Dynamic modeling of Listeria monocytogenes growth in pasteurized vanilla cream after postprocessing contamination

A product-specific model was developed and validated under dynamic temperature conditions for predicting the growth of Listeria monocytogenes in pasteurized vanilla cream, a traditional milk-based product. Model performance was also compared with Growth Predictor and Sym'Previus predictive microbiology software packages. Commercially prepared vanilla cream samples were artificially inoculated with a five-strain cocktail of L. monocytogenes, with an initial concentration of 102 CFU g(-1), and stored at 3, 5, 10, and 15 degrees C for 36 days. The growth kinetic parameters at each temperature were determined by the primary model of Baranyi and Roberts. The maximum specific growth rate (mu(max)) was further modeled as a function of temperature by means of a square root-type model. The performance of the model in predicting the growth of the pathogen under dynamic temperature conditions was based on two different temperature scenarios with periodic changes from 4 to 15 degrees C. Growth prediction for dynamic temperature profiles was based on the square root model and the differential equations of the Baranyi and Roberts model, which were numerically integrated with respect to time. Model performance was based on the bias factor (B(f)), the accuracy factor (A(f)), the goodness-of-fit index (GoF), and the percent relative errors between observed and predicted growth. The product-specific model developed in the present study accurately predicted the growth of L. monocytogenes under dynamic temperature conditions. The average values for the performance indices were 1.038, 1.068, and 0.397 for B(f), A(f), and GoF, respectively for both temperature scenarios assayed. Predictions from Growth Predictor and Sym'Previus overestimated pathogen growth. The average values of B(f), A(f), and GoF were 1.173, 1.174, and 1.162, and 1.267, 1.281, and 1.756 from Growth Predictor and Sym'Previus, respectively.     

Prediction of pathogen growth on iceberg lettuce under real temperature history during distribution from farm to table

The growth of pathogenic bacteria Escherichia coli O157:H7, Salmonella spp., and Listeria monocytogenes on iceberg lettuce under constant and fluctuating temperatures was modelled in order to estimate the microbial safety of this vegetable during distribution from the farm to the table. Firstly, we examined pathogen growth on lettuce at constant temperatures, ranging from 5 to 25 degrees C, and then we obtained the growth kinetic parameters (lag time, maximum growth rate (micro(max)), and maximum population density (MPD)) using the Baranyi primary growth model. The parameters were similar to those predicted by the pathogen modelling program (PMP), with the exception of MPD. The MPD of each pathogen on lettuce was 2-4 log(10) CFU/g lower than that predicted by PMP. Furthermore, the MPD of pathogens decreased with decreasing temperature. The relationship between mu(max) and temperature was linear in accordance with Ratkowsky secondary model as was the relationship between the MPD and temperature. Predictions of pathogen growth under fluctuating temperature used the Baranyi primary microbial growth model along with the Ratkowsky secondary model and MPD equation. The fluctuating temperature profile used in this study was the real temperature history measured during distribution from the field at harvesting to the retail store. Overall predictions for each pathogen agreed well with observed viable counts in most cases. The bias and root mean square error (RMSE) of the prediction were small. The prediction in which mu(max) was based on PMP showed a trend of overestimation relative to prediction based on lettuce. However, the prediction concerning E. coli O157:H7 and Salmonella spp. on lettuce greatly overestimated growth in the case of a temperature history starting relatively high, such as 25 degrees C for 5 h. In contrast, the overall prediction of L. monocytogenes under the same circumstances agreed with the observed data.     

生鲜猪肉中单增李斯特菌动态生长预测与数值模拟

构建生鲜猪肉中单增李斯特菌的动态生长预测模型。猪肉样品接种由3 株单增李斯特菌制备的混合菌液,并置于3 组波动温度（1～45 ℃）条件下培养,采用一步法对获得的生长数据进行分析,构建并比较由初级模型（Baranyi或Two-compartment模型）与二级模型（Cardinal模型）集成的组合模型。结果表明,Baranyi-Cardinal和Two-compartment-Cardinal模型均适合用于描述猪肉中单增李斯特菌的生长,由两者估计的猪肉样品中单增李斯特菌最低、最适、最高生长温度分别为0.94、38.37、45.36 ℃和1.03、37.96、45.58 ℃,最适生长速率分别为0.891 h－1和0.858 h－1,最大生长浓度分别为9.07（lg（CFU/g））和9.09（lg（CFU/g））;通过另设的4 组动态生长实验和3 组等温（4、20、37 ℃）生长实验对模型进行验证,分析表明,模型可以准确预测动态及等温条件下的单增李斯特菌的生长,预测曲线的均方根误差介于0.13～0.48 （lg（CFU/g））,残差服从均值为－0.02 （lg（CFU/g））、标准差为0.29（lg（CFU/g））的正态分布。最后,基于构建的模型开展生鲜猪肉家庭冰箱冷藏过程中单增李斯特菌的生长数值模拟,以证明模型潜在的应用性。本研究结果可用于猪肉中单增李斯特菌的生长预测及风险评估。     

Determination of the growth limits and kinetic behavior of Listeria monocytogenes in a sliced cooked cured meat product: validation of the predictive growth model under constant and dynamic temperature storage conditions

To describe the growth limits of Listeria monocytogenes NCTC10527 in a sliced vacuum-packaged cooked cured meat product, the binary logistic regression model was used to develop an equation to determine the probability of growth or no growth of L. monocytogenes as a function of temperature (from 0 to 10 degrees C) and water activity (from 0.88 to 0.98). Two inoculum concentrations were used (10 and 10(4) CFU g(-1)), and the growth limits for the two inocula were different. The kinetic behavior of L. monocytogenes as a function of temperature (4, 8, 12, and 16 degrees C) on the same meat product at the lower concentration (10 CFU g(-1)) was also studied. The Baranyi model appeared to fit the overall experimental data better than did the modified Gompertz and the modified logistic models. Maximum specific growth rate (micromax), lag phase duration (LPD), and maximum cell concentration (Nmax) derived from the primary model were modeled using the square root function (micromax and LPD) and a second order polynomial (Nmax) (secondary models). The selection of the best model (primary or secondary) was based on some statistical indices (the root mean square error of residuals of the model, the regression coefficient, the F test, the goodness of fit, and the bias and accuracy factor). The developed kinetic behavior model was validated under constant and dynamic temperature storage conditions. This prediction of L. monocytogenes growth provides useful information for improving meat safety and can be used for in-depth inspection of quality assurance systems in the meat industry.     

Use of commercially available antimicrobial compounds for prevention of Listeria monocytogenes growth in ready-to-eat minced tuna and salmon roe during shelf life

Listeria monocytogenes found in minced tuna and fish roe can cause listeriosis. These products are classified in category B according to the Codex Alimentarius Commission, i.e., ready-to-eat foods in which L. monocytogenes growth can occur. We investigated the effectiveness of nisin and other commercially available antimicrobial compounds (lysozyme, ε-polylysine, and chitosan) for prevention of L. monocytogenes growth during the expected shelf life of raw minced tuna and salmon roe products. Food samples inoculated with L. monocytogenes were incubated with each antimicrobial at 10°C for 7 days or at 25°C for 12 h. Nisaplin (an antimicrobial containing nisin) effectively inhibited L. monocytogenes growth in minced tuna at 500 ppm and in salmon roe at 250 ppm within their standard shelf lives. The effective concentration of each antimicrobial was determined: 2,000 ppm for ART FRESH 50/50 (containing lysozyme) and SAN KEEPER No. 381 (containing ε-polylysine) and 10,000 ppm for SAN KEEPER K-3 (containing chitosan).     

冷却猪肉中单增李斯特氏菌生长动力学模型的建立与评价

为建立冷却猪肉中单增李斯特氏菌的生长动力学模型,把单增李斯特氏菌接种到无污染的冷却猪肉中,分别放置于2、15、28℃条件下贮藏,分别测定其在不同贮藏时间的菌数。应用修正的Gompertz 方程描述单增李斯特氏菌在2、15、28℃下的生长动态,建立不同温度下其在冷却猪肉中的生长曲线和模型。温度对最大比生长速率(μmax)和延滞时间(λ)的影响,采用平方根模型在0～30℃范围内呈现较好的线性关系,R2 分别为0.7164 和0.9717。模型残差值的绝对值均小于0.03,在“零”上下浮动,表明该模型描述的温度与μmax 和λ(的关系是完全可信的,说明用平方根模型能很好的描述不同温度对单增李斯特氏菌生长的影响。     

Growth of Listeria monocytogenes on iceberg lettuce and solid media

The growth of pathogenic bacterium Listeria monocytogenes on fresh-cut iceberg lettuce under constant temperatures was modelled in order to investigate microbial safety during distribution of this vegetable. We examined the effects of several incubation temperatures, ranging from 5 to 25 degrees C, on bacterial growth. These data were fitted to the Baranyi model and the curves showed a high correlation coefficient at all temperature (R2 > 0.95). In addition, the native bacterial flora of the lettuce did not affect the growth rate of L. monocytogenes regardless of incubation temperature. However, the lag time was reduced at a ratio of native bacteria to inoculated L. monocytogenes (100:1) at low incubation temperatures (5 and 10 degrees C). Furthermore, the maximum population density (MPD) was increased at a low ratio of native to inoculated L. monocytogenes (1:1) at all incubation temperatures. These results were compared with the previous work published by [Buchanan, R.L., Stahl, H.G., Whiting, R.C., 1989. Effects and interactions of temperature, pH, atmosphere, sodium chloride, and sodium nitrite on the growth of Listeria monocytogenes. J. Food Prot. 52, 844-851] that is being developed at the US Department of Agriculture (USDA) Agricultural Research Service's Pathogen Modelling Program (PMP). The broth-based Buchanan model for L. monocytogenes was found to markedly deviate from the observed data. In order to investigate this discrepancy, we examined the effects of medium environment and nutrient content on L. monocytogenes growth using tryptic soy agar plates (TSAP) and agar plates (AP) containing 1.7% sucrose. The inoculated bacteria on both TSAP and AP showed slower growth rates than that predicted by the PMP. The MPD of bacteria grown on TSAP was similar to the PMP model ( approximately 9 log10 CFU/ml or plate (circle of diameter of 90 mm)) regardless of the incubation temperature. By contrast, the MPD observed on AP was approximately 4 log10 CFU lower than that observed on TSAP or predicted by the PMP. Both the growth rate and the MPD of L. monocytogenes on AP were similar to those on lettuce. These results suggest that the solid medium and poor nutrient content inhibited the growth of L. monocytogenes on lettuce. The growth rates of the inoculated L. monocytogenes on all media were described using Ratkowsky's simple square root model.     

The effect of micro-architectural structure of cabbage substratum and or background bacterial flora on the growth of Listeria monocytogenes

The effect of micro-architectural structure of cabbage (Brassica oleracea var. capitata L.) substratum and or background bacterial flora on the growth of Listeria monocytogenes as a function of incubation temperature was investigated. A cocktail mixture of Pseudomonas fluorescens, Pantoea agglomerans and Lactobacillus plantarum was constituted to a population density of approximately 5 log CFU/ml in order to pseudo-simulate background bacterial flora of fresh-cut cabbage. This mixture was co-inoculated with L. monocytogenes (approximately 3 log CFU/ml) on fresh-cut cabbage or in autoclaved cabbage juice followed by incubation at different temperatures (4-30 degrees C). Data on growth of L. monocytogenes were fitted to the primary growth model of Baranyi in order to generate the growth kinetic parameters of the pathogen. During storage, microbial ecology was dominated by P. fluorescens and L. plantarum at refrigeration and abuse temperature, respectively. At all temperatures investigated, lag duration (lambda, h), maximum specific growth rate (micro(max), h(-1)) and maximum population density (MPD, log CFU/ml) of L. monocytogenes were only affected by medium micro-architectural structure, except at 4 degrees C where it had no effect on the micro(max) of the pathogen. Comparison of observed values of micro(max) with those obtained from the Pathogen Modelling Program (PMP), showed that PMP overestimated the growth rate of L. monocytogenes on fresh-cut cabbage and in cabbage juice, respectively. Temperature dependency of micro(max) of L. monocytogenes, according to the models of Ratkowsky and Arrhenius, showed linearity for temperature range of 4-15 degrees C, discontinuities and linearity again for temperature range of 20-30 degrees C. The results of this experiment have shown that the constituted background bacterial flora had no effect on the growth of L. monocytogenes and that micro-architectural structure of the vegetable was the primary factor that limited the applicability of PMP model for predicting the growth of L. monocytogenes on fresh-cut cabbage. A major limitation of this study however is that nutrient profile of the autoclaved cabbage juice may be different from that of the raw juice thus compromising realistic comparison of the behaviour of L. monocytogenes as affected by micro-architectural structure.     

单增李斯特菌在生食鱼片中生长模型的建立

为研究生食鱼片中单增李斯特菌的生长规律,将单增李斯特菌接种到经冷杀菌后的3 种生食鱼片（三文鱼片、金枪鱼片、鲷鱼片）中,分别置于4、8、15、25、35 ℃环境下培养,间隔适当时间取出计数。用5 种常用的一级模型（Gompertz模型、Baranyi模型、Logistic模型、Richards模型和MMF模型）对实验数据进行拟合,通过比较相关系数R2和均方误差（mean square error,MSE）,确定最适一级模型为Gompertz模型。建立单增李斯特菌生长动力学参数（最大比生长速率μm和迟滞期λ）关于温度、pH值和水分活度的二级平方根扩展模型,并应用相关系数R2、偏差值Bf和准确值Af进行验证。结果表明,构建的二级模型能够很好地描述生食鱼片中单增李斯特菌的生长情况。     

基于一步法的金枪鱼生鱼片沙门氏菌生长数值模拟

食物中沙门氏菌的生长是公共健康的重大威胁之一。以生食金枪鱼为研究对象,构建生鱼片中沙门氏菌生长的预测模型。首先,考察恒定温度(8~35℃)条件下沙门氏菌在生鱼片中的生长特性,随机选取两次独立重复试验中一组生长数据,采用一步法同步构建初级模型(Huang模型、Baranyi模型)和二级模型(Huang Square-Root模型),并通过四阶龙格-库塔法联合最小二乘法估计模型参数;其次,选取另一组恒温条件下的独立重复试验数据及波动温度条件下的生长数据,对模型进行验证。结果表明:一步法适用于生鱼片中沙门氏菌的生长曲线分析,同步构建的Huang-HSR模型和Baranyi-HSR模型具有等同的拟合效果,基于Huang模型对迟滞期有着明确的定义,建议选择Huang-HSR模型;通过一步法估计的沙门氏菌的最低生长温度为6.91℃,最大生长浓度为9.15 lg(CFU/g);恒定温度和波动温度验证试验的RMSE分别为0.37 lg(CFU/g)和0.44 lg(CFU/g),其误差分别服从正太分布和拉普拉斯分布。本研究构建的预测模型可用于金枪鱼生鱼片中沙门氏菌的生长预测和风险评估。     

Listeria monocytogenes在经高氧化还原电位酸性水处理的鲜食莴苣上预测模型的建立

采用高氧化还原电位酸性水(EOW)对接种过单核细胞增生李斯特菌的鲜食莴苣进行处理,研究残留菌在不同温度下的保存期限。建立Gompertz,Logistic和Baranyi初级模型,描述单增李斯特菌在不同温度下的生长情况,对比结果表明,Gompertz模型的判定系数R2=0.9913,能够更好地拟合李斯特菌在各个温度下的生长状况,并得到李斯特菌生长的Gompertz模型生长参数(SGR,LT,MPD)。利用平方根模型对其的最大比生长速率的平方根-温度进行拟合,得到莴苣上单核细胞增生李斯特菌生长的二级模型:SGR=0.015T+0.069。使用判定系数(R2)、均方误差(MSE)、偏差因子(BF)和准确因子(AF)对模型进行验证,结果表明,本研究得出的二级模型能够很好地预测单核细胞增生李斯特菌在相应环境下的生长状况。     

Development and validation of a dynamic growth model for Listeria monocytogenes in fluid whole milk

Listeria monocytogenes, a psychrotrophic microorganism, has been the cause of several food-borne illness outbreaks, including those traced back to pasteurized fluid milk and milk products. This microorganism is especially important because it can grow at storage temperatures recommended for milk (< or =7 degrees C). Growth of L. monocytogenes in fluid milk depends to a large extent on the varying temperatures it is exposed to in the postpasteurization phase, i.e., during in-plant storage, transportation, and storage at retail stores. Growth data for L. monocytogenes in sterilized whole milk were collected at 4, 6, 8, 10, 15, 20, 25, 30, and 35 degrees C. Specific growth rate and maximum population density were calculated at each temperature using these data. The data for growth rates versus temperature were fitted to the Zwietering square root model. This equation was used to develop a dynamic growth model (i.e., the Baranyi dynamic growth model or BDGM) for L. monocytogenes based on a system of equations which had an intrinsic parameter for simulating the lag phase. Results from validation of the BDGM for a rapidly fluctuating temperature profile showed that although the exponential growth phase of the culture under dynamic temperature conditions was modeled accurately, the lag phase duration was overestimated. For an alpha0 (initial physiological state parameter) value of 0.137, which corresponded to the mean temperature of 15 degrees C, the population densities were underpredicted, although the experimental data fell within the narrow band calculated for extreme values of alpha0. The maximum relative error between the experimental data and the curve based on an average alpha0 value was 10.42%, and the root mean square error was 0.28 log CFU/ml.     

A MODEL FOR PREDICTING THE GROWTH OF LISTERIA MONOCYTOGENES IN PACKAGED WHOLE MILK

Experiments were conducted to determine growth characteristics of Listeria monocytogenes in sterilized whole milk at nine temperatures in the range of 277.15 to 308.15K (4 to 35C). Based on these data, the parameter values of the Baranyi dynamic growth model were statistically determined. Finite element software, ANSYS, was used to determine temperature distributions in milk cartons subject to a time‐varying ambient temperature profile. The space‐time‐temperature data were input to the Baranyi dynamic growth model, to predict the microbial population density distribution and the average population density in the milk carton. The Baranyi dynamic growth model and the finite element model were integrated and validated using experimental results from inoculated sterilized whole milk in half‐gallon laminated paper cartons. In all experiments, the milk cartons were subjected to the same temperature profile as the Baranyi dynamic growth model. Experimental microbial counts were within predicted upper and lower bounds obtained using the integrated Baranyi dynamic growth and finite element models. In addition, the growth curve at the mean value of initial physiological state parameter for L. monocytogenes underpredicted the microbial growth (standard error = 0.54 log (cfu/mL) and maximum relative difference = 15.49%).     

不同温度下椰汁中金黄色葡萄球菌的生长动力学模型比较

探讨不同温度下椰汁中金黄色葡萄球菌的生长预测模型。将菌悬液接种到椰汁中,测定不同温度(20、25、30、36℃)下的生长数据。使用Matlab软件拟合得到修正Gompertz(MGompertz)、修正Logistic(MLloistic)和Baranyi模型,比较残差和拟合度选择最优一级模型,并拟合出生长参数。用平方根和二次多项式方程建立二级模型,通过相关系数、偏差因子和准确因子对二级模型进行检验。在20~36℃下,Baranyi模型拟合出的各个拟合度最优,Baranyi模型适宜作为模拟金黄色葡萄球菌在椰汁中生长的一级预测模型。二次多项式相较于平方根模型可以更好地表达温度与最大比生长速率及延滞期的关系。因此选择Baranyi模型和二次多项式模型描述不同温度下椰汁中金黄色葡萄球菌的生长。     

Incidence of Listeria monocytogenes in raw seafood products in Japanese retail stores

The incidence of Listeria monocytogenes in raw fish, shellfish, and fish roe was investigated in seafood products collected from randomly selected retail stores in and around Tokyo, Japan. Of the 10 samples of 208 examined found positive for L. monocytogenes by mini-VIDAS LMO, seven were fish roe (cod, salmon) and three were minced tuna. Three serotypes (1/2a, 1/2b, 3b) were detected among the isolated strains; serotype 1/2a was predominant (8 of 10).     

Bayesian synthesis of a pathogen growth model: Listeria monocytogenes under competition

The Bayesian synthesis method is applied to data from two studies of Listeria monocytogenes grown in broth monocultures to draw inferences about the joint distribution of two Baranyi growth model parameters-lag time and maximum specific growth rate. The resultant joint distribution is then combined with prior distributions for the initial and maximum pathogen density parameters under competitive growth conditions. Finally, the pathogen growth model is updated using the Sampling/Importance Resampling (SIR) algorithm with data on L. monocytogenes growth in competition with natural microflora in fish. Although the latter data provide no information on the stationary phase to directly estimate the maximum pathogen density parameter, combining them with relevant prior information provides a means to characterize L. monocytogenes growth in a food with mixed microbial populations. Based on a specified tolerance for L. monocytogenes growth, the updated model provides a storage time limit for fish held at 5 degrees C, pH 6.8, 43% CO(2), 57% N(2).     

Comparison of primary predictive models to study the growth of Listeria monocytogenes at low temperatures in liquid cultures and selection of fastest growing ribotypes in meat and turkey product slurries

This study compared the performance of four primary mathematical models to study the growth kinetics of Listeria monocytogenes ribotypes grown at low temperature so as to identify the best predictive model. The parameters of the best-fitting model were used to select the fastest growing strains with the shortest lag time and greatest growth rate. Nineteen food, human and animal L. monocytogenes isolates with distinct ribotype were grown at 4, 8, and 12 degrees C in tryptic soy broth and slurries prepared from cooked uncured sliced turkey breasts (with or without potassium lactate and sodium diacetate, PL/SD) and cooked cured frankfurters (with or without PL/SD). Separate regressions were performed on semi-logarithm growth curves to fit linear (based on Monod) and non-linear (Gompertz, Baranyi-Roberts, and Logistic) equations and performance of each model was evaluated using an F-test. No significant differences were found in the performance of linear and non-linear models, but the Baranyi model had the best fit for most growth curves. The maximum growth rate (MGR) of Listeria strains increased with the temperature. Similarly MGR was found significantly greater when no antimicrobials were present in the formulation of turkey or frankfurter products. The variability in lag times and MGRs in all media as determined by the Baranyi model was not consistent among strains. No single strain consistently had the fastest growth (shortest lag time, fastest MGR, or shortest time to increase 100-fold), but nine strains were identified as fastest growing strains under most growth conditions. The lack of association between serotype and fastest strain was also observed in the slurry media study. The fastest growing strains resulting from this study can be recommended for future use in L. monocytogenes challenge studies in delicatessen meat and poultry food matrices, so as to develop conservative pathogen growth predictions.     

Growth kinetics of Listeria monocytogenes in broth and beef frankfurters--determination of lag phase duration and exponential growth rate under isothermal conditions

ABSTRACT:  The objective of this study was to develop a new kinetic model to describe the isothermal growth of microorganisms. The new model was tested with Listeria monocytogenes in tryptic soy broth and frankfurters, and compared with 2 commonly used models—Baranyi and modified Gompertz models. Bias factor (BF), accuracy factor (AF), and root mean square errors (RMSE) were used to evaluate the 3 models. Either in broth or in frankfurter samples, there were no significant differences in BF (approximately 1.0) and AF (1.02 to 1.04) among the 3 models. In broth, the mean RMSE of the new model was very close to that of the Baranyi model, but significantly lower than that of the modified Gompertz model. However, in frankfurters, there were no significant differences in the mean RMSE values among the 3 models. These results suggest that these models are equally capable of describing isothermal bacterial growth curves. Almost identical to the Baranyi model in the exponential and stationary phases, the new model has a more identifiable lag phase and also suggests that the bacteria population would increase exponentially until the population approaches to within 1 to 2 logs from the stationary phase. In general, there is no significant difference in the means of the lag phase duration and specific growth rate between the new and Baranyi models, but both are significantly lower than those determined from the modified Gompertz models. The model developed in this study is directly derived from the isothermal growth characteristics and is more accurate in describing the kinetics of bacterial growth in foods.     

盐水鸭中单核细胞增生李斯特菌生长预测模型的建立

为研究盐水鸭中单核细胞增生李斯特菌(Listeriamonocytogenes,Lm)的生长规律,通过测定4、10、16、25℃条件下的生长数据,选用4种常用的一级模型(Gompertz、Logistic、Richards及MMF模型)对数据进行拟合,比较各模型决定系数R^2和均方误差(MSE),确定最适一级模型,根据一级模型得到的最大比生长速率(μmax)和迟滞期(λ)建立与温度相关的二级模型。结果表明:Gompertz模型拟合的生长曲线R^2均达到0.99以上,为最适一级模型,在25℃条件下,Lm经0.78 h后即进入对数期,从4℃提高到10℃时,生长速率从0.02 1g(cfu/g)·h^-1增至0.05 1g(cfu/g)·h^-1,说明温度对盐水鸭中Lm的生长影响较大。选用Ratkowsky平方根模型建立的温度与μmax关系的二级模型R^2为0.98,偏差因子(Bf)、准确因子(Af)分别为0.99、1.01,二次多项式模型建立的温度与λ关系的R^2为0.99,Bf、Af分别为1.01、1.08,表明所建两种模型均能较好地描述盐水鸭中Lm的生长情况。本研究建立的生长模型可为监控盐水鸭的食品安全和风险评估提供参考。     

Quantifying nonthermal inactivation of Listeria monocytogenes in European fermented sausages using bacteriocinogenic lactic acid bacteria or their bacteriocins: a case study for risk assessment

Listeria monocytogenes NCTC10527 was examined with respect to its nonthermal inactivation kinetics in fermented sausages from four European countries: Serbia-Montenegro, Hungary, Croatia, and Bosnia-Herzegovina. The goal was to quantify the effect of fermentation and ripening conditions on L. monocytogenes with the simultaneous presence or absence of bacteriocin-producing lactic acid bacteria (i.e., Lactobacillus sakei). Different models were used to fit the experimental data and to calculate the kinetic parameters. The best model was chosen based on statistical comparisons. The Baranyi model was selected because it fitted the data better in most (73%) of the cases. The results from the challenge experiments and the subsequent statistical analysis indicated that relative to the control condition the addition of L. sakei strains reduced the time required for a 4-log reduction of L. monocytogenes (t(4D)). In contrast, the addition of the bacteriocins mesenterocin Y and sakacin P decreased the t(4D) values for only the Serbian product. A case study for risk assessment also was conducted. The data of initial population and t(4D) collected from all countries were described by a single distribution function. Storage temperature, packaging method, pH, and water activity of the final products were used to calculate the inactivation of L. monocytogenes that might occur during storage of the final product (U.S. Department of Agriculture Pathogen Modeling Program version 7.0). Simulation results indicated that the addition of L. sakei strains significantly decreased the simulated L. monocytogenes concentration of ready-to-eat fermented sausages at the time of consumption.