巴氏杀菌奶中单增李斯特菌生长动力学模型的研究

为研究巴氏杀菌奶中单增李斯特菌的生长规律,将4株单增李斯特菌混合接种到巴氏杀菌奶中,并分别置于4、8、12、16、20、25、30、37、40、43℃条件下恒温培养,间隔时间取样计数。使用美国农业部开发的IPMP 2013软件,将4～43℃条件下得的生长数据分别代入Huang模型和Baranyi模型进行拟合,分析单增李斯特菌在不同温度下的生长动力学特征。在所有温度下均可以观察到单增李斯特菌的生长,所有生长曲线都显示出滞后期,指数期和稳定期。综合比较2种初级模型的RMSE、RSE、AIC和生长速率,确定Baranyi模型和Huang模型均适合描述巴氏杀菌奶中单增李斯特菌的生长,且具有等同的拟合效果。采用Ratkowsky平方根模型、Huang平方根模型和Cardinal模型描述温度对巴氏杀菌奶中单增李斯特菌生长速率的影响。研究表明:3种模型都能用于评价温度对其生长速率的影响。Ratkowsky平方根模型预测的单增李斯特菌的最低、最高温度为0.218℃和46.389℃,与文献报道的更为接近。因此,Ratkowsky平方根模型比Huang平方根模型和Cardinal模型更适合描述温度对单增李斯特菌生长的影响。建立的模型可为相关监管部门开展巴氏杀菌奶中单增李斯特菌的安全风险评估提供科学依据。     

鸡肉中沙门氏菌和背景菌群生长动力学模型

本研究通过一级模型和二级模型描述鸡肉样品中沙门氏菌和背景菌群的生长动力学模型。用两种沙门氏菌血清型（鼠伤寒沙门氏菌（CICC22956）和肠炎沙门氏菌（CICC21482））的混合物接种到鸡肉样品中,分别将其在8、12、16、20、25、30、33、37、40、43 ℃下恒温培养。除了8 ℃以外,在其他温度下都可以观察到沙门氏菌和背景菌群的生长。将12～43 ℃下得到的微生物生长数据分别用一级模型Huang模型、Baranyi模型进行拟合,根据方差分析的结果,两种一级模型在模拟鸡肉样品中沙门氏菌和背景菌群的生长精确度方面没有显著差异（P＞0.05）,均适合描述鸡肉样品中沙门氏菌和背景菌群的生长。采用3 个二级模型（Ratkowsky平方根模型、Huang平方根模型和Cardinal模型）描述温度对鸡肉样品中沙门氏菌和背景菌群生长速率的影响。Cardinal模型低估了低温下微生物的生长速率,Huang平方根模型预测的沙门氏菌最低（7.81 ℃）和最高（49.67 ℃）生长温度与文献报道更为接近。Ratkowsky平方根模型描述的温度范围较广,更适合描述菌种复杂的背景菌群的生长速率。本研究结果可对食品工业和监管机构预测鸡肉样品中沙门氏菌的生长以及肉制品中该微生物安全风险评估提供科学依据。     

巴氏杀菌奶的微生物生长动力学模型研究

目的通过初级模型和二级模型来描述巴氏杀菌奶中微生物的生长动力学模型。方法样品放置在4、8、16、25、30、37、40和43℃条件下培养,使用IPMP 2013软件进行拟合,初级模型采用Huang模型和Baranyi模型分析不同温度下的生长动力学特征,二级模型采用Ratkowsky平方根模型、Huang平方根模型和Cardinal模型描述温度对其生长速率的影响。结果在所有温度下都能观测到微生物的生长,综合比较2种初级模型的均方根误差(root mean squared error,RMSE)、均方误差(mean squared errorMSE)、赤池信息量准则(Akaike information criterion, AIC)和生长速率,得到2种初级模型具有同等拟合效果;而3种二级模型得到的最低生长温度和最高生长温度分别是-3.191、0.56、-4.962和47.309、45.277、44.408℃。结论 Baranyi模型和Huang模型均适合描述巴氏杀菌奶中微生物菌群的生长,3种二级模型都能用于评价温度对其生长速率的影响,但Ratkowsky平方模型覆盖的温度范围更广,可能更适合描述温度对巴氏杀菌奶中微生物菌群生长的影响。     

鲜切雪莲果中单增李斯特菌生长动力学研究

为研究鲜切雪莲果中单增李斯特菌的生长规律,将4株单增李斯特菌混合接种至鲜切雪莲果表面,并分别置于4℃,10℃,16℃,20℃,25℃,30℃,37℃,40℃和43℃条件下培养,间隔时间取样计数,所得的生长数据分别代入Baranyi模型和Huang模型进行拟合,经综合比较2种初级模型的RMSE、RSE、AIC和生长速率,确定Baranyi模型和Huang模型均适合描述鲜切雪莲果中单增李斯特菌的生长,且具有等同的拟合效果。选取Huang平方根模型、Cardinal模型、Arrhenius-type模型描述温度对单增李斯特菌生长速率的影响,并通过Huang平方根模型和Cardinal模型估算单增李斯特菌的最低生长温度、最高生长温度,通过Cardinal模型估算单增李斯特菌的最适生长温度和最适生长速率,研究结果还表明Arrhenius-type模型能更准确地描述低温(4℃)条件下的单增李斯特菌的生长速率。建立的模型可为相关监管部门开展鲜切果蔬中单增李斯特菌的安全风险评估提供科学依据。     

沙门氏菌在鲜切蔬菜中生长行为及其预测模型构建

为揭示沙门氏菌在鲜食蔬菜或调味蔬菜中的生长情况,以蒜苗、香菜、西红柿、黄瓜和小葱为实验对象,点植接种两株沙门氏菌混合菌液(Salmonella enteritidis ATCC 13076和S.newport ATCC 6962),研究不同接种剂量下沙门氏菌在鲜切蔬菜中生长情况,考察不同温度下沙门氏菌在鲜切黄瓜中的动态生长情况,并构建生长模型。结果表明:4℃下,沙门氏菌在所试鲜切蔬菜中均不生长。28℃,高接种剂量下(2.0 log CFU/g和3.0 log CFU/g),沙门氏菌在各种蔬菜中的生长势(δ)在4.25~5.84 log CFU/g之间,表明其在各种蔬菜中生长良好(菌落数量7.0 log CFU/g)。1.0 log CFU/g接种剂量下,除了黄瓜外,沙门氏菌在其他蔬菜中生长良好(菌落数量约5.0 log CFU/g)。微量接种剂量0.1 log CFU/g,小葱和番茄中沙门氏菌长势尚好(δ0.5 log CFU/g),其他蔬菜中沙门氏菌不生长(δ0.5 log CFU/g)。采用Baranyi模型对实测数据进行拟合,结果显示:7、15、20和25℃下沙门氏菌在鲜切黄瓜中的最大比生长速率(μmax)分别为0.026、0.11、0.14和0.29 h-1;7℃和15℃时,迟滞时间分别为24.33 h和9.44 h,20℃和25℃时不经历迟滞期,直接进入对数生长期。采用次级模型Ratkowsky方程描述最大生长速率和储藏温度的关系,模型可靠性较好。所以,蔬菜品种、接种剂量和储藏温度影响沙门氏菌在鲜切蔬菜中的生长。     

鲜切草鱼脊肉品质变化及假单胞菌生长预测模型

以鲜切草鱼脊肉为研究对象进行感官评定,用食品安全快速检测仪测定挥发性盐基氮的变化,并用SAS软件构建假单胞菌生长预测模型。结果表明,挥发性盐基氮含量随着贮藏时间的延长而增加,且随着贮藏温度的升高而迅速增加,感官评分随着贮藏时间的延长而下降,且随着贮藏温度的升高而迅速下降,修正的Gompertz方程对不同贮藏温度下假单胞菌的生长预测模型拟合度较好。采用平方根模型拟合试验温度范围内温度与最大比生长速率、温度与延滞期的关系,线性关系良好。结论:采用挥发性盐基氮、感官评定指标可有效地反应鲜切草鱼脊肉的品质变化,建立的模型对0²0℃范围内鲜切草鱼脊肉中假单胞菌预测效果较好。     

冰温冷藏鲜肉的菌落总数动态变化预测模型拟合验证

采用Huang模型、Baranyi模型和修正的Gompertz模型对猪肉、鸡胸肉和牛肉在不同温度条件下冷藏时的菌落总数进行拟合,通过比较拟合效果筛选出能够准确预测鲜肉在冰温条件下贮藏时菌落总数的预测模型,进一步采用平方根模型来描述贮藏温度对菌落总数的影响,并用偏差因子和准确因子进行预测模型验证。结果表明：采用Huang模型对猪肉、鸡胸肉和牛肉分别在－1.0、－1.0、2.5 ℃条件下贮藏过程中菌落总数拟合的效果优于Baranyi模型和修正的Gompertz模型,Huang模型可以更好地预测不同冰温条件下贮藏鲜肉的菌落总数变化;通过平方根模型拟合得到的牛肉贮藏温度与最大比生长速率和迟滞期的判定系数R2Adj分别为0.999和0.985,这表明牛肉贮藏温度与最大比生长速率和迟滞期之间存在良好的线性关系;预测模型的准确因子和偏差因子平均值分别为1.164和0.998,尤其是在－2.5 ℃贮藏条件下,准确因子和偏差因子分别为1.009和1.000,均接近于1.000,预测模型可靠性高,说明Huang模型能较好地预测冰温贮藏鲜肉菌落总数的动态变化。     

鲜切结球莴苣中单增李斯特菌生长预测模型的建立

为建立不同温度下鲜切结球莴苣中单增李斯特菌生长模型,将单增李斯特菌接种到鲜切结球莴苣表面,并于不同温度下贮藏,获得其在4、8、16、24和32℃下的生长数据,选用Gompertz模型进行拟合,建立初级生长模型。在此基础上建立二级模型研究温度对初级模型中单增李斯特菌生长动力学参数的影响,并进行数学检验。结果表明,对最大比生长速率和延滞时间建立平方根模型,结果呈良好的线性关系,相关系数R2分别为0.977 2和0.984 7,所建立的预测模型能很好地描述不同温度下单增李斯特菌的生长动态。     

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。     

草鱼鱼糜中沙门氏菌生长预测模型的建立

为建立鱼糜中沙门氏菌生长预测模型,选用新鲜草鱼鱼糜和鼠伤寒沙门氏菌作为研究对象,比较了4、10、20、28、37℃条件下鱼糜中鼠伤寒沙门氏菌的生长情况,分别采用Huang模型,Baranyi模型和修正的Gompertz模型进行拟合,建立鱼糜中鼠伤寒沙门氏菌一级生长动力学模型。并用平方根模型方程描述温度与比生长速率和延滞期的关系,得到鼠伤寒沙门氏菌生长二级模型。使用判定系数R2,准确因子(Af),偏差因子(Bf)和均方误差(MSE)对一级和二级模型可靠性进行评价,结果表明修正的Gompertz模型更适合于描述4~37℃条件下鱼糜中鼠伤寒沙门氏菌的生长变化,二级平方根模型可用于描述鱼糜中鼠伤寒沙门氏菌的生长参数,能够为鱼糜中沙门氏菌的监测提供一定的参考依据。     

Description of growth of Clostridium perfringens in cooked beef with multiple linear models

The traditional linear model used in food microbiology employs three linear segments to describe the process of food spoilage and categorize a growth curve into three phases — lag, exponential, and stationary. The linear model is accurate only within certain portions of each phase of a growth process, and can underestimate or overestimate the transitional phases. While sigmoid functions (such as the Gompertz and logistic equations) can be used to fit the experimental growth data more accurately, they fail to indicate the physiological state of bacterial growth. The objective of this paper was to develop a new methodology to describe and categorize accurately the bacterial growth as a process using Clostridium perfringens as a test organism. This methodology utilized five linear segments represented by five linear models to categorize a bacterial growth process into lag, first transitional, exponential, second transitional, and stationary phases. Growth curves described in this paper using multiple linear models were more accurate than the traditional three-segment linear models, and were statistically equivalent to the Gompertz models. With the growth rates of transitional phases set to 1/3 of the exponential phase, the durations of the lag, first transitional, exponential, and second transitional phases in a growth curve described by the new method were correlated linearly. Since this linear relationship was independent of temperature, a complete five-segment growth curve could be generated from the maximum growth rate and a known duration of the first four growth phases. Moreover, the lag phase duration defined by the new method was a linear function of the traditional lag phase duration calculated from the Gompertz equation. With this relationship, the two traditional parameters (lag phase and maximum growth rate) used in a three-segment linear model can be used to generate a more accurate five-segment linear growth curve without involving complicated mathematical calculations.     

Comparison of predictive models for growth of parent and green fluorescent protein-producing strains of Salmonella

The green fluorescent protein (GFP) from the jellyfish Aequorea victoria can be expressed in, and used to follow the fate of, Salmonella in microbiologically complex ecosystems such as food. As a first step in the evaluation of GFP as a tool for the development of predictive models for naturally contaminated food, the present study was undertaken to compare the growth kinetics of parent and GFP-producing strains of Salmonella. A previously established sterile chicken burger model system was used to compare the growth kinetics of stationary-phase cells of parent and GFP strains of Salmonella Enteritidis, Salmonella Typhimurium, and Salmonella Dublin. Growth curves for constant temperatures from 10 to 48 degrees C were fit to a two- or three-phase linear model to determine lag time, specific growth rate, and maximum population density. Secondary models for the growth parameters as a function of temperature were generated and compared between the parent and GFP strain pairs. The effects of GFP on the three growth parameters were significant and were affected by serotype and incubation temperature. The expression of GFP reduced specific growth rate and maximum population density while having only a small effect on the lag times of the three serotypes. The results of this study indicate that the growth kinetics of the GFP strains tested were different from those of the parent strains and thus would not be good marker strains for the development of predictive models for naturally contaminated food.     

Analysis of a molecular predictive mode for the growth of Staphylococcus aureus in pork

The objective of this study was to develop a molecular predictive model from quantitative real-time polymerase chain reaction methods to describe the growth of S. aureus strains in arti?cially contaminated pork in storage dependent of a constant temperature (7–30°C). This model acquired by quantitative real-time polymerase chain reaction methods was compared to a conventional predictive model using data. This study used three of the main growth models to fit the growth equation. The results proved that Modified Gompertz, Logistic, and Richards models were adequate for describing the growth curves. These models had the very low rate of the growth of S. aureus in pork during a lag phase. The growth rate increased with temperature, and the lag time decreased. Lag phases were apparent in all models, and those samples stored at low temperatures had longer lag phases. There was no significant difference in the molecular and conventional predictive models for any of the growth curves. However, the use of a molecular predictive model could save more time and labor to construct more precise models of certain pathogens. In conclusion, the molecular predictive model could provide an effective method to lessen the risk of S. aureus of pork.     

A new logistic model for bacterial growth

A new logistic model for bacterial growth was developed in this study. The model is based on a logistic model, which is often applied for biological and ecological population kinetics. The new model is described by a differential equation and contains an additional term for suppression of the growth rate during the lag phase, compared with the original logistic equation. The new model successfully described sigmoidal growth curves of Escherichia coli and Salmonella under various initial conditions. Data for E. coli were obtained from our experiments and data for Salmonella from the literature. When the new model was compared with a modified Gompertz model, which is widely used by many predictive microbiology researchers, it proved to be superior to the Gompertz model. Further, Salmonella growth at varying temperature could be well simulated by the new model. These results indicate that the new model will be a useful tool to predict bacterial growth under various temperature profiles.     

When is simple good enough: a comparison of the Gompertz,Baranyi, and three-phase linear models for fitting bacterial growth curves

The use of primary mathematical models with curve fitting software is dramatically changing quantitative food microbiology. The two most widely used primary growth models are the Baranyi and Gompertz models. A three-phase linear model was developed to determine how well growth curves could be described using a simpler model. The model divides bacterial growth curves into three phases: the lag and stationary phases where the specific growth rate is zero (gm=0), and the exponential phase where the logarithm of the bacterial population increases linearly with time (gm=constant). The model has four parameters: N_o(Log₈of initial population density), NMAX(Log₈of final population density), tLAG(time when lag phase ends), and tMAX(time when exponential phase ends). A comparison of the linear model was made against the Baranyi and Gompertz models, using established growth data forEscherichia coli0157:H7. The growth curves predicted by the three models showed good agreement. The linear model was more ‘robust' than the others, especially when experimental data were minimal. The physiological assumptions underlying the linear model are discussed, with particular emphasis on assuring that the model is consistent with bacterial behavior both as individual cells and as populations. It is proposed that the transitional behavior of bacteria at the end of the lag phase can be explained on the basis of biological variability.     

卤制鸭腿中乳酸菌生长预测模型研究

测定了卤制鸭腿中的乳酸菌在5、10、15、20、25℃条件下的生长情况,并利用Gompertz模型拟合了测定温度下的乳酸菌生长一级模型和乳酸菌生长状况。结果表明:模型拟合的R2都大于0.99,利用平方根模型描述温度与最大比生长速率和延滞期的关系,建立了乳酸菌在鸭腿基质上的生长预测二级模型,方差分析表明二级模型拟合显著。模型可用于预测5～25℃范围内乳酸菌在鸭腿上的生长变化情况,为卤制鸭腿中腐败微生物的预测研究提供参考。     

Modeling the lag phase of Listeria monocytogenes

An estimate of the lag phase duration is an important component for predicting the growth of a bacterium and for creating process models and risk assessments. Most current research and data for predictive modeling programs initiated growth studies with cells grown to the stationary phase in a favorable pH, nutrient and temperature environment. In this work, Listeria monocytogenes Scott A cells were grown in brain heart infusion (BHI) broth at different temperatures from 4 to 37 degrees C to the exponential growth or stationary phases. Additional cells were suspended in a dilute broth, desiccated or frozen. These cells were then transferred to BHI broth at various temperatures from 4 to 37 degrees C and the lag phase durations were determined by enumerating cells at appropriate time intervals. Long lag phases were observed for cells initially grown at high temperatures and transferred to low temperatures. In general, exponential growth cells had the shortest lag phases, stationary phase and starved cells had longer, frozen cells had slightly longer and desiccated cells had the longest lag phases. These data were from immediate temperature transitions. When a computer-controlled water bath linearly changed the temperature from 37 to 5 degrees C over a 3.0- or 6.0-h period, the cells had short lags and grew continuously with declining growth rates. Transitions of 0.75 or 1.0 h had 20-h lag phases, essentially that of immediate transitions. When the transition was 1.5 h, an intermediate pattern of less than 1 log of growth followed by no additional growth for 20 h occurred.     

Bacterial contamination of cucumber fruit through adhesion

In this study, the adhesion of bacteria to fresh cucumber surfaces in aqueous suspension was shown to be dependent on time of incubation, inoculum species and concentration, and temperature. The adhesion of bacteria to the fruit in wash water was less extensive at lower temperatures and shorter exposure times. Various species of bacteria were adsorbed to cucumber surfaces in the following relative order: Salmonella Typhimurium > Staphylococcus aureus > Lactobacillus plantarum > Listeria monocytogenes. Cells were adsorbed at all temperatures tested (5, 15, 25, and 35 degrees C) at levels that depended on incubation time, but the numbers of cells adsorbed were larger at higher incubation temperatures. Levels of adhesion of bacteria to dewaxed fruit were higher for L. monocytogenes and lower for Salmonella Typhimurium, L. plantarum, and S. aureus than were levels of adhesion to waxed fruit.     

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.