原微生物分子检测技术,E-mail:zhaoxin2008999@126.com。

通讯作者:
兰青阔(1980-),男,硕士,副研究员,研究方向:主要从事农产品安全质量分子检测技术研究,E-mail:lanqingkuo@126.com。

中图分类号: TS251.5
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出版历程
- 收稿日期: 2017-06-15
- 网络出版日期: 2020-12-28
- 刊出日期: 2017-12-31

Mathematical modeling of growth of Salmonella paratyphi B and Staphylococcus aureus in ready-to-eat cucumber slices

1. Tianjin Institute of Agricultural Quality Standard and Testing Technology, Tianjin, 300381, China;
2. Institute of Genetics and Physiology, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, 050051, China

摘要

摘要: 为建立不同温度条件下鲜切黄瓜中乙型副伤寒沙门氏菌的生长预测模型,将新鲜黄瓜切丁,添加乙型副伤寒沙门氏菌,分别在10、15、20、25、30和35℃下的恒温条件下贮藏,以观察细菌的生长。使用USDA综合病原体建模程序(USDA-IPMP)拟合每个温度下每种细菌的生长曲线,以找出描述该细菌生长的最适初级生长模型,并拟合得到最大比生长速率。通过温度对初级模型中最大比生长速率的生长动力学拟合,分别建立Ratkowsky、Huang rate、Cardinal、Arrhenius-type二级生长模型,并进行数学评估和实测样品验证。结果表明,实验数据和生长曲线显示乙型副伤寒沙门氏菌的生长表现出三个阶段,包括延滞期,指数期和稳定期。乙型副伤寒沙门氏菌的延滞期时间随着孵育时间的增加而降低。相反,乙型副伤寒沙门氏菌的生长速率随着孵育温度而增加,由此表明风险随温度的升高而增加。使用Baranyi和Huang初级模型分析两种病原体的生长曲线,使用Ratkowsky、Huang平方根模型、Cardinal和Arrhenius模型描述温度对贮藏时间细菌生长的影响,同时应用实验数据和样品实测验证评估所建立的预测模型。从该研究中获得的结果和预测模型可用于预测鲜切黄瓜产品中乙型副伤寒沙门氏菌的生长。
- 鲜切黄瓜 /
- 乙型副伤寒沙门氏菌 /
- 生长行为 /
- 预测模型
Abstract: Fresh-cut cucumber slices which were inoculated with Salmonella paratyphi B were incubated under constant temperature conditions between 10, 15, 20, 25, 30 and 35℃ to observe the growth of bacteria. The growth curves of each bacterium under each temperature were analyzed using the USDA Integrated Pathogen Modeling Program(USDA-IPMP)to find the most suitable primary models for describing the bacterial growth. The effect of temperature on bacterial growth rate and lag time was also evaluated using various secondary models. Experimental data and growth curves showed that the growth of Salmonella paratyphi B exhibited three phases, including lag, exponential, and stationary phases. The lag time of each bacterium decreased as the incubation time increased. In contrast, the growth rate of both bacteria increased with the incubation temperature, suggesting increased risks at elevated temperatures during temperature abuse. The growth curves of both pathogens were analyzed with the Baranyi and Huang primary models, while the Ratkowsky and Huang square-root models, Cardinal and the Arrhenius-type model were used to describe the effect of temperature on bacterial growth during storage. The predictive models were validated using experimental data. The results and predictive models obtained from this study can be used to predict the growth of Salmonella paratyphi B in fresh-cut RTE cucumber products.
- fresh-cut cucumber /
- Salmonella paratyphi B /
- growth predictive model /
- prediction model

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参考文献(18)

[1]	Newell D G,Koopmans M,Verhoe L,et al.Food-borne diseases-the challenges of 20 years ago still persist while new ones continue to emerge[J]. InternationaI Journal of Food Microbiology,2010,139:S3-S15.
[2]	赵新,王永,刘娜,等.金针菇中单增李斯特菌生长预测模型的建立[J].生物加工过程,2016,14(6):12-17.
[3]	Yang B,Qu D,Zhang X,et al. Prevalence and characterization of Salmonella serovars in retail meats of marketplace in Shaanxi,China[J]. International Journal of Food Microbiology,2010,141(1):63-72.
[4]	马晨,陈雪华,李建国.国标法与快速法检测沙门氏菌的结果比较[J].食品科技,2015(9):276-282.
[5]	Lynch M F,Tauxe R V,Hedberg C W. The growing burden of foodborne outbreaks due to contaminated fresh produce:risks and opportunities[J]. Epidemiology and Infection,2009,137(3):307-315.
[6]	Brandl M T,Cox C E,Teplitski M. Salmonella interactions with plants and their associated microbiota[J]. Phytopathology,2013,103(4):316-325.
[7]	Deering A J,Mauer L J,Pruitt R E. Internalization of E. coli O157:H7 and Salmonella spp. in plants:a review[J]. Food Research International,2012,45(2):567-575.
[8]	马晨,李建国,程景.沙门氏菌在鲜切蔬菜中生长行为及其预测模型构建[J].食品工业科技,2016(4):29.
[9]	刘一倩,易欣欣.新鲜蔬果中食源性致病细菌研究进展[J].生物技术通报,2014,27(4):19-24.
[10]	Francis G A,Gallone A,Nychas G J,et al. Factors affecting quality and safety of fresh-cut produce[J]. Critical Reviews in Food Science and Nutrition,2012,52(7):595-610.
[11]	Painter J A. Attribution of Foodborne Illnesses,Hospitalizations,and Deaths to Food Commodities by using Outbreak Data,United States,1998-2008-Volume 19,Number 3-March 2013-Emerging Infectious Disease journal-CDC[J]. 2013,19(3):407-415.
[12]	罗惟,陈敏,陈安均,等.基于生长预测模型研究温度对鲜切苹果中大肠杆菌和沙门氏菌生长的影响[J].中国农学通报,2015,31(11):170-176.
[13]	Sant'Ana A S,Barbosa M S,Destro M T,et al. Growth potential of Salmonella spp. and Listeria monocytogenes in nine types of ready-to-eat vegetables stored at variable temperature conditions during shelf-life[J]. International Journal of Food Microbiology,2012,157(1):52-58.
[14]	Pin C,Avendaño-Perez G,Cosciani-Cunico E,et al. Modelling Salmonella concentration throughout the pork supply chain by considering growth and survival in fluctuating conditions of temperature,pH and a w[J]. International Journal of Food Microbiology,2011,145:S96-S102.
[15]	郑婷,董鹏程,王仁欢,等.冷却牛肉中沙门氏菌生长预测模型的建立和验证[J].食品与发酵工业,2015,41(7):38-44.
[16]	周康,李平兰.不同浓度沙门氏菌细胞生长分布规律研究[J].食品科学,2012,33(13):254-258.
[17]	姜英杰,邹晓葵,彭增起.大肠杆菌在猪背最长肌上生长预测模型的建立[J].食品科学,2008,29(12):115-119.
[18]	李飞燕.冷却牛肉菌落总数生长模型及货架期预测模型的研究[D].济南:山东农业大学,2011.

施引文献(4)

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3.	于海涛，刘娜，李瑞环，徐石勇，黄凤军，赵新. 天津地区黄瓜中风险性食源性致病菌污染水平分析. 天津农业科学. 2022(11): 61-65+71 . 百度学术