Thermal Inactivation Models Research Articles

Estimation of Bacteriophage MS2 Inactivation Parameters During Microwave Heating of Frozen Strawberries

Frozen berries have been repeatedly linked to acute gastroenteritis caused by norovirus, the most common cause of foodborne illness in the United States. Many guidelines recommend that frozen berries be microwaved for at least 2 min, but it is unclear if this thermal treatment is effective at inactivating norovirus. The objective of this study was to model the effect of microwave heating at varying power levels on the survival of bacteriophage MS2, a norovirus surrogate, when inoculated onto frozen strawberries. Bacteriophage MS2 was inoculated onto the surface of frozen strawberries with a starting concentration of approximately 10 log PFU/g. Samples (either 3 or 5 whole strawberries) were heated in a 1300-Watt domestic research microwave oven (frequency of 2450 MHz) at power levels of 30, 50, 70, and 100% (full power), for times ranging from 15 to 300 s to determine inactivation. Temperatures at berry surfaces were monitored during heating using fiberoptic thermometry. All experiments were conducted in triplicate. The primary model for thermal inactivation was a log-linear model of logN vs. time. The secondary model was for a D-value decreasing linearly with temperature and an added term that was path-dependent on the thermal history. Parameters in the model were estimated using dynamic temperature history at the surface of the berry, via nonlinear regression using all data simultaneously. The root mean square error was ∼0.5 PFU/g out of a total 6-log reduction. Log reductions of 1.1 ± 0.4, 1.5 ± 0.5, 3.1 ± 0.1, and 3.8 ± 0.2 log PFU/g were observed for 30, 50, 70, and 100% microwave power levels when three berries were heated for 60 s. D-values were 21.4 ± 1.95 s and 10.6 ± 1.1 s at 10 and 60°C, respectively. This work demonstrates an approach to estimate inactivation parameters for viruses from dynamic temperature data during microwave heating. These findings will be useful in predicting the safety effect of microwave heating of berries in the home or food service.

Disinfection efficiency prediction under dynamic conditions: Application to peracetic acid disinfection of wastewater

In this work, a mechanistic dynamic model of continuous flow peracetic acid (PAA) disinfection was developed, calibrated and validated, assuming E. coli as indicator microorganism. The model was conceived as a 1-dimensional dispersion model integrating PAA first order decay and E. coli inactivation rate. Lab-scale batch experiments of PAA decay and E. coli inactivation experiments were performed to calibrate corresponding kinetic models. In each sample, conventional wastewater quality parameters were monitored. A PAA pilot reactor was set up to perform both tracer studies, for dispersion model calibration, and continuous flow disinfection experiments, to validate the integration of hydraulics and kinetics models, under both stationary and dynamic conditions. Linear regression models were calibrated to predict hydrodynamic dispersion, given the flow rate, and PAA decay parameters, given effluent quality and PAA dosage. Successful validation of the PAA disinfection model proved the importance of (i) considering the disinfection process as a dynamic system and (ii) integrating real-time estimation of process disturbances, being the initial E. coli concentration and the impact of effluent quality and PAA dosage on PAA decay kinetics. Importantly, novel inactivation models were proposed, as two different modifications of a literature model for thermal inactivation. These models are suitable for dynamic simulation of Eulerian models and can describe the typical triphasic behavior of inactivation kinetics.

Modelling the thermal inactivation of spores from different phylogenetic groups of Bacillus cereus

The objective of this work is to match available phylogenetic information for Bacillus cereus strains with published thermal resistance parameters (D90°C, z) and to use this information to develop refined inactivation models for B. cereus sensu lato. To do so, the thermal resistance parameters were retrieved for 57 strains of B. cereus that could be assigned to a phylogenetic group. This information was used to build specific distributions for D90°C and z for the different phylogenetic groups of B. cereus to build refined thermal inactivation models for B. cereus. For validation purposes, thermal parameters were also retrieved for additional strains of unknown groups, but which had been classified as psychrotrophic or mesophilic. Monte Carlo simulations were first performed assuming that the model parameters D90°C and z are independent. However, based on the observation that combinations of very high D90°C and high z-values were not reported, an alternative Monte Carlo simulation set was explored for the phylogenetic Groups with very high z-values (i.e.i.e. Groups IV and VI). With both simulation sets, the predicted lower and upper limits of the D-values are close to the lowest and highest D-values reported in two previous meta-analysis studies. However, a better correspondence between the predicted and observed limits is obtained when using the alternative simulation set.

Predictive Microbial Modeling of Enterococcus faecium NRRL B-2354 Inactivation during Baking of a Multicomponent Low-Moisture Food

The use of baking ovens as a microbial kill step should be validated based on results of thermal inactivation models. Although traditional isothermal models may not be appropriate for these dynamic processes, they are being used by the food industry. Previous research indicates that the impact of additional process conditions, such as humidity, should be considered when validating thermal processes for the control of microbial hazards in low-moisture foods. In this study, the predictive performance of traditional and modified thermal inactivation kinetic models accounting for process humidity were assessed for predicting inactivation of Enterococcus faecium NRRL B-2354 in a multi-ingredient composite food during baking. Ingredients (milk powder, protein powder, peanut butter, and whole wheat flour) were individually inoculated to achieve ∼6 log CFU/g, equilibrated to a water activity of 0.25, and then mixed to form a cookie dough. An isothermal inactivation study was conducted for the dough to obtain traditional D- and z-values (n = 63). In a separate experiment, cookies were baked under four dynamic heating conditions: 135°C, high humidity; 135°C, low humidity; 150°C, high humidity; and 150°C, low humidity. Process humidity measurements; time-temperature profiles for the product core, surface, and bulk air; and microbial survivor ratios were collected for the four conditions at six residence times (n = 144). The traditional isothermal model had a high root mean square error (RMSE) of 856.51 log CFU/g, significantly overpredicting bacterial inactivation during the process. The modified model accounting for the dynamic time-temperature profile and process humidity data was a better predictor with an RMSE of 0.55 log CFU/g. These results indicate the importance of accounting for additional process parameters in baking inactivation models and that model performance can be improved by utilizing model parameters obtained directly from industrial-scale experimental data.

Modeling thermal inactivation of Salmonella Typhimurium in mash broiler feed

Feed hygienics is of increasing concern for poultry producers. This project included 2 studies to investigate kinetic parameters for inactivation of Salmonella Typhimurium in mash broiler feed heated at various temperatures. In study one, 2- and 5-g feed samples, contained in a sample bag, were inoculated with S. Typhimurium and submerged in a water bath heated to 90°C until internal temperatures of 75°, 80°, and 85°C were reached. In study two, 2-g of sample were inoculated with S. Typhimurium and submerged into a water bath set at 75°, 80°, 85°, 90°, and 95°C heated for 0 to 180 s. Feed sample and water bath temperature were monitored by thermocouples. Thermocouple data demonstrated 2- and 5-g samples achieved a 5-log reduction of S. Typhimurium when internal temperature of feed reached 80°C and 85°C, respectively. D-values for linear and Weibull models were calculated for the 5 temperatures. D-values of the linear model were 6.70, 8.83, 12.05, 13.91, and 24.40 s, and D-values for the Weibull model were 2.27, 3.67, 3.95, 4.68, and 7.63 s when heated to 95°, 90°, 85°, 80°, and 75°C. Individual temperature datasets were further analyzed using GinaFit software. As heating temperature decreased, Double-Weibull and Biphasic models fit all the thermal data, indicating that Salmonella could have generated 2 subpopulations with different thermoresistance. Similar to other thermal inactivation models, this study demonstrates that linear, Weibull, Double-Weibull, and Biphasic models could be used to predict thermal inactivation of Salmonella in mash broiler feed. These data may contribute to establishing feed mill microbiological safety standards and reducing Salmonella contamination in broiler feed.

Chemical kinetics, thermodynamics and inactivation kinetics of dextransucrase activity by ultrasound treatment

In this work, the impact of ultrasound on dextransucrase activity was investigated, and a biphasic model was introduced to investigate the inactivation kinetics of the dextransucrase catalytic reaction. In addition, a chemical kinetic model, the Michaelis–Menten equation, Eyring transition state theory and the Arrhenius equation were applied. Short periods of exposure to low-intensity ultrasound significantly increased the activity of dextransucrase. The maximum activity was 1.25 ± 0.01 u/mL at an ultrasound intensity of 1.8 W/cm3 for 3 min, which was 27.6% higher than the activity of the untreated enzyme (0.98 ± 0.038 U/mL). In addition, after the ultrasound treatment, the kinetic model of the dextransucrase catalytic reaction was fitted to a first-order kinetic model at low sucrose concentrations. At low sucrose concentrations, the Ea, ΔH, ΔS and ΔG of ultrasound-treated dextransucrase were reduced by 33.7, 35.7, 28.8 and 0.38%, respectively. Furthermore, compared with the parameters of the untreated sample, the value of Vmax the treated sample increased, and Km decreased. The thermal inactivation model of the dextransucrase catalytic reaction in a shaker was fitted to a biphasic model, and the percentage of the thermally stable fraction of ultrasound-treated dextransucrase was increased, while the rate of deactivation was decreased. Moreover, the degree of thermal inactivation was inversely proportional to the dextransucrase concentration. The fluorescence spectra showed a decrease in the amount of tryptophan on the surface of dextransucrase treated with ultrasound. In conclusion, short-term treatment with low ultrasound intensity increases the activity, thermal stability and reaction rate of dextransucrase.

Kinetics of the thermal inactivation and the refolding of bacterial luciferases in Bacillus subtilis and in Escherichia coli differ

Here we present a study of the thermal inactivation and the refolding of the proteins in Gram positive Bacillus subtilis. To enable use of bacterial luciferases as the models for protein thermal inactivation and refolding in B. subtilis cells, we developed a variety of bright luminescent B. subtilis strains which express luxAB genes encoding luciferases of differing thermolability. The kinetics of the thermal inactivation and the refolding of luciferases from Photorhabdus luminescens and Photobacterium leiognathi were compared in Gram negative and Gram positive bacteria. In B. subtilis cells, these luciferases are substantially more thermostable than in Escherichia coli. Thermal inactivation of the thermostable luciferase P. luminescens in B. subtilis at 48.5°С behaves as a first-order reaction. In E.coli, the first order rate constant (Kt) of the thermal inactivation of luciferase in E. coli exceeds that observed in B. subtilis cells 2.9 times. Incubation time dependence curves for the thermal inactivation of the thermolabile luciferase of P. leiognathi luciferase in the cells of E. coli and B. subtilis may be described by first and third order kinetics, respectively. Here we shown that the levels and the rates of refolding of thermally inactivated luciferases in B. subtilis cells are substantially lower that that observed in E. coli. In dnaK-negative strains of B. subtilis, both the rates of thermal inactivation and the efficiency of refolding are similar to that observed in wild-type strains. These experiments point that the role that DnaKJE plays in thermostability of luciferases may be limited to bacterial species resembling E. coli.

Process risk model for Salmonella and ground chicken.

To develop a process risk model (PRM) for evaluating the safety of individual lots of ground chicken (GC) contaminated with Salmonella (Salm). Data for prevalence, number and serotype of Salm were collected with 25g samples of GC using a combination of methods (whole sample enrichment, quantitative polymerase chain reaction, cultural isolation and serotyping). These data were used to develop a predictive model for Salm contamination of GC as a function of serving size from 25 to 300g. This model was combined with a model for thermal inactivation of Salm in GC and a dose-response model for Salm to develop a PRM in Excel that was simulated with NeuralTools and @Risk. Of 100, 25g samples of GC examined, 19 tested positive for Salm. Three serotypes were isolated: Infantis (n=13), Enteritidis (n=5) and Typhimurium (n=1). The number of Salm ranged from 0 to 2·56 log with a median of 0·93 log per 25g of GC. The PRM predicted that Salm prevalence would increase (P<0·05) from 19 to 57% to 82 to 93% as serving size increased from 25 to 100g to 200 to 300g. However, the total number of Salm in a 100-kg lot of GC and total severity of illness (TSI) were not affected (P>0·05) by serving size. The PRM was also used to evaluate effects of serving size distribution, cooking, food consumption behaviour, consumer demographics and Salmonella virulence on TSI. How a lot of GC is partitioned and consumed does not affect TSI. Scenario analysis demonstrated that the PRM can integrate prevalence, number and serotype data for Salm with consumer handling, consumption and demographics data to identify safe and unsafe lots of GC for improved food safety and public health. Process-risk models like the one developed in this study represent a new, holistic approach to food safety that holds great promise for improving public health and reducing food recalls.

Effect of microstructure and initial cell conditions on thermal inactivation kinetics and sublethal injury of Listeria monocytogenes in fish-based food model systems

The development of more accurate predictive models that describe the microbial kinetics of mild thermal treatments of foods requires knowledge concerning the influence of food microstructure and initial cell conditions on foodborne pathogens’ inactivation kinetics. The effect of food microstructure and initial cell conditions on thermal inactivation kinetics and sublethal injury (SI) of Listeria monocytogenes was investigated at 59, 64 and 69°C. Fish-based food model systems with different microstructures, possessing minimal compositional and physicochemical variations, were used. L. monocytogenes growth morphology had no significant influence on thermal inactivation kinetics. A gelled matrix resulted in a lower specific inactivation rate kmax and a higher residual cell population Nres, while the presence of fat droplets resulted in a higherkmaxand did not influenceNres. SI was higher in viscous than in gelled systems and more prominent for cells that were grown inside the matrix. Hence, predictive thermal inactivation models could benefit from the inclusion of factors related to the nature of the food matrix and fat properties. Starting inactivation from cells that were grown inside the matrix, resulted in lower (i.e., fail-safe)kmaxvalues and more uncertainty onNres as compared to starting from cells grown at optimal conditions.

Predictive models for thermal inactivation of human norovirus and surrogates in strawberry puree

Frozen berries contaminated with human norovirus (hNV) have been frequently identified as cause of foodborne gastroenteritis. To prevent virus transmission, heating can be applied to the berries. Here, the thermal inactivation of hNV in strawberry puree was assessed. Due to the lack of a reliable system for hNV infectivity assessment, capsid integrity assays using RNase treatment prior to detection of protected viral RNA were applied. In addition, murine norovirus (MNV) and Tulane virus (TV) served as surrogates. The method was optimized to allow direct comparisons between the viruses. The results indicated that infectious MNV is slightly more stable than TV. Both viruses were completely inactivated (>7 log10 reductions) after treatment at 80 °C for 8 s. TV infectivity decreased faster than capsid-protected RNA. In addition, TV showed a markedly lower stability compared to hNV using capsid integrity assays. Predictive models were generated for all viruses and D- and ɀ-values were calculated. The tertiary model covering reduction of hNV capsid-protected RNA between 50 and 80 °C suggests that temperatures under 70 °C are not reliable for inactivation. About 3.5 log10 reductions are achieved by heating at 80 °C for 8 s. Further studies should focus on the model validation with direct hNV infectivity data.

Thermal Inactivation of Shiga Toxin–Producing Escherichia coli in Ground Beef with Varying Fat Content

Decimal reduction time ( D-value) was calculated for six non-O157 Shiga toxin-producing Escherichia coli (STEC) in a laboratory medium and ground beef. For the laboratory medium, an overnight culture of each strain of STEC was divided into 10-mL sample bags and heated in a water bath for a specific time on the basis of the temperatures. Survival curves were generated by plotting the surviving bacterial population against time, and a linear-log primary model was used to estimate the D-values from survival curves. The z-values (the temperature raised to reduce the D-value by one-tenth) were calculated by plotting the log D-values against temperature. Similarly, for ground beef, six fat contents, 5, 10, 15, 20, 25, and 30% of ground beef were formulated for this study. Inoculated meat was divided into 5-g pouches and submerged in a water bath set at specific temperatures (55, 60, 65, 68, and 71.1°C). The average D-value for these strains in a laboratory medium was 17.96 min at 55°C, which reduced significantly ( P < 0.05) to 1.58 min at 60°C, and then further reduced ( P < 0.05) to 0.46 min at 65°C. In ground beef, a negative correlation ( P < 0.05) between fat content of ground beef and D-values was observed at 55°C. However, at temperatures greater than 60°C, there was no impact ( P > 0.05) of fat content of ground beef on the thermal resistance of non-O157 STECs. Irrespective of the fat content of ground beef, the D-values ranged from 15.93 to 11.69, 1.15 to 1.12, and 0.14 to 0.09 min and 0.05 at 55, 60, 65, and 68°C, respectively. The data generated from this study can be helpful for the meat industry to develop predictive models for thermal inactivation of non-O157 STECs in ground beef with varying fat content.

Praedicere Possumus: An Italian web-based application for predictive microbiology to ensure food safety.

The use of predictive modelling tools, which mainly describe the response of microorganisms to a particular set of environmental conditions, may contribute to a better understanding of microbial behaviour in foods. In this paper, a tertiary model, in the form of a readily available and userfriendly web-based application Praedicere Possumus (PP) is presented with research examples from our laboratories. Through the PP application, users have access to different modules, which apply a set of published models considered reliable for determining the compliance of a food product with EU safety criteria and for optimising processing throughout the identification of critical control points. The application pivots around a growth/no-growth boundary model, coupled with a growth model, and includes thermal and non-thermal inactivation models. Integrated functionalities, such as the fractional contribution of each inhibitory factor to growth probability (f) and the time evolution of the growth probability (Pt), have also been included. The PP application is expected to assist food industry and food safety authorities in their common commitment towards the improvement of food safety.

PH dependent C. jejuni thermal inactivation models and application to poultry scalding

Campylobacter jejuni related outbreaks and prevalence on retail poultry products pose threats to public health and cause financial burden worldwide. To resolve these problems, it is imperative to take a closer look at poultry processing practices and standards. Using available data (D-values) on the thermal inactivation of C. jejuni we develop a comprehensive inactivation model, taking into account the variation of strain-specific heat resistance, experimental method, and suspension pH. Utilizing our C. jejuni thermal inactivation model, we study the poultry scalding process. We present a mechanistic model of bacteria transfer and inactivation during a typical immersion scald in a high-speed industrial plant. Integration of our C. jejuni inactivation model into the scalding model culminates in validation against industrial processing data. In particular, we successfully predict bacteria concentrations in the scald water and link key factors such as scald water pH and temperature to cross-contamination and overall microbiological quality of carcasses. Furthermore, we demonstrate the applicability of our inactivation model for scalding operations at seven Canadian poultry plants. In addition to providing recommendations for best-practice and a review of scalding research, our work is intended to act as a modular foundation for further research in the interest of public health and financial well-being.

Neural Network Model for Thermal Inactivation of Salmonella Typhimurium to Elimination in Ground Chicken: Acquisition of Data by Whole Sample Enrichment, Miniature Most-Probable-Number Method

Predictive models are valuable tools for assessing food safety. Existing thermal inactivation models for Salmonella and ground chicken do not provide predictions above 71°C, which is below the recommended final cooked temperature of 73.9°C for chicken. They also do not predict when all Salmonella are eliminated without extrapolating beyond the data used to develop them. Thus, a study was undertaken to develop a model for thermal inactivation of Salmonella to elimination in ground chicken at temperatures above those of existing models. Ground chicken thigh portions (0.76 cm3) in microcentrifuge tubes were inoculated with 4.45 ± 0.25 log most probable number (MPN) of a single strain of Salmonella Typhimurium (chicken isolate). They were cooked at 50 to 100°C in 2 or 2.5°C increments in a heating block that simulated two-sided pan frying. A whole sample enrichment, miniature MPN (WSE-mMPN) method was used for enumeration. The lower limit of detection was one Salmonella cell per portion. MPN data were used to develop a multiple-layer feedforward neural network model. Model performance was evaluated using the acceptable prediction zone (APZ) method. The proportion of residuals in an APZ (pAPZ) from -1 log (fail-safe) to 0.5 log (fail-dangerous) was 0.911 (379 of 416) for dependent data and 0.910 (162 of 178) for independent data for interpolation. A pAPZ ≥0.7 indicated that model predictions had acceptable bias and accuracy. There were no local prediction problems because pAPZ for individual thermal inactivation curves ranged from 0.813 to 1.000. Independent data for interpolation satisfied the test data criteria of the APZ method. Thus, the model was successfully validated. Predicted times for a 1-log reduction ranged from 9.6 min at 56°C to 0.71 min at 100°C. Predicted times for elimination ranged from 8.6 min at 60°C to 1.4 min at 100°C. The model will be a valuable new tool for predicting and managing this important risk to public health.

Modeling the Effect of Temperature and Water Activity on the Thermal Resistance of Salmonella Enteritidis PT 30 in Wheat Flour

Salmonella continues to be a problem associated with low-moisture foods, particularly given enhanced thermal resistance at lower water activity (aw). However, there is a scarcity of thermal inactivation models accounting for the effect of aw. The objective of this study was to test multiple secondary models for the effect of product (wheat flour) aw on Salmonella enterica Enteritidis phage type 30 thermal resistance. A full-factorial experimental design included three temperatures (75, 80, and 85°C) and four aw values (~0.30, 0.45, 0.60, and 0.70). Prior to isothermal treatment, sample aw was achieved by equilibrating samples in a humidity-controlled conditioning chamber. Two primary models (log linear and Weibull type) and three secondary models (second-order response surface, modified Bigelow type, and combined effects) were evaluated using the corrected Akaike information criterion and root mean squared errors. Statistical analyses of the primary models favored the log-linear model. Incorporating the three secondary models into the log-linear primary model yielded root mean squared errors of 2.1, 0.78, and 0.96 log CFU/g and corrected Akaike information criterion values of 460, -145, and -19 for the response surface, modified Bigelow, and combined-effects models, respectively. The modified Bigelow-type model, which exponentially scaled both temperature and aw effects on thermal inactivation rates, predicted Salmonella lethality significantly better (P < 0.05) than did the other secondary models examined. Overall, aw is a critical factor affecting thermal inactivation of Salmonella in low-moisture products and should be appropriately included in thermal inactivation models for these types of systems.

Comparative thermal inactivation analysis of Aspergillus oryzae and Thiellavia terrestris cutinase: Role of glycosylation.

Cutinase thermostability is important so that the enzymes can function above the glass transition of what are often rigid polymer substrates. A detailed thermal inactivation analysis was performed for two well-characterized cutinases, Aspergillus oryzae Cutinase (AoC) and Thiellavia terrestris Cutinase (TtC). Both AoC and TtC are prone to thermal aggregation upon unfolding at high temperature, which was found to be a major reason for irreversible loss of enzyme activity. Our study demonstrates that glycosylation stabilizes TtC expressed in Pichia pastoris by inhibiting its thermal aggregation. Based on the comparative thermal inactivation analyses of non-glycosylated AoC, glycosylated (TtC-G), and non-glycosylated TtC (TtC-NG), a unified model for thermal inactivation is proposed that accounts for thermal aggregation and may be applicable to other cutinase homologues. Inspired by glycosylated TtC, we successfully employed glycosylation site engineering to inhibit AoC thermal aggregation. Indeed, the inhibition of thermal aggregation by AoC glycosylation was greater than that achieved by conventional use of trehalose under a typical condition. Collectively, this study demonstrates the excellent potential of implementing glycosylation site engineering for thermal aggregation inhibition, which is one of the most common reasons for the irreversible thermal inactivation of cutinases and many proteins. Biotechnol. Bioeng. 2017;114: 63-73. © 2016 Wiley Periodicals, Inc.

Application of a Nonlinear Model to Transcript Levels of Upregulated Stress Response Gene ibpA in Stationary-Phase Salmonella enterica Subjected to Sublethal Heat Stress

Sublethal heating, which can occur during slow cooking of meat products, is known to induce increased thermal resistance in Salmonella. However, very few studies have addressed the kinetics of this response. Although several recent studies have reported improved thermal inactivation models that include the effect of prior sublethal history on subsequent thermal resistance, none of these models were based on cellular-level responses to sublethal thermal stress. The goal of this study was to determine whether a nonlinear model could accurately portray the response of Salmonella to heat stress induced by prolonged exposure to sublethal temperatures. To accomplish this, stationary-phase Salmonella Montevideo cultures were subjected to various heating profiles (held at either 40 or 45°C for 0, 5, 10, 15, 30, 60, 90, 180, or 240 min) using a PCR thermal cycler. Differential plating on selective and nonselective media was used to confirm the presence of cellular injury. Reverse transcription quantitative PCR was used to screen the transcript levels of six heat stress-related genes to find candidate genes for nonlinear modeling. Injury was detected in populations of Salmonella held at 45°C for 30, 60, and 90 min and at 40°C for 0, 5, and 90 min (P < 0.05), whereas no significant injury was found at 180 and 240 min (P > 0.05). The transcript levels of ibpA, which codes for a small heat shock protein associated with the ClpB and DnaK-DnaJ-GrpE chaperone systems, showed the greatest increase relative to the transcript levels at 0 min, which was significant at 5, 10, 15, 30, 60, 90, and 180 min at 45°C and at 5, 10, 15, 30, 60, and 90 min at 40°C (P < 0.05). Using ibpA transcript levels as an indicator of adaptation to thermal stress, a nonlinear model for sublethal injury is proposed. The use of variables indicating the physiological state of the pathogen during stress has the potential to increase the accuracy of thermal inactivation models that must account for prolonged exposure to sublethal temperatures.

Kinetic models for pulsed electric field and thermal inactivation of Escherichia coli and Pseudomonas fluorescens in whole milk

Inactivation of Escherichia coli ATCC 11775 and Pseudomonas fluorescens ATCC 948 in UHT whole (4% fat) milk during thermal processing at 56–62 °C and pulsed electric field (PEF) processing at 30 or 35 kV cm−1 at approximately 30, 40 or 50 °C was investigated. E. coli ATCC 11775 was more heat-resistant than P. fluorescens ATCC 948, but more susceptible to PEF processing. All inactivation kinetics showed strong deviations from log-linearity. Thus, a simplified logistic (log-decay) regression model was used to accurately predict thermal and PEF inactivation of E. coli ATCC 11775 and P. fluorescens ATCC 948 under various treatment conditions. This is a useful tool for identifying processing conditions to inactivate pathogenic and spoilage microorganisms in whole milk at sub-pasteurisation temperatures.

Evaluation of heat treatments, different from those currently established in the EU legislation, that could be applied to live bivalve molluscs from B and C production areas, that have not been submitted to purification or relaying, in order to eliminate pathogenic microorganisms

EU rules state that unpurified live bivalve molluscs from B and C production areas must undergo specified heat treatment to eliminate pathogenic microorganisms. Alternative time-temperature conditions were evaluated to the permitted treatment of at least 90°C for at least 90 seconds (s) in the mollusc flesh. The most important viral hazards associated with bivalve molluscs were identified as Norovirus (NoV) and Hepatitis A virus (HAV). A HAV thermal inactivation model was developed to identify equivalent (achieve the same log reduction) time-temperature combinations to 90°C for 90 s. The model was based on HAV inactivation data in mollusc matrices during isothermal heat treatment and estimated the z-value as 27.5°C. Evaluation against inactivation in whole bivalve molluscs showed that the observed HAV inactivation is in general higher than predicted. Under the conditions and matrices studied HAV is generally more heat tolerant than NoV surrogates. The model provided alternative processes equivalent to 90°C for 90 s without considering the effect of heat-up and cool-down times on virus inactivation. As confirmed by industrial profiles, there is a heat-up and cool-down time that will enhance the safety of the final product and can lead to variations in HAV reduction depending on the process design. This shows the need for a Performance Criterion (PC) for the whole process, which is the required log reduction during heat treatment. A risk assessment model was developed and a case study illustrated the relationship between a PC and the HAV risk at consumption. If risk managers establish an ALOP, this can be translated to a PC and a Process Criterion (PrC). It is demonstrated that a PrC expressed as an F-value (the equivalent processing time of a hypothetical isothermal process at a reference temperature) is more appropriate than the currently used time-temperature combination since it takes into account non-isothermal conditions.

Evaluation of Salmonella Thermal Inactivation Model Validity for Slow Cooking of Whole-Muscle Meat Roasts in a Pilot-Scale Oven

Sublethal heating can increase subsequent thermal resistance of bacteria, which may compromise the validity of thermal process validations for slow-roasted meats. Therefore, this research evaluated the accuracy of a traditional log-linear inactivation model, developed via prior laboratory-scale isothermal tests, and a novel path-dependent model accounting for sublethal injury, applied to pilot-scale slow cooking of whole-muscle roasts. Irradiated turkey breasts, beef rounds, and pork loins were inoculated with an eight-serovar Salmonella cocktail via vacuum tumble marination in a salt-phosphate marinade. The resulting initial Salmonella population in the geometric center (core) was 7.0, 6.3, and 6.3 log CFU/g for turkey, beef, and pork, respectively. Seven different cooking schedules representing industry practices were evaluated in a pilot-scale, moist-air convection oven. Core temperatures recorded during cooking were used to calculate lethality real-time via the log-linear model. The path-dependent model reduced the bias (mean residual) and root mean square error by 4.24 and 4.60 log CFU/g respectively, in turkey; however, the new model did not reduce the prediction error in beef or pork. Overall, results demonstrated that slow-cooked roasts, processed to a computed lethality at or near that required by the regulatory performance standards, as calculated with a state-dependent model, may be underprocessed.