Dynamic determination of kinetic parameters, computer simulation, and probabilistic analysis of growth of Clostridium perfringens in cooked beef during cooling

Growth kinetics of Bacillus cytotoxicus in liquid Egg yolk during treatment with phospholipase A2 - A one-step global dynamic analysis

During commercial production of liquid egg yolk (LEY), phospholipase A2 (PLA2) is used to improve its emulsification capacity and thermal stability. The enzymatic treatment may occur at elevated temperatures such as 50 °C, potentially allowing foodborne pathogens, such as Bacillus cereus, to grow. Little knowledge is available concerning growth of B. cereus in LEY during PLA2 treatment. Therefore, the objective of this study was to investigate the growth kinetics of B. cereus during PLA2 treatment using pathogenic B. cytotoxicus NVH391-98, the most thermotolerant member in the B. cereus group, as a surrogate. Inoculated LEY samples were placed in precision programmable incubators to observe the growth of B. cytotoxicus NVH391-98 under multiple isothermal and dynamic temperature conditions between 20 and 53 °C. The bacterial growth was described using the differential Baranyi model coupled with two different secondary models. The kinetic parameters were determined using one-step dynamic inverse analysis of multiple growth curves. The least square method was used in combination with the 4th order Runge-Kutta method to solve the differential Baranyi model using multiple growth curves to determine the cardinal kinetic parameters. The results showed that B. cytotoxicus NVH391-98 can grow prolifically at 50 °C. The estimated minimum, optimum and maximum temperatures were 16.7 or 18.5, 47.8 or 48.1, and 52.1 or 52.4 °C, respectively, depending on the secondary models, with an optimum growth rate of 2.1 log colony-forming-unit (CFU)/g per hour. The dynamic model is validated using isothermal curves with reasonable accuracy. B. cytotoxicus died off slowly at 15 °C. At 55 °C, thermal inactivation was observed, with a D value of approximately 2.7 h. Holding at 55 °C or below 15 °C can effectively prevent the growth of B. cytotoxicus in egg yolk.

Dynamic kinetic analysis of growth of Listeria monocytogenes in pasteurized cow milk

The objective of this study was to develop a dynamic model for predicting the growth of Listeria monocytogenes in pasteurized cow milk under fluctuating temperature conditions during storage and temperature abuse. Six dynamic temperature profiles that simulated random fluctuation patterns were designed to change arbitrarily between 4 and 30°C. The growth data collected from 3 independent temperature profiles were used to determine the kinetic parameters and construct a growth model combining the primary and secondary models using a 1-step dynamic analysis method. The results showed that the estimated minimum growth temperature and maximum cell concentration were 0.6 ± 0.2°C and 7.8 ± 0.1 log cfu/mL (mean ± standard error), with the root mean square error (RMSE) only 0.3 log cfu/mL for model development. The model and the associated kinetic parameters were validated using the data collected under both dynamic and isothermal conditions, which were not used for model development, to verify the accuracy of prediction. The RMSE of prediction was approximately 0.3 log cfu/mL for fluctuating temperature profiles, and it was between 0.2 and 1.1 log cfu/mL under certain isothermal temperatures (2-30°C). The resulting model and kinetic parameters were further validated using 3 growth curves at 4, 7, and 10°C arbitrarily selected from ComBase (www.combase.cc). The RMSE of prediction was 0.8, 0.4, and 0.5 log cfu/mL, respectively, for these curves. The validation results indicated the predictive model was reasonably accurate, with relatively small RMSE. The model was then used to simulate the growth of L. monocytogenes under a variety of continuous and square-wave temperature profiles to demonstrate its potential application. The results of this study showed that the model developed in this study can be used to predict the growth of L. monocytogenes in contaminated milk during storage.

A survey of a blown pack spoilage produced by Clostridium perfringens in vacuum-packaged wurstel

Three hundred Clostridium strains were isolated from spoiled wurstels and were identified by traditional and molecular methods as Clostridium perfringens. The phenotypic characteristics of the strains were studied. All the strains produced acetic and butyric acids and enterotoxin. C. perfringens grew in the spoiled wurstels because it was present in raw meat (Lot 150) at a level of 3.2 log CFU/g due to an unchecked cooling phase that took 28 h to decrease the temperature of the wurstels from 60 to 9-10 °C, which is the lower limit for C. perfringens growth. During the 28 h of cooling, the concentration of C. perfringens increased to 6.5 CFU/g. It was concluded that its presence and the long cooling time were the main factors responsible for the spoilage. Wurstels intentionally made with contaminated meat (3 log CFU/g) but cooled after cooking for 17 h to 9 °C did not support C. perfringens growth; consequently, these wurstels remained unspoiled. The packages of the spoiled wurstels were blown, and the products were soft (soggy), textureless and had the odour of acetic acid, ethanol and sulfur.

Holistic Approach to the Uncertainty in Shelf Life Prediction of Frozen Foods at Dynamic Cold Chain Conditions

Systematic kinetic modeling is required to predict frozen systems behavior in cold dynamic conditions. A one-step procedure, where all data are used simultaneously in a non-linear algorithm, is implemented to estimate the kinetic parameters of both primary and secondary models. Compared to the traditional two-step methodology, more precise estimates are obtained, and the calculated parameter uncertainty can be introduced in realistic shelf life predictions, as a tool for cold chain optimization. Additionally, significant variability of the real distribution/storage conditions is recorded, and must be also incorporated in a kinetic prediction scheme. The applicability of the approach is theoretically demonstrated in an analysis of data on frozen green peas Vitamin C content, for the calculation of joint confidence intervals of kinetic parameters. A stochastic algorithm is implemented, through a double Monte Carlo scheme incorporating the temperature variability during distribution, drawn from cold chain databases. Assuming a distribution scenario of 130 days in the cold chain, 93 ± 110 days remaining shelf life was predicted compared to 180 days assumed based on the use by date. Overall, through the theoretical case study investigated, the uncertainty of models’ parameters and cold chain dynamics were incorporated into shelf life assessment, leading to more realistic predictions.

Modeling for Survival of Clostridium perfringens in Saeng-sik, a Powdered Ready-to-Eat Food with Low Water Activity

HIGHLIGHTS

We developed a mathematical model to predict the survival of C. perfringens in food. C. perfringens vegetative cells and spores were inoculated into dried powder food. The a_w of saeng-sik was below 0.1. Weibull and Davey models can successfully describe the survival of C. perfringens. The developed model can be applied to samples with different microbial communities.

Kinetics of vacuum and air cooling of chicken breasts arranged in stacks

The aim of this study was to compare the vacuum and air cooling of cooked chicken breast samples arranged in stacks with one, two and three layers (1 kg per layer). The cooling rate obtained with vacuum cooling was approximately three times faster than that of air cooling. Moreover, a more homogeneous cooling was obtained with vacuum cooling, with similar temperature reductions for samples at different positions of the stack. On the other hand, vacuum cooling led to mass losses of 11-12%, while air cooling led to losses of 7-8%. The counts of mesophiles and psychrophiles of the vacuum-cooled samples were lower than those observed for air-cooled samples after ten days of product storage. Thus, the results presented in this work illustrate the potential benefits and disadvantages of the vacuum cooling technique as compared to the air cooling, especially for the processing of small meat cuts.

A Theoretical Analysis for Assessing the Variability of Secondary Model Thermal Inactivation Kinetic Parameters

Traditionally, for the determination of the kinetic parameters of thermal inactivation of a heat labile substance, an appropriate index is selected and its change is measured over time at a series of constant temperatures. The rate of this change is described through an appropriate primary model and a secondary model is applied to assess the impact of temperature. By this approach, the confidence intervals of the estimates of the rate constants are not taken into account. Consequently, the calculated variability of the secondary model parameters can be significantly lower than the actual variability. The aim of this study was to demonstrate the influence of the variability of the primary model parameters in establishing the confidence intervals of the secondary model parameters. Using a Monte Carlo technique and assuming normally distributed DT values (parameter associated with a primary inactivation model), the error propagating on the DTref and z-values (secondary model parameters) was assessed. When DT confidence intervals were broad, the secondary model's parameter variability was appreciably high and could not be adequately estimated through the traditional deterministic approach that does not take into account the variation on the DT values. In such cases, the proposed methodology was essential for realistic estimations.

Evaluating the Performance of a New Model for Predicting the Growth of Clostridium perfringens in Cooked, Uncured Meat and Poultry Products under Isothermal, Heating, and Dynamically Cooling Conditions

Clostridium perfringens type A is a significant public health threat and its spores may germinate, outgrow, and multiply during cooling of cooked meats. This study applies a new C. perfringens growth model in the USDA Integrated Pathogen Modeling Program-Dynamic Prediction (IPMP Dynamic Prediction) Dynamic Prediction to predict the growth from spores of C. perfringens in cooked uncured meat and poultry products using isothermal, dynamic heating, and cooling data reported in the literature. The residual errors of predictions (observation-prediction) are analyzed, and the root-mean-square error (RMSE) calculated. For isothermal and heating profiles, each data point in growth curves is compared. The mean residual errors (MRE) of predictions range from -0.40 to 0.02 Log colony forming units (CFU)/g, with a RMSE of approximately 0.6 Log CFU/g. For cooling, the end point predictions are conservative in nature, with an MRE of -1.16 Log CFU/g for single-rate cooling and -0.66 Log CFU/g for dual-rate cooling. The RMSE is between 0.6 and 0.7 Log CFU/g. Compared with other models reported in the literature, this model makes more accurate and fail-safe predictions. For cooling, the percentage for accurate and fail-safe predictions is between 97.6% and 100%. Under criterion 1, the percentage of accurate predictions is 47.5% for single-rate cooling and 66.7% for dual-rate cooling, while the fail-dangerous predictions are between 0% and 2.4%. This study demonstrates that IPMP Dynamic Prediction can be used by food processors and regulatory agencies as a tool to predict the growth of C. perfringens in uncured cooked meats and evaluate the safety of cooked or heat-treated uncured meat and poultry products exposed to cooling deviations or to develop customized cooling schedules. This study also demonstrates the need for more accurate data collection during cooling.

Clostridium perfringens: Comparative effects of heat and osmotic stress on non-enterotoxigenic and enterotoxigenic strains

Clostridium perfringens isolates associated with food poisoning carries a chromosomal cpe gene, while non-foodborne human gastrointestinal disease isolates carry a plasmid cpe gene. The enterotoxigenic strains tested produced vegetative cells and spores with significantly higher resistance than non-enterotoxigenic strains. These results suggest that the vegetative cells and spores have a competitive advantage over non-enterotoxigenic strains. However, no explanation has been provided for the significant associations between chromosomal cpe genotypes with the high resistance, which could explain the strong relationship between chromosomal cpe isolates and C. perfringens type A food poisoning. Here, we analyse the action of physical and chemical agent on non-enterotoxigenic and enterotoxigenic regional strains. And this study tested the relationship between the sensitivities of spores and their levels SASPs (small acid soluble proteins) production in the same strains examined.