590 微生物学通报 2008, Vol.35, No.4,, 1 模型介绍, ; ;,, [4] Whiting Buchanan(1993) [5] Isabelle Andre(2006) [6], 1 Primary models 表 1 模型的分类 Table 1 Classificati

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1 微生物学通报 APR 20, 2008, 35(4): 589~594 Microbiology 2008 by Institute of Microbiology, CAS 专论与综述 食品微生物生长预测模型研究新进展 周康 1 刘寿春 1 李平兰 1* 马长伟 1 彭朝辉 2 ( ) ( ) 摘要 : 为了更好的了解食品微生物学预测模型的基本内容, 探讨数学模型在预测微生物学中的作用, 达到提高食品卫生检测效率, 保证食品质量安全的目的, 本文以文献综述形式, 简要概述了预测微生物学一级 二级和三级模型的含义与内容 并在此基础上, 着重介绍了全球范围内已经成功推广使用的多种三级模型, 阐述了它们的研究背景 研究进展 使用方法, 分析了各种模型存在的优缺点, 可为实际应用中选择合适的模型提供参考 在比较使用不同种类模型后, 发现 Baranyi & Roberts 响应面和 ComBase 模型在各级模型中具有更好的使用价值 关键词 : 预测模型, 微生物, 食品 New Advances in Predictive Food Microbial Growth Model ZHOU Kang 1 LIU Shou-Chun 1 LI Ping-Lan 1* MA Chang-Wei 1 PENG Zhao-Hui 2 (1. Food Science and Nutritional Engineering, China Agricultural University, Beijing ) (2. Beijing Beishui Food Company Limited, Beijing ) Abstract: Predictive food microbiology is an emerging multidisciplinary area of microbiology. For the purpose of understanding the basic principles of predictive food microbiology, studying the usage of mathematics model in predictive microbiology, improving the efficiency of food sanitary detection and guarantee the food safety, this paper provides a review on different sorts of predictive model with emphasized on the tertiary model. It is included that the classifications of global modeling, research background, recent advances, operation approaches and also the analysis and evaluation of these models, which could be helpful for practical use. Baranyi & Roberts, Response surface, ComBase models are better than the others models. Keywords: Predictive model, Microbiology, Food (Predictive Food Microbiology) [1],,, [2], QMRA(Quantitative microbial risk assessment) HACCP(Hazard Analysis Critical Control Point) [3] 基金项目 : FP6 CHILL-ON (No. FP ); * 通讯作者 :Tel: ; : plli@sohu.com 收稿日期 : ; 接受日期 :

2 590 微生物学通报 2008, Vol.35, No.4,, 1 模型介绍, ; ;,, [4] Whiting Buchanan(1993) [5] Isabelle Andre(2006) [6], 1 Primary models 表 1 模型的分类 Table 1 Classification of Models Secondary models Tertiary models Gompertz function Response surface models Pathogen Modelling Programme Logistic model Arrhenius model Growth Predictor Baranyi model Square root models Pseudomonas Predictor Rosso model γ-models Seafood Spoilage and Safety Predictor Monod model Z values ComBase D value of inactivation Sym Previus 2 一级模型,,,, (Logistic function) Gompertz Baranyi & Roberts 2.1 线型和 Logistic 模型 logn=a+kt logn t ; A ( ); k Logistic y A /{1+exp[4μ m (λ-t)/a+2]} y t, logn t /N 0 ; A, logn max /N 0 ; μ m ; λ,, 2.2 Gompertz 模型 Gompertz, logn=a+c*exp{-exp[-b(t-m)]} logn t ; A ( ); C ; B M ; M [7], ; Logistic Gompertz, Gompertz, 2.3 Baranyi & Roberts 模型 Baranyi & Roberts ( Baranyi ) kmax [ t B ( t )] min ( 0 min ) t n n n N = N + N N e Bt () = [ r / r + s ] ds 0 N t ; N 0 0 ;

3 : 591 N min ; k max ; r, s [8], Baranyi ; ; ; [9], Baranyi,,,,, Baranyi,,, Baranyi 3 二级模型 ( Gompertz A B C M) (Squareroot model) (Arrhenius relationship) (Response surface model) 3.1 平方根模型, U =b (T T min ) U, b T min, [10],, 3.2 响应面模型,, ph ;,,, [11],,,,,,,, 4 三级模型,,,, ; ;, 4.1 Growth Predictor Growth Predictor Food MicroModel, Growth Predictor Food MicroModel Gompertz, Baranyi & Roberts Food MicroModel Gompertz ;, Growth Predictor 0 α ; α 0 0, ; α 0 1, [9],,,,,,,, 4.2 PMP PMP (Pathogen Modelling Program), 11

4 592 微生物学通报 2008, Vol.35, No.4 35, ph, PMP [12] PMP,,, Growth Predictor,, 4.3 SSSP 介绍 :(Seafood Spoilage and Safety Predictor, SSSP), SSSP 1999 (Seafood Spoilage Predictor, SSP) SSP, [13] ; SSSP (Relative Rate of Spoilage, RRS) (Microbial Spoilage, MS), SSSP Logistic model, squareroot polynomial models, SSSP, ; ;, ; SSSP ;, 相对腐败速率 (RRS) 模型 :RRS,, RRS RRS,, RRS RRS,,, RRS 微生物腐败 (MS) 模型 : MS,,,,,, (Specific Spoilage Organisms, SSO), SSO [14] SSO, SSO, SSO SSO SSSP SSP,,,,,,,,, 4.4 Sym Previus Sym Previus, ( ph ),,,, ;,,,, Sym Previus Rosso s cardinal model

5 : ; ; Sym Previus,,,, 4. 5 ComBase 模型简介 :ComBase (Food Standards Agency) (Institute of Food Reseach), (USDA Agricultural Research Service) (Eastern Regional Research Center), (Australian Food Safety Centre of Excellence) ComBase ComBase ( ComBase Browser ),, ComBase Predictor,, ; ; 1988,, Food MicroModel, Food MicroModel, PMP(Pathogen Modelling Program) ,, ComBase , ComBase, ComBase ;, ;, 2006, ComBase, ComBase Predictor 使用方法 :ComBase ComBase Predictor, ComBase Predictor, ( ph ) ph,, ComBase Predictor Baranyi, ph ComBase Predictor ;,, ComBase, ComBase 19, 29, 5 ComBase,,,,, ph,,,, Predictor Fit the

6 594 微生物学通报 2008, Vol.35, No.4 Data Predictor ComBase Fit the Data ComBase 5 1, ComBase,,,,,, 5 小结,,,,,, Baranyi & Roberts ComBase [15],,,,,,,,,,,,,,, 参考文献 [1] McMeekin TA, Olley J, Ratkowsky DA, et al. Predictive microbiology: towards the interface and beyond. International Journal of Food Microbiology, 2002, 73: [2] Walls I, Scott VN. Use of predictive microbiology in microbial food safety risk assessment. International Journal of Food Microbiology, 1997, 36: [3] McMeekin TA, Baranyi J, Bowman J, et al. Information systems in food safety management. International Journal of Food Microbiology, 2006, 113: [4] McDonald K, Sun DW. Predictive food microbiology for the meat industry: a review. International Journal of Food Microbiology, 1999, 52: [5] Whiting RC, Buchanan RL. A classification of models for predictive microbiology. Food Microbiology, 1993, 10: [6] Isabelle L, Andre L. Quantitative prediction of microbial behaviour during food processing using an integrated modeling approach: a review. International Journal of Refrigeration, 2006, 29: [7] Giannuzzi L, Pinotti A, Zaritzky N. Mathematical modeling of microbial growth in packaged refrigerated beef stored at different temperatures. International Journal of Food Microbiology, 1998, 39: [8] Xiong R, Xie G, Edmondson AS, et al. Comparison of the Baranyi model with the modified Gompertz equation for modelling thermal inactivation of Listeria monocytogenes. Food Microbiology, 1999, 16: [9] Baranyi J, Roberts TA. A dynamic approach to predicting bacterial growth in food. International Journal of Food Microbiology, 1994, 23: [10] Greer GG, Gill CO, Dilts BD. Evaluation of the bacteriological consequences of the temperature regimes experienced by fresh chilled meat during retail display. International Food Research, 1994, 27: [11] Zurera-Cosano G, Garcia-Gimeno RM, Rodriguez-perez R, et al. Performance of response surface model for prediction of Leuconostoc Mesenteroides growth parameters under different experimental conditions. Food Control, 2006, 17: [12] Tamplin M, Baranyi J, Paoli G. Software programs to increase the utility of predictive microbiology information. In: McKellar RC, Lu X (Eds.). Modeling Microbial Responses in Foods. Boca Raton: CRC Press, 2004, pp [13] Dalgaard P, Buch P, Silberg S. Seafood Spoilage Predictor-development and distribution of a product specific application software. International Journal of Food Microbiology, 2002, 73: [14] Dalgaard P. Modelling of microbial activity and prediction of shelf life for packed fresh fish. International Journal of Food Microbiology, 1995, 26: [15],,,.., 2007, 7: