Modelling the influence of single acid and mixture on bacterial growth

Relationships between the inhibitory efficacy and physicochemical properties of six organic acids and monolaurin against Bacillus weihenstephanensis KBAB4 growth in liquid medium

Organic acids are widely used in foodstuffs to inhibit pathogen and spoiler growth. In this study, six organic acids (acetic, lactic, propionic, phenyllactic, caprylic, and lauric acid) and monolaurin were selected based on their physicochemical properties: their molecular structure (carbon chain length), their lipophilicity (logP), and their ability to dissociate in a liquid environment (pKa). The relation between these physicochemical properties and the inhibitory efficacy against B. weihenstephanensis KBAB4 growth was evaluated. After assessing the active form of these compounds against the strain (undissociated, dissociated or both forms), their MIC values were estimated in nutrient broth at pH 6.0 and 5.5 using two models (Lambert & Pearson, 2000; Luong, 1985). The use of two models highlighted the mode of action of an antibacterial compound in its environment, thanks to the additional estimation of the curve shape α or the Non-Inhibitory Concentration (NIC). The undissociated form of the tested acids is responsible for growth inhibition, except for lauric acid and monolaurin. Moreover, long-carbon chain acids have lower estimated MICs, compared to short-chain acids. Thus, the inhibitory efficacy of organic acids is strongly related to their carbon chain length and lipophilicity. Lipophilicity is the main mechanism of action of a membrane-active compound, it can be favored by long chain structure or high pKa in an acid environment like food.

Microbiological and physicochemical profile of Italian steak tartare and predicting growth potential of Listeria monocytogenes

In the present study, growth potential of Listeria monocytogenes in steak tartare samples taken at retail and belonging to 13 brands marketed in Northern Italy was investigated. The samples were submitted to microbiological and chemical-physical characterization. The data obtained were used as inputs for the application of the predictive microbiology software FSSP that allows the estimation of the growth of L. monocytogenes during the shelf-life. Lactic acid bacteria, the main component of the microflora, gave variable counts among the brands (from 3.38 to 6.24 log CFU/g). pH and aw values were always higher than 5.3 and 0.96, respectively, thus they could not be considered as single efficient hurdles to prevent the growth of L. monocytogenes according to the EC Reg. 2073/2005; the same was observed for salt content (constantly <2 %) and nitrites (not quantifiable in all the samples, even if declared in some labels). Nevertheless, the combination of all the hurdles, evaluated by predictive microbiology using critical development factors, resulted in an estimated growth <0.5 log CFU/g throughout the shelf life; this output allowed us to consider all the steak tartare analysed as unfavourable substrate for L. monocytogenes growth. The information obtained could be useful for tartare producers as well as for competent authority to evaluate the effective risk concerning these typology of products.

Enhancement of Electricity Production in Microbial Fuel Cells Using a Biosurfactant-Producing Co-Culture

Microbial fuel cells are bio-electrochemical devices that enable the conversion of chemical energy into bioelectricity. In this manuscript, the use of biosurfactants (Tween 80 and surfactin) and the effect of coculturing E. coli and L. plantarum were used to investigate the generation of bioelectricity coming from an H-type microbial fuel cell. In this setup, E. coli acts as an electron donor while L. plantarum acts as an in situ biosurfactant producer. It was observed that the use of exogenous surfactants enhanced electricity production compared to conventional E. coli cultures. The utilization of Tween 80 and surfactin increased the power generation from 204 µW m-2 to 506 µW m-2 and 577 µW m-2, respectively. Furthermore, co-culturing E. coli and L. plantarum also resulted in a higher power output compared to pure cultures (132.8% more when compared to using E. coli alone and 68.1% more when compared to using L. plantarum alone). Due to the presence of surfactants, the internal resistance of the cell was reduced. The experimental evidence collected here clearly indicates that the production of endogenous surfactants, as well as the addition of exogenous surfactants, will enhance MFC electricity production.

Effects of carbon dioxide and oxygen on the growth rate of various food spoilage bacteria

The growth of six bacterial species (Carnobacterium maltaromaticum, Bacillus weihenstephanensis, Bacillus cereus, Paenibacillus spp., Leuconostoc mesenteroides and Pseudomonas fragi) was studied in various gas compositions. Growth curves were obtained at various oxygen concentrations (between 0.1 and 21%), or various carbon dioxide concentrations (between 0 and 100%). Decreasing the O₂ concentration from 21% to about 3-5% has no effect on the bacterial growth rates, which are only affected by low oxygen levels. For each strain studied, the growth rate decreased linearly with carbon dioxide concentration, except for L. mesenteroides which remained insensible to this gas. Conversely, the most sensitive strain was totally inhibited by 50% of carbon dioxide in the gas phase at 8 °C. Predictive models were fitted, and the parameters characterizing the inhibitory effect of these two gases were estimated. This study provides new tools to help the food industry design suitable packaging for MAP storage.

Modeling of Growth and Organic Acid Kinetics and Evolution of the Protein Profile and Amino Acid Content during Lactiplantibacillus plantarum ITM21B Fermentation in Liquid Sourdough

The application of mathematical modeling to study and characterize lactic acid bacterial strains with pro-technological and functional features has gained attention in recent years to solve the problems relevant to the variabilities of the fermentation processes of sourdough. Since the key factors contributing to the sourdough quality are relevant to the starter strain growth and its metabolic activity, in this study, the cardinal growth parameters for pH, temperature (T), water activity (a_w), and undissociated lactic acid of the sourdough strain Lactiplantibacillus plantarum ITM21B, were determined. The strain growth, pH, organic acids (lactic, acetic, phenyllactic, and hydroxy-phenyllactic), total free amino acids, and proteins were monitored during fermentation of a liquid sourdough based on wheat flour and gluten (Bio21B) after changing the starting T, pH, and inoculum load. Results demonstrated that the different fermentation conditions affected the strain growth and metabolite pattern. The organic acid production and growth performance were modeled in Bio21B, and the resulting predictive model allowed us to simulate in silico the strain performances in liquid sourdough under different scenarios. This mathematical predictive approach can be useful to optimize the fermentation conditions needed to obtain the suitable nutritional and technological characteristics of the L. plantarum ITM21B liquid sourdough.

Inhibitory Activity of Natural Synergetic Antimicrobial Consortia Against Salmonella enterica on Broiler Chicken Carcasses

The currently most utilized antimicrobial agent in poultry processing facilities is peracetic acid, a chemical increasingly recognized as hazardous to human health. We evaluated the efficacy of mixtures of natural antimicrobial compounds, namely reuterin, microcin J25, and lactic acid, for reducing the viability of Salmonella enterica and total aerobes on broiler chicken carcasses. The compounds were compared singly and in combination with water and 0.1% peracetic acid. The minimum inhibitory concentrations of reuterin, lactic acid, and microcin J25 against S. enterica serovar Enteritidis were respectively 2 mM, 0.31%, and 0.03 μM. In vitro, the combinations of reuterin + lactic acid and reuterin + microcin J25 were synergic, making these compounds effective at four times lower concentrations than those used alone. Salmonella viable counts fell to zero within 10 min of contact with reuterin + lactic acid at 10 times the concentrations used in combination, compared to 18 h in the case of reuterin + microcin J25. Sprayed onto chilled chicken carcasses, this reuterin + lactic acid mixture reduced Salmonella spp. counts by 2.02 Log CFU/g, whereas reuterin + microcin J25 and peracetic acid reduced them by respectively 0.83 and 1.13 Log CFU/g. The synergy of reuterin with lactic acid or microcin J25 as inhibitors of bacterial growth was significant. Applied as post-chill spray, these mixtures could contribute to food safety by decreasing Salmonella counts on chicken carcasses.

Cardinal parameter growth and growth boundary model for non-proteolytic Clostridium botulinum - Effect of eight environmental factors

A new cardinal parameter growth and growth boundary model for non-proteolytic C. botulinum was developed and validated for fresh and lightly preserved seafood and poultry products. 523 growth rates in broth were used to determine cardinal parameter values and terms for temperature, pH, NaCl/water activity, acetic, benzoic, citric, lactic and sorbic acids. The new growth and growth boundary model included the inhibiting interactive effect between these factors and it was calibrated using growth curves from 10 challenge tests with unprocessed seafood. For model evaluation, 40 challenge tests with well characterized fresh and lightly preserved seafood were performed. Comparison of these observed growth curves and growth rates (μ_max-values) predicted by the new model resulted in a bias factor (B_f) of 1.12 and an accuracy factor (A_f) of 1.40. Furthermore, the new model was evaluated with 94 growth rates and 432 time to toxin formation data extracted from the scientific literature for seafood, poultry, meat, pasta and prepared meals. These data included responses for 36 different toxigenic strains of non-proteolytic C. botulinum. The obtained B_f-/A_f-values were 0.97/2.04 for μ_max-values and 0.96/1.80 for time to toxin formation. The model correctly predicted 93.8% of the growth responses with 5.6% being fail-safe and <1% fail-dangerous. A cocktail of four non-toxin producing Clostridium spp. isolates was used to develop the new model and these isolates had more than 99.8% 16S rRNA gene similarity to non-proteolytic C. botulinum (Group II). The high number of environmental factors included in the new model makes it a flexible tool to facilitate development or reformulation of seafood and poultry products that do not support the growth of non-proteolytic C. botulinum. Further, evaluation of the new model with well characterized products is desirable particularly for meat, vegetables, pasta and prepared meals as well as for dairy products that was not included in the present study.

Development of a model for the alcoholic fermentation of cocoa beans by a Saccharomyces cerevisiae strain

The aromatic quality of chocolate requires the use of cocoa with high aromatic potential, this being acquired during the fermentation of cocoa beans. Traditional fermentation is still often carried out on a small scale with wild strains of yeasts and acetic bacteria and under poorly controlled conditions leading to cocoa quality ranging from best to worst. This study is the first part of a project aiming to control quality of cocoa to produce high aromatic quality chocolate by using a mixed starter of selected strains of yeast and acetic bacteria and by controlling the conditions of fermentation. To achieve this objective, a mathematical model of the alcoholic fermentation of cocoa beans has been developed. The growth, glucose consumption and ethanol production of Saccharomyces cerevisiae LM strain in synthetic broth were modeled for the most important intrinsic (pH, glucose, ethanol, free nitrogen and oxygen levels) and extrinsic (temperature, oxygen level) fermentation parameters. The model was developed by combining the effects of individual conditions in a multiplicative way using the gamma concept. The model was validated in liquid synthetic medium at two different inoculation levels 10⁴ and 10⁶ CFU/mL with an increase in temperature that recorded during spontaneous fermentations. The model clearly shows that the level of inoculation and the speed of the increase in temperature clearly drive yeast growth, while other factors including pH and ethanol, free nitrogen and oxygen levels have no significant impact on yeast growth.

Growth and growth boundary model with terms for melting salts to predict growth responses of Listeria monocytogenes in spreadable processed cheese

The aim of this study was to develop and validate a growth and growth boundary model with terms for melting salts to predict growth of Listeria monocytogenes in spreadable processed cheese. Cardinal parameter terms for phosphate salts and citric acid were developed in broth studies and used to expand an available growth and growth boundary model. The expanded model includes the effect of nine environmental factors (temperature, pH, a_w, lactic acid, acetic acid, citric acid, orthophosphate, di-phosphate and tri-phosphate). To generate growth data for model evaluation challenge tests with inoculated commercial (n = 10) and customized (n = 10) spreadable processed cheeses were performed. Evaluation of the new model by comparison of observed and predicted μ_max-values resulted in a bias factor of 1.12 and an accuracy factor of 1.33 (n = 42). Prediction of growth and no-growth responses in processed cheese (n = 60) were 89% correct with 11% fail-safe and 0% fail-dangerous predictions. The developed model can be used to support product development, reformulation or risk assessment for spreadable processed cheese.

Growth prediction of two bacterial populations in co-culture with lactic acid bacteria

The co-culture growth of Staphylococcus aureus, Escherichia coli and lactic acid bacteria starter culture in milk was quantitatively evaluated and modelled with a set of coupled differential equations originally proposed by Baranyi and Roberts and by Gimenez and Dalgaard (BR–GD model). The lactic acid bacteria starter culture showed the ability to induce an early stationary phase of both E. coli and S. aureus populations at different combination of temperature (ranging from 12 to 37 ℃) and lactic acid bacteria inocula (from approx. 103 to 106 CFU/ml). First, the prediction ability was performed only with parameters estimated from individual growth curves of E. coli, S. aureus and the lactic acid bacteria in milk (Dataset 1, 21 experiments). Subsequently, the model was extended with the average competition coefficients (E-BR–GD model) that represented quantitative relations among the populations. The prediction ability of this model was validated with the second dataset consisting of seven experiments. Results and also their statistical indices (accuracy and bias factors) showed that the E-BR–GD model improved growth prediction of all involved populations. Thus, the total root mean square error decreased from 0.457, 0.840 and 0.322 log CFU/ml (BR–GD model) to 0.290, 0.245 and 0.333 log CFU/ml (E-BR–GD) for S. aureus, E. coli and lactic acid bacteria, respectively. This approach in growth prediction of multiple competing microbial populations can be used in assessment of S. aureus and E. coli exposure from raw milk cheeses consumption and contribute to decision making in prevention of staphylococcal enterotoxin production.

A low-complexity metabolic network model for the respiratory and fermentative metabolism of Escherichia coli

Over the last decades, predictive microbiology has made significant advances in the mathematical description of microbial spoiler and pathogen dynamics in or on food products. Recently, the focus of predictive microbiology has shifted from a (semi-)empirical population-level approach towards mechanistic models including information about the intracellular metabolism in order to increase model accuracy and genericness. However, incorporation of this subpopulation-level information increases model complexity and, consequently, the required run time to simulate microbial cell and population dynamics. In this paper, results of metabolic flux balance analyses (FBA) with a genome-scale model are used to calibrate a low-complexity linear model describing the microbial growth and metabolite secretion rates of Escherichia coli as a function of the nutrient and oxygen uptake rate. Hence, the required information about the cellular metabolism (i.e., biomass growth and secretion of cell products) is selected and included in the linear model without incorporating the complete intracellular reaction network. However, the applied FBAs are only representative for microbial dynamics under specific extracellular conditions, viz., a neutral medium without weak acids at a temperature of 37℃. Deviations from these reference conditions lead to metabolic shifts and adjustments of the cellular nutrient uptake or maintenance requirements. This metabolic dependency on extracellular conditions has been taken into account in our low-complex metabolic model. In this way, a novel approach is developed to take the synergistic effects of temperature, pH, and undissociated acids on the cell metabolism into account. Consequently, the developed model is deployable as a tool to describe, predict and control E. coli dynamics in and on food products under various combinations of environmental conditions. To emphasize this point,three specific scenarios are elaborated: (i) aerobic respiration without production of weak acid extracellular metabolites, (ii) anaerobic fermentation with secretion of mixed acid fermentation products into the food environment, and (iii) respiro-fermentative metabolic regimes in between the behaviors at aerobic and anaerobic conditions.

Detection of Antilisterial Activity of 3-Phenyllactic Acid Using Listeria innocua as a Model

The 3-Phenyllactic acid (PLA) produced by various lactic acid bacteria (LAB) possesses a broad spectrum of antimicrobial activity. In this study, the effect of PLA against Listeria innocua was studied with the aim to obtain additional information about its mechanism of action. The effect of pH on the antilisterial activity of PLA was investigated and a pH-dependent behavior, typical of weak acid, was detected. The antilisterial effect of PLA was firstly compared to that produced by lactic acid (LA) and than to that expressed by phenolic acids (gallic, caffeic, and ferulic acids) evaluating minimum inhibitory concentration (MIC), MBC, and survival kinetic parameters. PLA showed MIC values and death kinetic parameters significantly different from those exhibited by LA and by tested phenolic acids. In particular, the MIC value observed for PLA vs L. innocua resulted lower than that of the other preservative compounds studied herein, and consistent with the quantity generally produced by LAB. Moreover, the effect of PLA and phenolic acids on bacterial surface charge and loss of cellular content resulted different. The overall results highlighted strong differences in the antilisterial mechanism of action among PLA and other compounds such as LA and phenols. Specifically, it is possible to hypothesize that the antilisterial mechanism of action due to PLA is associated with the affinity to cell surface, which contributes to the cellular damage.

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.

Modeling carbon dioxide effect in a controlled atmosphere and its interactions with temperature and pH on the growth of L. monocytogenes and P. fluorescens

The effect of carbon dioxide, temperature, and pH on growth of Listeria monocytogenes and Pseudomonas fluorescens was studied, following a protocol to monitor microbial growth under a constant gas composition. In this way, the CO₂ dissolution didn't modify the partial pressures in the gas phase. Growth curves were acquired at different temperatures (8, 12, 22 and 37 °C), pH (5.5 and 7) and CO₂ concentration in the gas phase (0, 20, 40, 60, 80, 100% of the atmospheric pressure, and over 1 bar). These three factors greatly influenced the growth rate of L. monocytogenes and P. fluorescens, and significant interactions have been observed between the carbon dioxide and the temperature effects. Results showed no significant effect of the CO₂ concentration at 37 °C, which may be attributed to low CO2 solubility at high temperature. An inhibitory effect of CO₂ appeared at lower temperatures (8 and 12 °C). Regardless of the temperature, the gaseous CO₂ is sparingly soluble at acid pH. However, the CO₂ inhibition was not significantly different between pH 5.5 and pH 7. Considering the pKa of the carbonic acid, these results showed the dissolved carbon under HCO₃^- form didn't affect the bacterial inhibition. Finally, a global model was proposed to estimate the growth rate vs. CO₂ concentration in the aqueous phase. This dissolved concentration is calculated according to the physical equations related to the CO₂ equilibriums, involving temperature and pH interactions. This developed model is a new tool available to manage the food safety of MAP.

Modeling Lactic Fermentation of Gowé Using Lactobacillus Starter Culture

A global model of the lactic fermentation step of gowé was developed by assembling blocks hosting models for bacterial growth, lactic acid production, and the drop of pH during fermentation. Commercial strains of Lactobacillus brevis and of Lactobacillus plantarum were used; their growth was modeled using Rosso's primary model and the gamma concept as a secondary model. The optimum values of pH and temperature were 8.3 ± 0.3, 44.6 ± 1.2 °C and 8.3 ± 0.3, 3.2 ± 37.1 °C with μmax values of 1.8 ± 0.2 and 1.4 ± 0.1 for L. brevis and L. plantarum respectively. The minimum inhibitory concentration of undissociated lactic acid was 23.7 mM and 35.6 mM for L. brevis and L. plantarum, respectively. The yield of lactic acid was five times higher for L. plantarum than for L. brevis, with a yield of glucose conversion to lactic acid close to 2.0 for the former and 0.8 for the latter. A model was developed to predict the pH drop during gowé fermentation. The global model was partially validated during manufacturing of gowé. The global model could be a tool to aid in the choice of suitable starters and to determine the conditions for the use of the starter.

Modelling and predicting the simultaneous growth of Escherichia coli and lactic acid bacteria in milk

Modelling and predicting the simultaneous competitive growth of Escherichia coli and starter culture of lactic acid bacteria (Fresco 1010, Chr. Hansen, Hørsholm, Denmark) was studied in milk at different temperatures and Fresco inoculum concentrations. The lactic acid bacteria (LAB) were able to induce an early stationary state in E. coli. The developed model described and tested the growth inhibition of E. coli (with initial inoculum concentration 103 CFU/mL) when LAB have reached maximum density in different conditions of temperature (ranging from 12 ℃ to 30 ℃) and for various inoculum sizes of LAB (ranging from approximately 103 to 107 CFU/mL). The prediction ability of the microbial competition model (the Baranyi and Roberts model coupled with the Gimenez and Dalgaard model) was first performed only with parameters estimated from individual growth of E. coli and the LAB and then with the introduced competition coefficients evaluated from co-culture growth of E. coli and LAB in milk. Both the results and their statistical indices showed that the model with incorporated average values of competition coefficients improved the prediction of E. coli behaviour in co-culture with LAB.

Modeling red cabbage seed extract effect on Penicillium corylophilum: Relationship between germination time, individual and population lag time

The inhibitory effect of a red cabbage seed extract on germination time, individual (single spore) and population lag time of Penicillium corylophilum was studied. First, to compare the biological variability of single spore germination and lag times under stressful conditions, data were collected at levels of red cabbage seed extract varying from 0 to 10 mg/g (150 spores observed in each trial of germination, ca 50 spores in each individual lag experiment). Experiments were performed on malt agar at 25 °C, pH 5.2, aw 0.99. The data, without any transformation, were statistically analyzed; several probability distribution functions were used to fit the cumulated germination times and the individual lag times of spores. In both cases, the best fit was obtained with the Normal distribution. In parallel, lag times at the population level (ca 2000 spores per trial) were collected for the same range of plant extract. Not surprisingly, the difference between individual and population lag times could be explained by a stochastic process. More interestingly, it was shown that under stressful conditions, the population lag time did not correspond to the time required for germination of 95% of spores, but to a much longer time. Finally, it was deduced from the statistical analysis, completed by microscopic observations, that the plant extract affected mainly the hyphal elongation (and then the lag time) and not the germination. Next, secondary models were developed to quantify the effect of red cabbage seed extract on the median of germination times, individual and population lag times. The Minimum Inhibitory Concentrations (MICs) were estimated. It was shown that the red cabbage seed extract MIC for P. corylophilum lag time did not depend on the inoculum load. Application of the secondary models allowed us to conclude that under the conditions of our experiment, the addition of 10 mg/g of red cabbage seed extract enabled extension of lag time to two weeks.

Quantifying Effect of Lactic, Acetic, and Propionic Acids on Growth of Molds Isolated from Spoiled Bakery Products

The combined effect of undissociated lactic acid (0 to 180 mmol/liter), acetic acid (0 to 60 mmol/liter), and propionic acid (0 to 12 mmol/liter) on growth of the molds Aspergillus niger, Penicillium corylophilum, and Eurotium repens was quantified at pH 3.8 and 25°C on malt extract agar acid medium. The impact of these acids on lag time for growth (λ) was quantified through a gamma model based on the MIC. The impact of these acids on radial growth rate (μ) was analyzed statistically through polynomial regression. Concerning λ, propionic acid exhibited a stronger inhibitory effect (MIC of 8 to 20 mmol/liter depending on the mold species) than did acetic acid (MIC of 23 to 72 mmol/liter). The lactic acid effect was null on E. repens and inhibitory on A. niger and P. corylophilum. These results were validated using independent sets of data for the three acids at pH 3.8 but for only acetic and propionic acids at pH 4.5. Concerning μ, the effect of acetic and propionic acids was slightly inhibitory for A. niger and P. corylophilum but was not significant for E. repens. In contrast, lactic acid promoted radial growth of all three molds. The gamma terms developed here for these acids will be incorporated in a predictive model for temperature, water activity, and acid. More generally, results for μ and λ will be used to identify and evaluate solutions for controlling bakery product spoilage.

Modelling the effect of lactic acid bacteria from starter- and aroma culture on growth of Listeria monocytogenes in cottage cheese

Four mathematical models were developed and validated for simultaneous growth of mesophilic lactic acid bacteria from added cultures and Listeria monocytogenes, during chilled storage of cottage cheese with fresh- or cultured cream dressing. The mathematical models include the effect of temperature, pH, NaCl, lactic- and sorbic acid and the interaction between these environmental factors. Growth models were developed by combining new and existing cardinal parameter values. Subsequently, the reference growth rate parameters (μref at 25°C) were fitted to a total of 52 growth rates from cottage cheese to improve model performance. The inhibiting effect of mesophilic lactic acid bacteria from added cultures on growth of L. monocytogenes was efficiently modelled using the Jameson approach. The new models appropriately predicted the maximum population density of L. monocytogenes in cottage cheese. The developed models were successfully validated by using 25 growth rates for L. monocytogenes, 17 growth rates for lactic acid bacteria and a total of 26 growth curves for simultaneous growth of L. monocytogenes and lactic acid bacteria in cottage cheese. These data were used in combination with bias- and accuracy factors and with the concept of acceptable simulation zone. Evaluation of predicted growth rates of L. monocytogenes in cottage cheese with fresh- or cultured cream dressing resulted in bias-factors (Bf) of 1.07-1.10 with corresponding accuracy factor (Af) values of 1.11 to 1.22. Lactic acid bacteria from added starter culture were on average predicted to grow 16% faster than observed (Bf of 1.16 and Af of 1.32) and growth of the diacetyl producing aroma culture was on average predicted 9% slower than observed (Bf of 0.91 and Af of 1.17). The acceptable simulation zone method showed the new models to successfully predict maximum population density of L. monocytogenes when growing together with lactic acid bacteria in cottage cheese. 11 of 13 simulations of L. monocytogenes growth were within the acceptable simulation zone, which demonstrated good performance of the empirical inter-bacterial interaction model. The new set of models can be used to predict simultaneous growth of mesophilic lactic acid bacteria and L. monocytogenes in cottage cheese during chilled storage at constant and dynamic temperatures. The applied methodology is likely to be applicable for safety prediction of other types of fermented and unripened dairy products where inhibition by lactic acid bacteria is important for growth of pathogenic microorganisms.

Use of marination for controlling Salmonella enterica and Listeria monocytogenes in raw beef

The effect of marination on the survival and growth of the pathogens Salmonella enterica and Listeria monocytogenes on beef pieces was investigated. Five marinades were used: soy sauce base marinade without (SB) or with lactic acid (SBLA), red wine base marinade without (WB) or with 0.5% v/v oregano essential oil (WBO), and sterile saline used as control (C). Inoculated fresh beef pieces were marinated for 18 h at 5 °C, removed from the marinade and subjected to storage trials at 5 °C and 15 °C. Heat inactivation studies were also performed on the isolates after exposure to the marinades to determine if marination affects heat resistance of the pathogens. The marinades with antimicrobials caused a significant decrease in viable count of the pathogens during marinations at 5 °C for 18 h of up to 2.1 and 3.4 log cfu cm(-2) for Salmonella and L. monocytogenes, respectively. Marinades without antimicrobials were less bactericidal resulting to reductions ranging from 0.3 to 0.4 and 1.3 to 2.0 log cfu cm(-2) for Salmonella and L. monocytogenes, respectively. Growth of L. monocytogenes was observed in the controls at both tested temperatures, while growth of Salmonella was observed in the controls stored at 15 °C. No growth of the pathogens was observed in any of the marinated samples at both temperature tested. No significant changes of heat resistance of the tested pathogens after exposure to the marinades were observed demonstrating the enhanced safety of the marinated beef product.

Managing the potential risks of using bacteria-laden water in mineral processing to protect freshwater

The minerals industry is being driven to access multiple water sources and increase water reuse to minimize freshwater withdrawal. Bacteria-laden water, such as treated effluent, has been increasingly used as an alternative to freshwater for mineral processing, in particular flotation, where conditions are favorable for bacterial growth. However, the risk posed by bacteria to flotation efficiency is poorly understood. This could be a barrier to the ongoing use of this water source. This study tested the potential of a previously published risk-based approach as a management tool to both assist mine sites in quantifying the risk from bacteria, and finding system-wide cost-effective solutions for risk mitigation. The result shows that the solution of adjusting the flotation chemical regime could only partly control the risk. The second solution of using tailings as an absorbent was shown to be effective in the laboratory in reducing bacterial concentration and thus removing the threat to flotation recovery. The best solution is likely to combine internal and external approaches, that is, inside and outside processing plants. Findings in this study contribute possible methods applicable to managing the risk from water-borne bacteria to plant operations that choose to use bacteria-containing water, when attempting to minimize freshwater use, and avoiding the undesirable consequences of increasing its use.

Modeling the growth of Listeria monocytogenes in soft blue-white cheese

The aim of this study was to develop a predictive model simulating growth over time of the pathogenic bacterium Listeria monocytogenes in a soft blue-white cheese. The physicochemical properties in a matrix such as cheese are essential controlling factors influencing the growth of L. monocytogenes. We developed a predictive tertiary model of the bacterial growth of L. monocytogenes as a function of temperature, pH, NaCl, and lactic acid. We measured the variations over time of the physicochemical properties in the cheese. Our predictive model was developed based on broth data produced in previous studies. New growth data sets were produced to independently calibrate and validate the developed model. A characteristic of this tertiary model is that it handles dynamic growth conditions described in time series of temperature, pH, NaCl, and lactic acid. Supplying the model with realistic production and retail conditions showed that the number of L. monocytogenes cells increases 3 to 3.5 log within the shelf life of the cheese.

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.

Modelling of growth, growth/no-growth interface and nonthermal inactivation areas of Listeria in foods

Growth, growth boundary and inactivation models have been extensively developed in predictive microbiology and are commonly applied in food research nowadays. Few studies though report the development of models which encompass all three areas together. A tiered modelling approach, based on the Gamma hypothesis, is proposed here to predict the behaviour of Listeria. Datasets of Listeria spp. behaviour in laboratory media, meat, dairy, seafood products and vegetables were collected from literature, unpublished sources and from the databases ComBase and Sym'Previus. The explanatory factors were temperature, pH, water activity, lactic and sorbic acids. For the growth part, 697 growth kinetic datasets were fitted. The estimated growth rates and 2021 additional growth primary datasets were used to fit the secondary growth models. In a second step, the fitted model was used to predict the growth/no-growth boundary. For the inactivation modelling phase, 535 inactivation curves were used. Gamma models with and without interactions between the explanatory factors were used for the growth and boundary models. The correct prediction percentage (predicted growth when growth is observed+predicted inactivation when inactivation is observed) varied from 62% to 81% for the models without interactions, and from 85% to 87% for the models with interactions. The median error for the predicted population size was less than 0.34 log(10)(CFU/mL) for all models. The kinetics of inactivation were fitted with modified Weibull primary models and the estimated bacterial resistance was then modelled as a function of the explanatory factors. The error for the predicted microbial population size was less than 0.71 log(10)(CFU/mL) with a median value of less than 0.21 for all foods. The model enables the quantification of the increase or decrease in the bacterial population for a given formulation or storage condition. It might also be used to optimise a food formulation or storage condition in the case of a targeted increase or decrease of the bacterial population.

Chemical Composition and Antimicrobial Activity of Essential Oils of Genista ulicina and G. vepres

The hydrodistilled oils from the aerial parts of Genista ulicina Spach. and G. vepres Pomel., which are endemic to Algeria, were analyzed by gas chromatography-mass spectrometry (GC-MS). In the oil of G. ulicina, 41 compounds were identified representing 90.8% of the total oil, and in G. vepres, 61 compounds representing 84.5% of the total oil. The analyses showed that the major constituents of the oils were lauric acid (14.3% – 8.5%), myristic acid (11.5% – 5%), linoleic acid (3.1% –11.7%) and palmitic acid (18.6% – 26.4%). Using a diffusion method, the oils showed significant antibacterial activities against Escherichia coli (ATCC 25922), Pseudomonas aeruginosa (ATCC 27853) and Staphylococcus aureus (ATCC 25923).

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.

Modeling the effect of marination and temperature on Salmonella inactivation during drying of beef jerky

This study modeled the effect of drying temperature in combination with predrying marination treatments to inactivate Salmonella on beef jerky. Beef inside round slices were inoculated with Salmonella and treated with (1) nothing (C), (2) traditional marinade (M), or (3) dipped into a 5% acetic acid solution for 10 min before exposure to M (AM). After 24 h of marination at 4 degrees C, samples were dehydrated at 52, 57, or 63 degrees C. Total counts (tryptic soy agar supplemented with 0.1% sodium pyruvate, TSAP) and Salmonella (XLD agar) were enumerated after inoculation and at 0, 2, 4, 6, 8, and 10 h during drying. For calculation of death rates (DR, log CFU/cm(2)/h), shoulder period (h), low asymptote, and upper asymptote, cell counts from TSAP were fitted to the Baranyi model. The DRs were then further expressed as a function of storage temperature. Inactivation occurred without an initial lag phase (shoulder period), while correlation (R(2)) values of fitted curves were >/= 0.861. The DRs of C (-0.29 to -0.62) and M (-0.36 to -0.63) treatments were similar, while DRs of the AM treatment were higher (-1.22 to -1.46). The DRs were then fitted to a polynomial equation as a function of temperature. After validation, good (C and M) or acceptable (AM) model performances were observed (R(2)= 0.954 to 0.987; bias factors: 1.03 [C], 1.01 [M], 0.71 [AM]; accuracy factors: 1.05 [C], 1.06 [M], 1.41 [AM]). The developed models may be useful in selecting drying temperatures and times in combination with predrying treatments for adequate inactivation of Salmonella in beef jerky.

Effect of capric, lauric and alpha-linolenic acids on the division time distributions of single cells of Staphylococcus aureus

The effect of non-inhibitory concentrations of capric, lauric and alpha-linolenic acids (C10:0, C12:0 and C18:3 respectively) on the division time distribution of single cells of Staphylococcus aureus was evaluated at pH 7 and pH 5. The effect of the initial cell concentration on the lag time of growing cell populations was also assessed. The statistical properties of the division times (defined as the time interval from birth to next binary fission for a single cell) were studied using the method of Elfwing et al. [Elfwing, A., Le Marc, Y., Baranyi, J., Ballagi, A., 2004. Observing the growth and division of large number of individual bacteria using image analysis. Applied and Environmental Microbiology 70, 675-678]. The division times were significantly longer in the presence of free fatty acids than in the control. Shorter division intervals were detected at pH 7 than at pH 5 in the control experiment and in the presence of C10:0. However, both C12:0 and C18:3 slowed down the growth, regardless of the pH. The observed division time distributions were used to simulate growth curves from different inoculum sizes using the stochastic birth process described by Pin and Baranyi [Pin, C., Baranyi, J., 2006. Kinetics of single cells: observation and modelling of a stochastic process. Applied and Environmental Microbiology 72, 2163-2169]. The output of the simulation results were compared with observed data. The lag times fitted to simulated growth curves were in good agreement with those fitted to growth curves measured by plate counts. The averaged out effect of the population masked the effect of the free fatty acids and pH on the division times of single cells.

Growth response of Salmonella typhimurium in the presence of natural and synthetic antimicrobials: estimation of MICs from three different models

The aim of this study was to determine the MICs of 14 antimicrobials for Salmonella Typhimurium with three methods and to check the influence of experiment duration on the estimation of MICs. The growth of Salmonella Typhimurium in a brain heart infusion medium containing various concentrations of natural aromatic compounds, organic acids, or salts was monitored by absorbance measurements for 24 or 72 h. Three different ways of analyzing optical density (OD) curves were tested for the determination of MICs. Both quantitative methods gave similar MICs for most of the compounds. The semiquantitative method does not allow estimating the MIC for all compounds. Noticeable differences were found between MICs obtained for 24- or 72-h experiments, whatever the method used. The proposed methods and models can be used for the estimation of MICs from OD data. MICs could be used for a quantitative approach to Salmonella Typhimurium growth.

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.