Modelling the growth rate of Listeria monocytogenes with a multiplicative type model including interactions between environmental factors

Prevalence of Listeria monocytogenes in RTE Meat Products of Quevedo (Ecuador)

Listeria monocytogenes is a foodborne pathogen that causes listeriosis and can be a problem in areas where meat products are sold at unregulated storage temperatures. In this work, the prevalence of L. monocytogenes was determined in the five most widely traded meat products in the province of Quevedo (Ecuador): bacon, "chorizo paisa", grilled hamburger meat, mortadella, and salami. A total of 1000 samples of these products were analyzed in two seasons of the year (dry season/rainy season). All L. monocytogenes isolates were confirmed by PCR with primers designed for the iap gene. Furthermore, the positive samples were quantified for L. monocytogenes. Of the 1000 meat products analyzed, 163 were positive for L. monocytogenes (16.3%). The prevalence of L. monocytogenes in the two seasons in different meat products was as follows: 22.5% in mortadella, 19% in hamburger meat, 15% in bacon, 14.5% in chorizo paisa and 10.5% in salami. In addition, the concentration of L. monocytogenes in most of the positive samples was in the range of 4-6 log CFU/g or even higher. The results show the need for improvements in the hygienic measures and meat storage temperatures in Quevedo (Ecuador) to avoid risks of foodborne listeriosis.

The effect of pH on the growth rate of Bacillus cereus sensu lato: Quantifying strain variability and modelling the combined effects of temperature and pH

In this study, the effect of pH, alone or in combination with temperature, on the maximum growth rate (μ_max) of B. cereus sensu lato was investigated. In phase 1, the effect of pH at 30 °C was studied for 16 mesophilic strains and 2 psychrotrophic strains of Bacillus cereus sensu lato. The μ_max vs. pH relationship was found to show a similar pattern for all the strains. Several pH models from literature were evaluated and the best performing 'growth rate vs. pH' model selected. A stochastic model was then developed to predict the maximum specific growth rate of mesophilic B. cereus at 30 °C as a function of pH, the intra-species variability being incorporated via considering the model parameters (e.g. pH_min) randomly distributed. The predicted maximum specific growth rates were acceptably close to independent published data. In phase 2, the combined effects of temperature and pH were studied. Growth rates were also generated at 15, 20 and 40 °C for a selection of strains and the pH model was fitted at each temperature. Interestingly, the results showed that the estimates for the pH_min parameter for mesophilic strains were lower at 20-30 °C than near the optimum temperature (40 °C), suggesting that experiments for the determination of this parameter should be conducted at lower-than-optimum temperatures. New equations were proposed for the relationship between temperature and the minimum pH-values, which were also consistent with the experimental growth boundaries. The parameters defining this equation quantify the minimum temperature for growth observed experimentally, the temperature of maximum enzyme stability and the maximum temperature for growth. Deviations from the Gamma hypothesis (multiplicative effects of environmental factors on the maximum specific growth rate) were observed near the growth limits, especially at 40 °C. To improve model performance, two approaches, one based on a minimum pH-term (doi: https://doi.org/10.3389/fmicb.2019.01510) and one based on an interaction term (doi: http://dx.doi.org/10.1016/S0168-1605(01)00640-7) were evaluated.

The Inclusion of the Food Microstructural Influence in Predictive Microbiology: State-of-the-Art

Predictive microbiology has steadily evolved into one of the most important tools to assess and control the microbiological safety of food products. Predictive models were traditionally developed based on experiments in liquid laboratory media, meaning that food microstructural effects were not represented in these models. Since food microstructure is known to exert a significant effect on microbial growth and inactivation dynamics, the applicability of predictive models is limited if food microstructure is not taken into account. Over the last 10-20 years, researchers, therefore, developed a variety of models that do include certain food microstructural influences. This review provides an overview of the most notable microstructure-including models which were developed over the years, both for microbial growth and inactivation.

Modeling the Growth and Interaction Between Brochothrix thermosphacta, Pseudomonas spp., and Leuconostoc gelidum in Minced Pork Samples

The aim of this study was to obtain the growth parameters of specific spoilage micro-organisms previously isolated in minced pork (MP) samples and to develop a three-spoilage species interaction model under different storage conditions. Naturally contaminated samples were used to validate this approach by considering the effect of the food microbiota. Three groups of bacteria were inoculated on irradiated samples, in mono- and in co-culture experiments (n = 1152): Brochothrix thermosphacta, Leuconostoc gelidum, and Pseudomonas spp. (Pseudomonas fluorescens and Pseudomonas fragi). Samples were stored in two food packaging [food wrap and modified atmosphere packaging (CO2 30%/O2 70%)] at three isothermal conditions (4, 8, and 12°C). Analysis was carried out by using both 16S rRNA gene amplicon sequencing and classical microbiology in order to estimate bacterial counts during the storage period. Growth parameters were obtained by fitting primary (Baranyi) and secondary (square root) models. The food packaging shows the highest impact on bacterial growth rates, which in turn have the strongest influence on the shelf life of food products. Based on these results, a three-spoilage species interaction model was developed by using the modified Jameson-effect model and the Lotka Volterra (prey-predator) model. The modified Jameson-effect model showed slightly better performances, with 40-86% out of the observed counts falling into the Acceptable Simulation Zone (ASZ). It only concerns 14-48% for the prey-predator approach. These results can be explained by the fact that the dynamics of experimental and validation datasets seems to follow a Jameson behavior. On the other hand, the Lotka Volterra model is based on complex interaction factors, which are included in highly variable intervals. More datasets are probably needed to obtained reliable factors, and so better model fittings, especially for three- or more-spoilage species interaction models. Further studies are also needed to better understand the interaction of spoilage bacteria between them and in the presence of natural microbiota.

New Term to Quantify the Effect of Temperature on pH min -Values Used in Cardinal Parameter Growth Models for Listeria monocytogenes

The aim of this study was to quantify the influence of temperature on pH_min-values of Listeria monocytogenes as used in cardinal parameter growth models and thereby improve the prediction of growth for this pathogen in food with low pH. Experimental data for L. monocytogenes growth in broth at different pH-values and at different constant temperatures were generated and used to determined pH_min-values. Additionally, pH_min-values for L. monocytogenes available from literature were collected. A new pH_min-function was developed to describe the effect of temperatures on pH_min-values obtained experimentally and from literature data. A growth and growth boundary model was developed by substituting the constant pH_min-value present in the Mejlholm and Dalgaard (2009) model (J. Food. Prot. 72, 2132–2143) by the new pH_min-function. To obtain data for low pH food, challenge tests were performed with L. monocytogenes in commercial and laboratory-produced chemically acidified cheese including glucono-delta-lactone (GDL) and in commercial cream cheese. Furthermore, literature data for growth of L. monocytogenes in products with or without GDL were collected. Evaluation of the new and expanded model by comparison of observed and predicted μ_max-values resulted in a bias factor of 1.01 and an accuracy factor of 1.48 for a total of 1,129 growth responses from challenge tests and literature data. Growth and no-growth responses of L. monocytogenes in seafood, meat, non-fermented dairy products, and fermented cream cheese were 90.3% correctly predicted with incorrect predictions being 5.3% fail-safe and 4.4% fail-dangerous. The new pH_min-function markedly extended the range of applicability of the Mejlholm and Dalgaard (2009) model from pH 5.4 to pH 4.6 and therefore the model can now support product development, reformulation or risk assessment of food with low pH including chemically acidified cheese and cream cheese.

Listeria monocytogenes contamination of ready-to-eat foods and the risk for human health in the EU

Food safety criteria for Listeria monocytogenes in ready-to-eat (RTE) foods have been applied from 2006 onwards (Commission Regulation (EC) 2073/2005). Still, human invasive listeriosis was reported to increase over the period 2009-2013 in the European Union and European Economic Area (EU/EEA). Time series analysis for the 2008-2015 period in the EU/EEA indicated an increasing trend of the monthly notified incidence rate of confirmed human invasive listeriosis of the over 75 age groups and female age group between 25 and 44 years old (probably related to pregnancies). A conceptual model was used to identify factors in the food chain as potential drivers for L. monocytogenes contamination of RTE foods and listeriosis. Factors were related to the host (i. population size of the elderly and/or susceptible people; ii. underlying condition rate), the food (iii. L. monocytogenes prevalence in RTE food at retail; iv. L. monocytogenes concentration in RTE food at retail; v. storage conditions after retail; vi. consumption), the national surveillance systems (vii. improved surveillance), and/or the bacterium (viii. virulence). Factors considered likely to be responsible for the increasing trend in cases are the increased population size of the elderly and susceptible population except for the 25-44 female age group. For the increased incidence rates and cases, the likely factor is the increased proportion of susceptible persons in the age groups over 45 years old for both genders. Quantitative modelling suggests that more than 90% of invasive listeriosis is caused by ingestion of RTE food containing > 2,000 colony forming units (CFU)/g, and that one-third of cases are due to growth in the consumer phase. Awareness should be increased among stakeholders, especially in relation to susceptible risk groups. Innovative methodologies including whole genome sequencing (WGS) for strain identification and monitoring of trends are recommended.

Mechanistic modelling of the inhibitory effect of pH on microbial growth

Modelling and simulation of microbial dynamics as a function of processing, transportation and storage conditions is a useful tool to improve microbial food safety and quality. The goal of this research is to improve an existing methodology for building mechanistic predictive models based on the environmental conditions. The effect of environmental conditions on microbial dynamics is often described by combining the separate effects in a multiplicative way (gamma concept). This idea was extended further in this work by including the effects of the lag and stationary growth phases on microbial growth rate as independent gamma factors. A mechanistic description of the stationary phase as a function of pH was included, based on a novel class of models that consider product inhibition. Experimental results on Escherichia coli growth dynamics indicated that also the parameters of the product inhibition equations can be modelled with the gamma approach. This work has extended a modelling methodology, resulting in predictive models that are (i) mechanistically inspired, (ii) easily identifiable with a limited work load and (iii) easily extended to additional environmental conditions.

An interaction model for the combined effect of temperature, pH and water activity on the growth rate of E. coli K12

Previous research has indicated that more complex model structures than the commonly used gamma model are needed to obtain an accurate prediction of the effect of multiple environmental conditions on the microbial growth rate. Due to the complexity associated with the development of such model structures, it is recommended that the model structure is compatible with a modular model building method. In this research, a gamma-interaction model was built to describe the combined effect of temperature, pH and water activity on the microbial growth rate of E. coli K12 based on a dataset of 68 bioreactor experiments. This novel interaction model was compared with the standard gamma model. The model structures were tested separately for the combined effects of (i) temperature and pH, (ii) pH and water activity, (iii) temperature and water activity and (iv) temperature, pH and water activity. Based on the results of this research, it was concluded that models for the combined effect of environmental conditions need to allow for sufficient flexibility for the description of combined effects of environmental conditions to obtain accurate model predictions. In the current study, this flexibility was successfully introduced by using the gamma-interaction model. A cross-validation study also demonstrated that the predictions of the interaction model are more robust with respect to the specific data used than the gamma model. As such, the gamma-interaction model provides food producers and food safety authorities with a more accurate and reliable tool for the prediction of the microbial growth rate as a function of multiple environmental conditions.

Modelling the effect of combined antimicrobials: A base model for multiple-hurdles

Combining antimicrobials to reduce microbial growth and to combat the potential impact of antimicrobial resistance is an important subject both in foods and in pharmaceutics. Modelling of combined treatments designed to reduce or eliminate microbial contamination in foods (microbiological predictive modelling) has become commonplace. Two main reference models are used to analyse mixtures: the Bliss Independence and the Loewe reference models (LRM). By using optical density to analyse the growth of Aeromonas hydrophila, Cronobacter sakazakii and Escherichia coli in combined NaCl/NaCl (a mock combination experiment) and combined NaCl/KCl experiments, previous models for combined antimicrobials in foods, based on the Bliss approach, were shown to be inconsistent and that models based on the LRM more applicable. The LRM was shown, however, to be valid only in the specific cases where the concentration exponents of all components in a mixture were identical. This is assured for a mock combination experiment but not for a true mixture. This, essentially, invalidates the LRM as a general reference model. A new model, based on the LRM but allowing for mixed exponents, was used to analyse the combined inhibition data, and concluded that the NaCl/KCl system gave the additive effect expected from literature studies. This study suggests the need to revise current models used to analyse combined effects.

Effects of Soluble Gas Stabilisation, Modified Atmosphere, Gas to Product Volume Ratio and Storage on the Microbiological and Sensory Characteristics of Ready-to-Eat Shrimp (Pandalus borealis)

The effects of storage time, modified atmospheres (30% or 60% CO2), soluble gas stabilisation and gas to product volume ( g/ p) ratio were investigated on the microbiological and sensory characteristics of cooked, peeled and brined ready-to-eat (RTE) deep-water shrimps ( Pandalus borealis). Soluble gas stabilisation (SGS) treatment prior to packaging (2h) increased the CO2 content in the packaged shrimp and counteracted package collapse, even at low g/ p ratios (0.66). SGS treatment reduced significantly (P 0.01) the aerobic plate count and psychrotrophic count. The increase of CO2 levels during modified atmosphere (MA) packaging and the application of SGS significantly enhanced (P 0.01) the sensory quality of the shrimps. The exudates in the packages (%) were significantly reduced (P 0.01) when applying SGS treatment. Therefore, SGS treatment in combination with MA packaging can be used successfully on RTE shrimps to reduce the package volume and to improve the microbiological and sensory characteristics.

Modeling and Validation of the Ecological Behavior of Wild-Type Listeria monocytogenes and Stress-Resistant Variants

Listeria monocytogenes exhibits a heterogeneous response upon stress exposure which can be partially attributed to the presence of stable stress-resistant variants. This study aimed to evaluate the impact of the presence of stress-resistant variants of Listeria monocytogenes and their corresponding trade-offs on population composition under different environmental conditions. A set of stress robustness and growth parameters of the wild type (WT) and an rpsU deletion variant was obtained and used to model their growth behavior under combined mild stress conditions and to model their kinetics under single- and mixed-strain conditions in a simulated food chain. Growth predictions for the WT and the rpsU deletion variant matched the experimental data generally well, although some deviations from the predictions were observed. The data highlighted the influence of the environmental conditions on the ratio between the WT and variant. Prediction of performance in the simulated food chain proved to be challenging. The trend of faster growth and lower stress robustness for the WT than for the rpsU variant in the different steps of the chain was confirmed, but especially for the inactivation steps and the time needed to resume growth after an inactivation step, the experimental data deviated from the model predictions. This report provides insights into the conditions which can select for stress-resistant variants in industrial settings and discusses their potential persistence in food processing environments.

IMPORTANCE

Listeria monocytogenes exhibits a heterogeneous stress response which can partially be attributed to the presence of genetic variants. These stress-resistant variants survive better under severe conditions but have, on the other hand, a reduced growth rate. To date, the ecological behavior and potential impact of the presence of stress-resistant variants is not fully understood. In this study, we quantitatively assessed growth and inactivation behavior of wild-type L. monocytogenes and its stress-resistant variants. Predictions were validated under different conditions, as well as along a model food chain. This work illustrates the effects of environmental factors on population dynamics of L. monocytogenes and is a first step in evaluating the impact of population diversity on food safety.

Introducing a novel interaction model structure for the combined effect of temperature and pH on the microbial growth rate

Efficient modelling of the microbial growth rate can be performed by combining the effects of individual conditions in a multiplicative way, known as the gamma concept. However, several studies have illustrated that interactions between different effects should be taken into account at stressing environmental conditions to achieve a more accurate description of the growth rate. In this research, a novel approach for modeling the interactions between the effects of environmental conditions on the microbial growth rate is introduced. As a case study, the effect of temperature and pH on the growth rate of Escherichia coli K12 is modeled, based on a set of computer controlled bioreactor experiments performed under static environmental conditions. The models compared in this case study are the gamma model, the model of Augustin and Carlier (2000), the model of Le Marc et al. (2002) and the novel multiplicative interaction model, developed in this paper. This novel model enables the separate identification of interactions between the effects of two (or more) environmental conditions. The comparison of these models focuses on the accuracy, interpretability and compatibility with efficient modeling approaches. Moreover, for the separate effects of temperature and pH, new cardinal parameter model structures are proposed. The novel interaction model contributes to a generic modeling approach, resulting in predictive models that are (i) accurate, (ii) easily identifiable with a limited work load, (iii) modular, and (iv) biologically interpretable.

Sensitivity analysis for critical control points determination and uncertainty analysis to link FSO and process criteria: application to Listeria monocytogenes in soft cheese made from pasteurized milk

Microbiological food safety is an important economic and health issue in the context of globalization and presents food business operators with new challenges in providing safe foods. The hazard analysis and critical control point approach involve identifying the main steps in food processing and the physical and chemical parameters that have an impact on the safety of foods. In the risk-based approach, as defined in the Codex Alimentarius, controlling these parameters in such a way that the final products meet a food safety objective (FSO), fixed by the competent authorities, is a big challenge and of great interest to the food business operators. Process risk models, issued from the quantitative microbiological risk assessment framework, provide useful tools in this respect. We propose a methodology, called multivariate factor mapping (MFM), for establishing a link between process parameters and compliance with a FSO. For a stochastic and dynamic process risk model of Listeriamonocytogenes in soft cheese made from pasteurized milk with many uncertain inputs, multivariate sensitivity analysis and MFM are combined to (i) identify the critical control points (CCPs) for L.monocytogenes throughout the food chain and (ii) compute the critical limits of the most influential process parameters, located at the CCPs, with regard to the specific process implemented in the model. Due to certain forms of interaction among parameters, the results show some new possibilities for the management of microbiological hazards when a FSO is specified.

Sporulation boundaries and spore formation kinetics of Bacillus spp. as a function of temperature, pH and a(w)

Sporulation niches in the food chain are considered as a source of hazard and are not clearly identified. Determining the sporulation environmental boundaries could contribute to identify potential sporulation niches. Spore formation was determined in a Sporulation Mineral Buffer. The effect of incubation temperature, pH and water activity on time to one spore per mL, maximum sporulation rate and final spore concentration was investigated for a Bacillus weihenstephanensis and a Bacillus licheniformis strain. Sporulation boundaries of B. weihenstephanensis and of B. licheniformis were similar to, or included within, the range of temperatures, pH and water activities supporting growth. For instance, sporulation boundaries of B. weihenstephanensis were evaluated at 5°C, 35°C, pH 5.2 and a(w) 0.960 while growth boundaries were observed at 5°C, 37°C, pH 4.9 and a(w) 0.950. Optimum spore formation was determined at 30°C pH 7.2 for B. weihenstephanensis and at 45°C pH 7.2 for B. licheniformis. Lower temperatures and pH delayed the sporulation process. For instance, the time to one spore per mL was tenfold longer when sporulation occurred at 10°C and 20°C, for each strain respectively, than at optimum sporulation temperature. The relative effect of temperature and pH on sporulation rates and on growth rates is similar. This work suggests that the influence of environmental factors on the quantitative changes in sporulation boundaries and rates was similar to their influence on changes in growth rate.

Establishing equivalence for microbial-growth-inhibitory effects ("iso-hurdle rules") by analyzing disparate listeria monocytogenes data with a gamma-type predictive model

Preservative factors act as hurdles against microorganisms by inhibiting their growth; these are essential control measures for particular food-borne pathogens. Different combinations of hurdles can be quantified and compared to each other in terms of their inhibitory effect ("iso-hurdle"). We present here a methodology for establishing microbial iso-hurdle rules in three steps: (i) developing a predictive model based on existing but disparate data sets, (ii) building an experimental design focused on the iso-hurdles using the model output, and (iii) validating the model and the iso-hurdle rules with new data. The methodology is illustrated with Listeria monocytogenes. Existing data from industry, a public database, and the literature were collected and analyzed, after which a total of 650 growth rates were retained. A gamma-type model was developed for the factors temperature, pH, a(w), and acetic, lactic, and sorbic acids. Three iso-hurdle rules were assessed (40 logcount curves generated): salt replacement by addition of organic acids, sorbic acid replacement by addition of acetic and lactic acid, and sorbic acid replacement by addition of lactic/acetic acid and salt. For the three rules, the growth rates were equivalent in the whole experimental domain (γ from 0.1 to 0.5). The lag times were also equivalent in the case of mild inhibitory conditions (γ ≥ 0.2), while they were longer in the presence of salt than acids under stress conditions (γ < 0.2). This methodology allows an assessment of the equivalence of inhibitory effects without intensive data generation; it could be applied to develop milder formulations which guarantee microbial safety and stability.

Comparing nonsynergy gamma models and interaction models to predict growth of emetic Bacillus cereus for combinations of pH and water activity values

This research aims to test the absence (gamma hypothesis) or occurrence of synergy between two growth-limiting factors, i.e., pH and water activity (a(w)), using a systematic approach for model selection. In this approach, preset criteria were used to evaluate the performance of models. Such a systematic approach is required to be confident in the correctness of the individual components of the combined (synergy) models. With Bacillus cereus F4810/72 as the test organism, estimated growth boundaries for the a(w)-lowering solutes NaCl, KCl, and glucose were 1.13 M, 1.13 M, and 1.68 M, respectively. The accompanying a(w) values were 0.954, 0.956, and 0.961, respectively, indicating that equal a(w) values result in similar effects on growth. Out of the 12 models evaluated using the preset criteria, the model of J. H. T. Luong (Biotechnol. Bioeng. 27:280-285, 1985) was the best model to describe the effect of a(w) on growth. This a(w) model and the previously selected pH model were combined into a gamma model and into two synergy models. None of the three models was able to describe the combined pH and a(w) conditions sufficiently well to satisfy the preset criteria. The best matches between predicted and experimental data were obtained with the gamma model, followed by the synergy model of Y. Le Marc et al. (Int. J. Food Microbiol. 73:219-237, 2002). No combination of models that was able to predict the impact of both individual and combined hurdles correctly could be found. Consequently, in this case we could not prove the existence of synergy nor falsify the gamma hypothesis.

Modeling and predicting the simultaneous growth of Listeria monocytogenes and natural flora in minced tuna

The growth kinetics of Listeria monocytogenes and natural flora (NF) in minced tuna from 2 to 30 °C were examined, and a simultaneous growth model was developed. The inhibiting effect of the NF on the growth of L. monocytogenes was examined by inoculating different levels of NF isolated from the minced tuna. The kinetic data were fitted to the Baranyi model and estimated the growth parameters such as specific growth rate (μ(max)), maximum population density (N(max)), and lag time. The temperature and inoculated NF dependency on the μ(max) of L. monocytogenes and NF were described by modified Ratkowsky's square-root model. As the initial NF level increased, the slopes of the square-root models were decreased for both L. monocytogenes and NF. The N(max) of L. monocytogenes was described as a function of temperature and inoculated NF level. Simultaneous growth prediction of L. monocytogenes and NF under constant temperature conditions was examined by using the differential equations based on the Baranyi model with the effect of interspecies competition substituted into the developed μ(max) and N(max) models. The root mean square errors between the model prediction and the observation for L. monocytogenes and NF were 0.42 and 0.34, respectively. Predictive simulation under fluctuating temperature conditions also demonstrated a high accuracy of simultaneous prediction for both L. monocytogenes and NF, representing the root mean square errors of 0.19 and 0.34, respectively. These results illustrate that the developed model permits accurate estimation of the behavior of L. monocytogenes in minced tuna under real temperature history until consumption.

Comparing nonsynergistic gamma models with interaction models to predict growth of emetic Bacillus cereus when using combinations of pH and individual undissociated acids as growth-limiting factors

A combination of multiple hurdles to limit microbial growth is frequently applied in foods to achieve an overall level of protection. Quantification of hurdle technology aims at identifying synergistic or multiplicative effects and is still being developed. The gamma hypothesis states that inhibitory environmental factors aiming at limiting microbial growth rates combine in a multiplicative manner rather than synergistically. Its validity was tested here with respect to the use of pH and various concentrations of undissociated acids, i.e., acetic, lactic, propionic, and formic acids, to control growth of Bacillus cereus in brain heart infusion broth. The key growth parameter considered was the maximum specific growth rate, mu(max), as observed by determination of optical density. A variety of models from the literature describing the effects of various pH values and undissociated acid concentrations on mu(max) were fitted to experimental data sets and compared based on a predefined set of selection criteria, and the best models were selected. The cardinal model developed by Rosso (for pH dependency) and the model developed by Luong (for undissociated acid) were found to provide the best fit and were combined in a gamma model with good predictive performance. The introduction of synergy factors into the models was not able to improve the quality of the prediction. On the contrary, inclusion of synergy factors led to an overestimation of the growth boundary, with the inherent possibility of leading to underestimation of the risk under the conditions tested in this research.

The combination of lactate and diacetate synergistically reduces cold growth in brain heart infusion broth across Listeria monocytogenes lineages

Combinations of organic acids are often used in ready-to-eat foods to control the growth of Listeria monocytogenes during refrigerated storage. The purpose of this study was to quantitatively assess synergy between two organic acid growth inhibitors under conditions similar to those present in cold-smoked salmon, and to assess the effect of evolutionary lineage on response to those growth inhibitors. Thirteen strains of L. monocytogenes, representing lineages I and II, were grown at 7 degrees C in broth at pH 6.1 and 4.65% water-phase NaCl, which was supplemented with 2% potassium lactate, 0.14% sodium diacetate, or the combination of both at the same levels. Our data suggest that lineages adapt similarly to these inhibitors, as the only significant growth parameter difference between lineages was a minor effect (+/- 0.16 day, P = 0.0499) on lag phase (lambda). For all strains, lactate significantly extended lambda, from 2.6 +/- 0.4 to 3.8 +/- 0.5 days (P < 0.001), and lowered the maximum growth rate (mu(max)) from 0.54 +/- 0.06 to 0.49 +/- 0.04 log(CFU/ml)/day (P < 0.001), compared with the control. Diacetate was ineffective alone, but in combination with lactate, synergistically increased lambda to 6.6 +/- 1.6 days (P < 0.001) and decreased mu(max) to 0.34 +/- 0.05 log(CFU/ml)/day (P < 0.001). Monte Carlo simulations provided further evidence for synergy between diacetate and lactate by predicting signficantly slower growth to nominal endpoints for the combination of inhibitors. This study shows potassium lactate and sodium diacetate have significant synergistic effects on both lambda and mu(max) of L. monocytogenes at refrigeration temperature in broth, and justifies combining these inhibitors, at effective levels, in food product formulations.

Development and validation of an extensive growth and growth boundary model for Listeria monocytogenes in lightly preserved and ready-to-eat shrimp

An existing cardinal parameter growth and growth boundary model for Listeria monocytogenes (O. Mejlholm and P. Dalgaard, J. Food Prot. 70:70-84 and 2485-2497, 2007) was expanded with terms for the effects of acetic, benzoic, citric, and sorbic acids to include a total of 12 environmental parameters and their interactive effects. The new model predicted growth rates (micro(max) values) of L. monocytogenes accurately with bias and accuracy factors of 1.0 and 1.5, respectively, for 16 batches of brined shrimp with benzoic, citric, and sorbic acids. Corresponding values of 0.9 and 1.2, respectively, were obtained for five batches of brined shrimp with acetic and lactic acids. Growth and no-growth responses of L. monocytogenes were also appropriately predicted with 88% correct prediction for 26 experiments with brined shrimp. The new model performed better than existing L. monocytogenes models with a comparable degree of complexity. The high number of environmental parameters, including six organic acids (acetic acid, benzoic acid, citric acid, diacetate, lactic acid, and sorbic acid), allows the new model to predict the effect of substituting one set of preserving parameters for another. The new model also allowed the distance between the growth boundary and specific product characteristics to be quantified by a psi value. This can be of practical importance in the development or reformulation of seafood with preserving parameters that prevent growth of L. monocytogenes and take variability in product characteristics into account.

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, 1.162, and 0.956, 1.115, 0.713 for [corrected] Growth Predictor and Sym'Previus, respectively.

Effect of salt, smoke compound, and storage temperature on the growth of Listeria monocytogenes in simulated smoked salmon

Smoked salmon can be contaminated with Listeria monocytogenes. It is important to identify the factors that are capable of controlling the growth of L. monocytogenes in smoked salmon so that control measures can be developed. The objective of this study was to determine the effect of salt, a smoke compound, storage temperature, and their interactions on L. monocytogenes in simulated smoked salmon. A six-strain mixture of L. monocytogenes (10(2) to 10(3) CFU/g) was inoculated into minced, cooked salmon containing 0 to 10% NaCl and 0 to 0.4% liquid smoke (0 to 34 ppm of phenol), and the samples were stored at temperatures from 0 to 25 degrees C. Lag-phase duration (LPD; hour), growth rate (GR; log CFU per hour), and maximum population density (MPD; log CFU per gram) of L. monocytogenes in salmon, as affected by the concentrations of salt and phenol, storage temperature, and their interactions, were analyzed. Results showed that L. monocytogenes was able to grow in salmon containing the concentrations of salt and phenol commonly found in smoked salmon at the prevailing storage temperatures. The growth of L. monocytogenes was affected significantly (P < 0.05) by salt, phenol, storage temperature, and their interactions. As expected, higher concentrations of salt or lower storage temperatures extended the LPD and reduced the GR. Higher concentrations of phenol extended the LPD of L. monocytogenes, particularly at lower storage temperatures. However, its effect on reducing the GR of L. monocytogenes was observed only at higher salt concentrations (>6%) at refrigerated and mild abuse temperatures (< 10 degrees C). The MPD, which generally reached 7 to 8 log CFU/g in salmon that supported L. monocytogenes growth, was not affected by the salt, phenol, and storage temperature. Two models were developed to describe the LPD and GR of L. monocytogenes in salmon containing 0 to 8% salt, 0 to 34 ppm of phenol, and storage temperatures of 4 to 25 degrees C. The data and models obtained from this study would be useful for estimating the behavior of L. monocytogenes in smoked salmon.

Survival of Listeria innocua on hot and cold beef carcass surfaces

AIMS

This study aimed to determine the survival and growth of Listeria innocua on hot and cold beef carcass surfaces.

METHODS AND RESULTS

Four sites, the neck, outside round, brisket and foreshank/brisket, were inoculated with L. innocua (i) immediately after dressing while hot and (ii) when cold after chilling. After inoculation, all carcasses were stored at 4 degrees C for 72 h. Survival of L. innocua on cold surfaces declined during storage and was less than on hot carcasses at all times. Data on the survival of L. innocua in broth (maximum recovery diluent) indicated that counts could not be compared with those on carcasses, in particular on cold carcasses.

CONCLUSIONS

The results indicate that L. innocua survives on hot carcass surfaces during chilling, but declines over time on cold surfaces. The decrease in L. innocua counts on cold surfaces may be related to a synergy between the combined stresses of low available water (a(w)) and low temperature.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study is the first to determine the effect of chilling on the survival and growth of Listeria on beef carcass surfaces. The information can potentially be used to determine the survival and growth of the pathogen, L. monocytogenes on beef surfaces.

Modelling the behaviour of Listeria monocytogenes in ground pork as a function of pH, water activity, nature and concentration of organic acid salts

AIMS

to study and model the effect of sodium acetate, sodium lactate, potassium sorbate and combination of acid salts on the behaviour of Listeria monocytogenes in ground pork.

METHODS AND RESULTS

Water activity (a(w)), pH and concentration of acid salt of the meat were adjusted. The behaviour of inoculated L. monocytogenes was studied and modelled according to physicochemical parameters values. Whatever the acid salt concentration used, we observed an inhibition of the growth of L. monocytogenes at pH 5.6 and a(w) 0.95. At pH 6.2 and a(w) 0.97, addition of 402 mmol l(-1) of sodium lactate or 60 mmol l(-1) of potassium sorbate was required to observe a slower growth.

CONCLUSIONS

The inhibitory effect of acid salts was a function of pH, a(w), as well as of the nature and concentration of acid salts added. When one acid salt was added, the Augustin's model (Augustin et al. 2005) yielded generally correct predictions of either the survival or growth of L. monocytogenes.

SIGNIFICANCE AND IMPACT OF THE STUDY

The suggested model can be used for risk assessment concerning L. monocytogenes in pork products.

An investigation of the Gamma hypothesis: A predictive modelling study of the effect of combined inhibitors (salt, pH and weak acids) on the growth of Aeromonas hydrophila

The Gamma hypothesis, that multiple inhibitory factors combine independently, is the underlying hypothesis for the quantification of the Hurdle concept used in food manufacture. The literature, however, is confused as to whether interactive effects exist and under which circumstances they occur, if at all. Using the method of time to detection (TTD), the inhibitory effect of pH, salt and specific weak acids (acetic, propionic, sorbic and benzoic) and combinations of these with respect to the growth of Aeromonas hydrophila (ATCC 7966) were analysed. A model based on the relative rate to detection described all combinations analysed as having independent effects on the TTD. No synergistic interactions were found between pH and salt, between pH and individual weak acids or between combinations of weak acids and pH for any of the systems under study. This study supports the validity of the Gamma concept -- that individual environmental effects act independently and should, in turn, facilitate attempts to model the growth of other microorganisms under a variety of conditions.