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。     

糯米面团中金黄色葡萄球菌生长预测模型的构建

通过建立一级和二级模型描述糯米面团中金黄色葡萄球菌的生长动力学,为糯米制品原料中金黄色葡萄球菌的生长监测提供依据。将2株金黄色葡萄球菌(ATCC 8095和NCTC 8325)混合菌悬液接种至糯米面团样品中,分别将其在4、11、18、25、32℃和37℃恒温培养。结果表明,除4℃生长缓慢无法构建模型外,其他温度下3种一级生长模型(Baranyi、修正的Gompertz和Huang模型)均能对糯米面团中金黄色葡萄球菌生长曲线进行良好的拟合;但在较低和较高温度(11℃和37℃)下修正的Gompertz模型表现出最好的拟合准确度。赤池信息准则和决定系数(R²)等数据分析显示,修正的Gompertz模型可作为金黄色葡萄球菌最优一级生长预测模型。采用2个二级模型(Ratkowsky和Huang平方根模型)分析温度对金黄色葡萄球菌生长速率的影响,结果表明Ratkowsky平方根模型预测最低(0.049℃)和最高(47.135℃)生长温度相较于Huang平方根模型与实验结果更为接近,因而更适合作为糯米面团中金黄色葡萄球菌的二级生长模型。本研究结果可对食品企业和监管机构预测糯米制...     

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

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。     

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。     

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。     

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。     

市售五香牛肉货架期预测模型的建立

以菌落总数为指标建立微生物生长模型及散装五香牛肉货架期预测模型.将市售散装五香牛肉分割贮藏,测定了4、7、10℃条件下,贮藏期内样品菌落总数的变化.对恒定温度下的五香牛肉建立微生物初级生长模型、平方根二级模型及货架期预测模型.建立菌落总数的一级模型(Gompertz方程),拟合度在95％以上;平方根二级模型的R2值为0.998,温度与生长速率的平方根呈良好的线性关系,并且残差值在0上下浮动.     

铜绿假单胞菌在牛乳中生长的预测

以食源致病性铜绿假单胞菌ATCC27853为试材,研究其在牛乳中的生长模型参数与温度之间的关系,为其在牛乳中的安全控制提供理论依据。将ATCC27853接种于新鲜灭菌的牛乳中,分别置于6、10、16、22、28、36、42、45、48、50 ℃共10 个温度下生长,采用Matlab软件建立了在不同温度下ATCC27853的一级Gompertz模型;基于Gompertz模型拟合的参数,结合修正Ratkowsky模型与Hyperbola模型,分别建立了ATCC27853的最大比生长速率（μmax）与温度、延滞时间（λ）与温度之间的二级模型;采用决定系数、均方根误差、准确因子和偏差因子对ATCC27853的一级和二级模型进行评价。对一级Gompertz模型和二级修正Ratkowsky模型、Hyperbola模型进行验证,结果表明：一级Gompertz模型显著,能较好地预测不同温度下ATCC27853在牛乳中的生长;二级修正Ratkowsky模型和Hyperbola模型均显著,且拟合度较好;在6、10、48 ℃时,初始生理状态参数（h0）明显高于16～45 ℃时。ATCC27853的生长温度对μmax、λ和h0的影响可用于其在牛乳的加工、运输、贮藏和销售等过程中的安全预测,为ATCC27853在牛乳中的安全控制提供理论依据。     

冷却牛肉中沙门氏菌生长预测模型的建立和验证

建立了恒温条件下牛肉中沙门氏菌的生长动力学模型,准确掌握并及时预报沙门氏菌的生长情况,为冷却牛肉生产过程中该菌的控制提供有效的手段。将不同血清型的沙门氏菌混合菌株(以下简称沙门氏菌)接种到无污染的冷却牛肉表面,分别置于0、4、7、10、15和20℃恒温条件下贮藏并计数,采用Linear方程或修正的Gompertz方程拟合一级模型,并采用Ratkowsy平方根方程拟合二级模型。最后分别在恒温和波动温度下对模型进行验证。修正的Gompertz方程能较好地描述沙门氏菌在4~20℃贮藏条件下的生长动态(R2均大于0.99),而在0℃下则适用Linear方程拟合。采用平方根模型构建的沙门氏菌预测二级模型,表明温度对最大比生长速率(μmax)和迟滞期(λ)均呈现良好的线性关系(R2均大于0.96)。用贮藏在9℃、12℃和波动温度下沙门氏菌的生长实验值进行验证,偏差度分别为0.913、0.997、0.889,准确度分别为1.118、1.019、1.147。该预测模型能有效预测4~20℃条件下沙门氏菌在冷却牛肉中的生长情况。     

凉皮中金黄色葡萄球菌生长预测模型的建立

为了研究金黄色葡萄球菌在凉皮中的生长规律,通过测定5℃、10℃、15℃、20℃、25℃下金黄色葡萄球菌在凉皮中的生长数据,采用Baranyi模型、Modified Gompertz和Huang模型拟合金黄色葡萄球菌的生长曲线。比较3种模型的相关系数和参数,将一级模型得到的最大比生长速率(μmax)与迟滞期(λ)建立与温度相关的二级模型。实验表明,Modified Gompertz模型建立的一级模型的偏差因子(B_f)和准确因子(A_f)均在合理范围内。采用Modified Gompertz模型拟合的μmax和λ建立其与温度的平方根模型,拟合得到的R2为0.80和0.88,说明Modified Gompertz模型最适合拟合生长曲线,二级模型经方差分析显示方程显著,表明所建模型能有效预测金黄色葡萄球菌在凉皮中的生长情况。本研究为凉皮中金黄色葡萄球菌的定量风险评估提供理论依据。     

Evaluating the effect of temperature on microbial growth rate--the Ratkowsky and a Bělehrádek-type models

The objective of this paper to conduct a parallel comparison of a new Bělehrádek-type growth rate (with an exponent of 1.5, or the Huang model), Ratkowsky square-root, and Ratkowsky square equations as secondary models for evaluating the effect of temperature on the growth of microorganisms. Growth rates of psychrotrophs and mesophiles were selected from the literature, and independently analyzed with the 3 models using nonlinear regression. Analysis of variance (ANOVA) was used to compare the means of growth rate (μ), estimated minimum temperature (T(min) ), approximate standard errors (SE) of T(min) , model mean square errors (MSE), accuracy factor (A(f) ), bias factor (B(f) ), relative residual errors (δ), Akaike information criterion (AICc), and Bayesian information criterion (BIC). Based on the estimated T(min) values, the Huang model distinctively classified the bacteria into 2 groups (psychrotrophs and mesophiles). No significant difference (P > 0.05) was observed among the means of the μ values reported in the literature or estimated by the 3 models, suggesting that all 3 models were suitable for curve fitting. Nor was there any significant difference in MSE, SE, δ, A(f) , B(f) , AICc, and BIC. The T(min) values estimated by the Huang model were significantly higher than those estimated by the Ratkowsky models, but were in closer agreement with the biological minimum temperatures for both psychrotrophs and mesophiles. The T(min) values estimated by the Ratkowsky models systematically underestimated the minimum growth temperatures. In addition, statistical estimation showed that the mean exponent for the new Bělehrádek-type growth rate model may indeed be 1.5, further supporting the validity of the Huang model.     

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。     

Growth kinetics of Listeria monocytogenes and spoilage microorganisms in fresh-cut cantaloupe

The main objective of this study was to investigate the growth kinetics of Listeria monocytogenes and background microorganisms in fresh-cut cantaloupe. Fresh-cut cantaloupe samples, inoculated with three main serotypes (1/2a, 1/2b, and 4b) of L. monocytogenes, were incubated at different temperatures, ranging from 4 to 43 °C, to develop kinetic growth models. During storage studies, the population of both background microorganisms and L. monocytogenes began to increase almost immediately, with little or no lag phase for most growth curves. All growth curves, except for two growth curves of L. monocytogenes 1/2a at 4 °C, developed to full curves (containing exponential and stationary phases), and can be described by a 3-parameter logistic model. There was no significant difference (P = 0.28) in the growth behaviors and the specific growth rates of three different serotypes of L. monocytogenes inoculated to fresh-cut cantaloupe. The effect of temperature on the growth of L. monocytogenes and spoilage microorganisms was evaluated using three secondary models. For L. monocytogenes, the minimum and maximum growth temperatures were estimated by both the Ratkowsky square-root and Cardinal parameter models, and the optimum temperature and the optimum specific growth rate by the Cardinal parameter model. An Arrhenius-type model provided more accurate estimation of the specific growth rate of L. monocytogenes at temperatures <4 °C. The kinetic models developed in this study can be used by regulatory agencies and food processors for conducting risk assessment of L. monocytogenes in fresh-cut cantaloupe, and for estimating the shelf-life of fresh-cut products.     

Development and validation of growth model for Yersinia enterocolitica in cooked chicken meats packaged under various atmosphere packaging and stored at different temperatures.

Mathematical models that can predict the growth of Yersinia enterocolitica in chicken meats were evaluated in this study. The growth curves for Y. enterocolitica in chicken meats variously packaged (air, vacuum, and modified atmosphere packaging [MAP]) and stored at various temperatures (4, 10, 16, 22, 28, and 34 degrees C) were constructed. The Gompertz model was applied to fit each of the experimental curves for the conditions mentioned above. The variations in the parameters, including lag time (lambda) and specific growth rate (mu), at various temperatures were then described by the following models: the variations in lag time were described by the Adair and Smith models and the variations in the specific growth rate were described by the Ratkowsky and Zwietering models. The various models were then compared using graphical and mathematical analyses such as mean square error (MSE), regression coefficient (r2), bias factor, and accuracy factor. The results indicate that the mean r values in the Gompertz model for chicken meats packaged in air, vacuum, and MAP were 0.99, 0.99, and 0.95, respectively. The lag time modeled with the Adair and Smith functions exhibited a greater variance and demonstrated larger errors. The MSEs were 0.0015 and 0.0017 for Ratkowsky and Zwietering models, respectively. The r2 values in the Ratkowsky and Zwietering models were both 0.99. The bias factor was 1.017 for the Ratkowsky model and 1.096 for the Zwietering model. The accuracy factor of the Zwietering model was 1.174, which was lower than that in the Ratkowsky model (1.275), indicating that the former model was more accurate than the latter in predicting the specific growth rate of Y. enterocolitica in chicken meats.     

Effect of native microflora on the growth kinetics of salmonella enteritidis strain 04-137 in raw ground chicken

Effects of native microflora (NM) on growth kinetics of Salmonella Enteritidis strain 04-137 were studied in raw ground chicken. First, samples of ground chicken with high and low levels of NM (10(7.1) and 10(4.9) CFU/g, respectively) were spiked with Salmonella at doses ranging from 10(1) to 10(4) CFU/g. The growth kinetics, including the rate constant of growth, r, and the lag period, were similar, but the maximum cell level, N(max), was higher at higher initial Salmonella doses for both NM levels. Second, samples of ground chicken with high and low NM levels (10(6.8) and 10(4.7) CFU/g, respectively) were spiked with Salmonella and then stored at various constant temperatures ranging from 8 to 32°C. Both N(max) and r for Salmonella were higher at higher temperatures for both NM levels. Although r for total bacteria, which consisted of NM and Salmonella, was also higher at higher temperatures, N(max) was constant at all temperatures for both NM levels. Further, Salmonella growth was compared among samples of ground chicken with high and low NM levels and samples of sterilized chicken. Salmonella growth, characterized by both N(max) and r, was highest in sterilized chicken, followed by chicken with the low NM level. Our growth model successfully described and analyzed the growth of Salmonella and total bacteria in chicken at constant temperatures; using the data obtained, the model also successfully predicted the growth of Salmonella and total bacteria in chicken stored at dynamic temperatures. Our study clarified the effects that different doses of NM in ground chicken had on the growth kinetics of the Salmonella strain and demonstrated the usability of the growth model for foods with NM.     

Predictive Modeling of the Effect of ε‐Polylysine Hydrochloride on Growth and Thermal Inactivation of Listeria monocytogenes in Fish Balls

This study aimed to evaluate the effect of ε‐polylysine hydrochloride (ε‐PLH) on the growth and thermal inactivation kinetics of Listeria monocytogenes in fish balls. Samples, supplemented with ε‐PLH (0, 150, or 300 ppm, w/w), were inoculated with a three‐strain cocktail of L. monocytogenes and incubated at constant temperatures of 3.4, 8, 12, or 16 °C for growth studies, or heated at 60, 62.5, 65, or 67.5 °C for thermal inactivation tests. The growth curves were fitted to the Huang primary model, and the Huang and Ratkowsky square‐root models (SRM) were used as the secondary models to evaluate the effect of temperature on bacterial growth. The survival during heating was analyzed with a log‐linear model. The results showed that, while the lag time of L. monocytogenes was affected by both ε‐PLH concentration and temperature, the specific growth rate was unaffected by ε‐PLH. Under the same temperature, a 10‐time in increase of the lag time would be expected for every 565 ppm in the increase of ε‐PLH concentration. Using the Ratkowsky SRM, the estimated nominal minimum growth temperature was –2.04 °C, while the minimum growth temperature was 0.29 °C when estimated with the Huang SRM. Validation at 10 °C showed that the Huang primary model, in combination with either the Huang or Ratkowsky SRM, could accurately predict the growth of L. monocytogenes. On the other hand, the thermal resistance of the pathogen was significantly reduced by increase in temperature or ε‐PLH. The thermal z value of L. monocytogenes was 5.78 °C, and the ε‐PLH z value was 1642 ppm. The results of this study showed that the combined application of ε‐PLH and temperature can be used to control L. monocytogenes in fish balls and to improve food safety and reduce risks to public health.     

腐生酵母菌在鲜榨苹果汁中的生长速率预测模型

通过研究温度、pH和水分活度对鲜榨苹果汁中腐生酵母菌生长情况的影响 ,建立了最大生长速率和迟滞时间与生长限制因子之间关系的数学预测模型 ,并对Ratkowsky扩展模型和响应面模型进行了对比。结果表明 ,Ratkowsky扩展模型的相关系数优于响应面模型 ,响应面模型在较高温度 ( 2 0℃以上 )最大生长速率呈现下降趋势的预测结果与实际情况不符。应用Ratkowsky扩展模型对鲜榨苹果汁的货架期进行预测时发现 ,温度、pH和水分活度对货架期的影响有协同作用。通过模型验证证实Ratkowsky扩展模型预测结果与实测值有良好的拟合性 ,相对误差在±1 0 %左右 ,可以用于鲜榨苹果汁货架期的预测     

低温条件下冷却猪肉中假单胞菌生长模型的比较分析

为了确定拟合冷却猪肉中假单胞菌低温下生长的最适模型,分别对低温(0、5、10℃)条件下托盘和真空包装冷却猪肉中假单胞菌的生长特点进行分析,应用修正的Gompertz、Baranyi及Huang模型对其进行拟合,通过残差和拟合度(RSS、AIC、RSE)等统计指标比较3种模型的拟合能力,分析不同模型拟合假单胞菌生长的差别。结果表明：低温托盘和真空包装条件下假单胞菌在延滞期出现了明显的菌数下降现象,随后呈现“S”形生长;0℃条件下Baranyi模型拟合出最小的RSS、AIC、RSE值,分别是5.2933、－54.0428、0.1708;而修正的Gompertz模型和Huang模型分别在5℃和10℃条件下拟合出最小的RSS、AIC、RSE值,分别是17.7372、－18.9098、0.5068和13.0410、－22.4848、0.4207。拟合冷却猪肉中假单胞菌生长的最适模型0℃是Baranyi模型,5℃是修正的Gompertz模型,10℃是Huang模型。因此,在冷却猪肉腐败菌预测时,不同温度条件下应该选择最适合的模型而不是单一的模型来预测假单胞菌的生长。