Exploring the performance of logistic regression model types on growth/no growth data of Listeria monocytogenes

Modelling the low temperature growth boundaries of Salmonella Enteritidis in raw and pasteurized egg yolk, egg white and liquid whole egg: Influence of the initial concentration

Salmonella is the most frequently reported cause of foodborne outbreaks with known origin in Europe, with eggs and egg products standing out as the most frequent food source (when it was known). The growth and survival of Salmonella in eggs and egg products have been extensively studied and, recently, it has been reported that factors such as the initial concentration and thermal history of the egg product can also influence its growth capability. Therefore, the objective of this study was to define the boundary zones of the growth/no growth domain of Salmonella Enteritidis (4 strains) as a function of temperature (low temperature boundary) and the initial concentration in different egg products. A series of polynomial logistic regression equations were successfully adjusted, allowing the study of these factors and their interaction on the probability of growth of S. Enteritidis in these products. Results obtained indicate that the minimum growth temperatures of Salmonella Enteritidis are higher in egg white (9.5-18.3 °C) than in egg yolk (7.1-7.8 °C) or liquid whole egg (7.2-7.9 °C). Results also demonstrate that in raw liquid whole egg and raw and pasteurized egg white, the minimum growth temperature of Salmonella Enteritidis does depend on the initial concentration. Similarly, the previous thermal history of the egg product only influenced the minimum growth temperature in some of them. On the other hand, large differences in the minimum growth temperatures among strains were observed in some products (up to approx. 6 °C in egg white). Finally, it should be noted that none of the strains grew at 5 °C under any of the conditions assayed. Therefore, storage of egg products (particularly whole liquid egg and egg yolk) below this temperature might be regarded/proposed as a good management approach. Our experimental approach has allowed us to provide a more accurate prediction of S. Enteritidis minimum growth temperatures in egg products by taking into account additional factors (initial concentration and thermal history) while also providing a quantification of the intra-specie variability. This would be of high relevance for improving the safety of egg products.

Construction of a dynamic model to predict the growth of Staphylococcus aureus and the formation of enterotoxins during Kazak cheese maturation

Staphylococcus aureus is a common pathogen found in cheese whose Staphylococcal enterotoxins (SE) are the main pathogenic factors that cause food poisoning. The objective of this study was to construct two models to evaluate the safety of Kazak cheese products in terms of composition, changes in S. aureus inoculation amount, Aw, fermentation temperature during processing, and growth of S. aureus in the fermentation stage. A total of 66 experiments comprised of five levels of inoculation amount (2.7-4 log CFU/g), five levels of Aw (0.878-0.961), and six levels of fermentation temperature (32-44 °C) were performed to confirm the growth of S. aureus and the presence of SE limit conditions. Two artificial neural networks (ANN) successfully described the relationship between the assayed conditions and the growth kinetic parameters (maximum growth rates and lag times) of the strain. The good fitting accuracy (R² values were 0.918 and 0.976, respectively) showed that the ANN was appropriate. Experimental results showed fermentation temperature had the greatest influence on the maximum growth rate and lag time, followed by the Aw and inoculation amount. Furthermore, a probability model was built to predict the production of SE by logistic regression and neural network under the assayed conditions, which proved to be concordant in 80.8-83.8% of the cases with the observed probabilities. The maximum total number of colonies predicted by the growth model in all combinations detected with SE exceeded 5 log CFU/g. Within the range of variables, the minimum Aw for predicting SE production was 0.938, and the minimum inoculation amount for predicting SE production was 3.22 log CFU/g. Additionally, as competition between S. aureus and lactic acid bacteria (LAB) occurs in the fermentation stage, higher fermentation temperatures are conducive to the growth of LAB, which can reduce the risk of S. aureus producing SE. This study can help manufacturers to make decisions on the most appropriate production parameters for Kazak cheese products and to prevent S. aureus growth and SE production.

Modelling the Adhesion and Biofilm Formation Boundary of Listeria monocytogenes ST9

Listeria monocytogenes is a major foodborne pathogen that can adhere to or form a biofilm on food contact surfaces, depending on the environmental conditions. The purpose of this work is to determine the adhesion and biofilm formation boundaries for L. monocytogenes ST9 under the combination environments of temperature (5, 15, and 25 °C), NaCl concentration (0%, 3%, 6%, and 9% (w/v)) and pH (5.0, 6.0, 7.0, and 8.0). The probability models of adhesion and biofilm formation were built using the logistic regression. For adhesion, only the terms of linear T and NaCl are significant for L. monocytogenes ST9 (p < 0.05), whereas the terms of linear T, NaCl, and pH, and the interaction between T and pH were significant for biofilm formation (p < 0.05). By analyzing contour maps and their surface plots for two different states, we discovered that high temperature promoted adhesion and biofilm formation, whereas excessive NaCl concentration inhibited both of them. With a stringent threshold of 0.1667, the accuracy rate for identifying both adhesion/no-adhesion and biofilm formation/no-biofilm formation events were 0.929, indicating that the probability models are reasonably accurate in predicting the adhesion and biofilm formation boundary of L. monocytogenes ST9. The boundary model may provide a useful way for determining and further controlling L. monocytogenes adhesion and biofilm formation in various food processing environments.

Modeling the combined effect of temperature, pH, acetic and lactic acid concentrations on the growth/no growth interface of acid-tolerant Bacillus spores

The application of minimal processing technologies has led to increased spoilage incidents in low-acid pasteurized sauces due to the outgrowth of acid-tolerant spore-forming spoilage bacteria (ATSSB). Controlling the germination and subsequent growth of ATSSB spores is vital to enhance the ambient storage stability of pasteurized sauces. This study developed and validated a set of growth/no growth (G/NG) models for spores of two ATSSB strains (Bacillus velezensis and Bacillus subtilis subsp. subtilis) isolated from pasteurized sauces. The G/NG data at two levels of temperature (22 and 30 °C) were collected in Nutrient Broth (a_w = 0.98 adjusted with NaCl) by a full factorial design with five equidistant levels of pH (4.4-5.6), four concentrations of total acetic acid (0.0-0.3% (w/w)), and four concentrations of total lactic acid (0.00-1.00% (w/w)). The growth, starting from heat-treated (10 min 80 °C) spores, of each strain was assessed under 160 combinations by regular optical density measurements during three months. Twelve replicates were made for each combination. The developed models demonstrate that without organic acids even the lowest pH (4.4) allows a high growth possibility of the ATSSB spores, while acetic and lactic acids exhibit a significant antibacterial activity, which can be enhanced at decreased pH. The growth starting from B. subtilis spores can be inhibited for at least three months with 1.0% (w/w) total lactic acid in the water phase at both temperatures, which was not the case for B. velezensis, while 0.3% acetic acid achieves a full inhibition on both strains at 22 °C. With a combination of 0.3% acetic acid and 0.7% lactic acid, no growth should occur in the investigated range. This research is one of the first studies exploring the feasibility of ambient storage for low-acid pasteurized sauces eliminating preservatives such as benzoic and sorbic acids, and proves the synergistic effect of decreased pH and the presence of acetic and lactic acids on inhibiting bacterial growth from ATSSB spores.

A Binary Logistic Regression Model as a Tool to Predict Craft Beer Susceptibility to Microbial Spoilage

Beer spoilage caused by microorganisms, which is a major concern for brewers, produces undesirable aromas and flavors in the final product and substantial financial losses. To address this problem, brewers need easy-to-apply tools that inform them of beer susceptibility to the microbial spoilage. In this study, a growth/no growth (G/NG) binary logistic regression model to predict this susceptibility was developed. Values of beer physicochemical parameters such as pH, alcohol content (% ABV), bitterness units (IBU), and yeast-fermentable extract (% YFE) obtained from the analysis of twenty commercially available craft beers were used to prepare 22 adjusted beers at different levels of each parameter studied. These preparations were assigned as a first group of samples, while 17 commercially available beers samples as a second group. The results of G/NG from both groups, after artificially inoculating with one wild yeast and different lactic acid bacteria (LAB) previously adapted to grow in a beer-type beverage, were used to design the model. The developed G/NG model correctly classified 276 of 331 analyzed cases and its predictive ability was 100% in external validation. This G/NG model has good sensitivity and goodness of fit (87% and 83.4%, respectively) and provides the potential to predict craft beer susceptibility to microbial spoilage.

Modelling viability of Listeria monocytogenes in paneer

Paneer is a fresh, soft ready-to-eat cheese that is susceptible to Listeria monocytogenes contamination, exemplified by product recalls in Australia, Canada, and the USA. Previous research demonstrates that L. monocytogenes grows in paneer, however there are no paneer-specific predictive models that quantify the effect of environmental conditions on L. monocytogenes viability. This study measured the viability of a five-strain cocktail of L. monocytogenes in freshly prepared paneer incubated at 4-40 °C. Growth rates were fitted with the extended Ratkowsky square root model, with growth rates ranging from 0.014 to 0.352 log₁₀ CFU/h. In comparison with published models, only the ComBase L. monocytogenes broth model acceptably predicted growth (B_f = 1.01, A_f = 1.12) versus the developed model. The influence of paneer pH (5.0-6.0) and storage temperature (41-45 °C) on L. monocytogenes growth at the upper temperature growth boundary was described using a logistic model. These models provide quantitative tools to improve the safety of paneer processing conditions, shelf-life estimation, food safety management plans, and risk assessment.

Combined effect of water activity and pH on the growth of food-related ascospore-forming molds

Purpose

The contamination of raw materials, packaging, or processing environments by fungal ascospores is a real concern for food industries, where variable rates of spoilage can be reached in pasteurized acidic products such as fruit juices, fruit jams, or soft drinks. The aim of this work was to assess the combined effect of aw and pH on the growth of six isolates from three genera of ascospore-forming molds that may occur in raw materials and in food industrial environments, in order to determine the environmental conditions that prevent the spoilage of pasteurized foods and beverages.

Methods

Growth tests were carried out on 60-day-old ascospores from Aspergillus hiratsukae (≡Neosartorya hiratsukae), Aspergillus thermomutatus (≡Neosartorya pseudofischeri), Chaetomium flavoviride, Chaetomium globosum, Talaromyces bacillisporus, and Talaromyces trachyspermus. The tests were performed up to 90 days at 25 °C, using sucrose solutions at different aw (0.85, 0.88, 0.92, 0.95) and pH (3.20, 3.50, 3.80, 4.20, 4.60) values. Growth was characterized by fitting an ordinary logistic regression model to the collected growth data.

Results

The explained percentage of the growth/no growth models ranged between 81.0 and 99.3%: aw exerted the largest influence on the growth of all tested species, while pH was significant only for Chaetomium isolates. The minimum conditions for germination and growth were aw 0.92 and pH 3.50 or 3.80, respectively, for C. flavoviride (46 days) and C. globosum (39 days), aw 0.92 and pH 3.20 for T. trachyspermus (13 days), aw 0.88 and pH 3.20 for T. bacillisporus (39 days), and aw 0.88 and pH 3.20 for the two aspergilli (33 and 27 days, respectively, for A. hiratsukae and A. thermomutatus).

Conclusions

Most of the spoiling mycetes tested were well-adapted to the formulations considered; therefore, foods strategies aiming to inhibit their growth should explore also the hurdle effect exerted by other factors (e.g., antioxidants, organic acids, oxygen levels).

High hydrostatic pressure inactivation of microorganisms: A probabilistic model for target log-reductions

A probabilistic model based on logistic regression was developed for a target log reduction of microorganisms inactivated by high hydrostatic pressure. Published inactivation data of Salmonella Typhimurium in broth for 4 and 5 log reductions, and Escherichia coli in buffer and carrot juice for 5 log reduction were used. The probabilities of achieving 4 or 5 log reductions for S. Typhimurium in broth and 5 log reduction for E. coli in buffer and carrot juice could be calculated at different pressure, temperature and time levels. The fitted interfaces of achieving/not achieving the target log reduction were consistent with the experimental data. Although the reliability of the predictions of the developed models could be questioned due to strain variation and different food matrix, a validation study has demonstrated that the developed models could be used to predict the target log reduction of these microorganisms at different pressure, temperature and time levels. This study has indicated that the probabilistic modeling for target log reductions can be useful tool for HHP inactivation of microorganisms, but further studies could be performed with several other factors such as pH and water activity of the food, concentration of certain additives as well as initial number of bacteria present in the food.

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.

Inoculation density is affecting growth conditions of Listeria monocytogenes on fresh cut lettuce

Listeria monocytogenes is a particular risk for the ready-to-eat food sector because of its ability to grow in various environmental conditions. In the literature, growth and survival of L. monocytogenes on food is tested using inoculation densities ranging from less than 102 to over 105 CFU g-1. Inoculation densities on food have been rarely tested as a factor for growth. In this study, inoculation densities from 102 to 105 of L. monocytogenes were tested on iceberg lettuce (Lactuca sativa) in modified atmospheres and air in model packages at 4 and 8 °C to identify any potential inoculation density effects. On days 0, 2, 5 and 7, L. monocytogenes was extracted from the lettuce surface and enumerated via selective media. The resulting growth curves identified a significant inoculation density effect at 4 and 8 °C with significantly higher amounts of growth (1-2 logs) when lettuce was inoculated at 102 CFU g-1 as opposed to 104 and 105 CFU g-1. In contrast, the use of different atmospheres had limited influence on growth of L. monocytogenes. In conclusion, greater emphasis on inoculation density of L. monocytogenes should be taken in inoculation experiments when confirmation of growth or the efficacies of growth inhibiting treatments are tested on ready-to-eat food such as lettuce.

Growth/no growth models for Zygosaccharomyces rouxii associated with acidic, sweet intermediate moisture food products

The most notorious spoilage organism of sweet intermediate moisture foods (IMFs) is Zygosaccharomyces rouxii, which can grow at low water activity, low pH and in the presence of organic acids. Together with an increased consumer demand for preservative free and healthier food products with less sugar and fat and a traditionally long self-life of sweet IMFs, the presence of Z. rouxii in the raw materials for IMFs has made assessment of the microbiological stability a significant hurdle in product development. Therefore, knowledge on growth/no growth boundaries of Z. rouxii in sweet IMFs is important to ensure microbiological stability and aid product development. Several models have been developed for fat based, sweet IMFs. However, fruit/sugar based IMFs, such as fruit based chocolate fillings and jams, have lower pH and aw than what is accounted for in previously developed models. In the present study growth/no growth models for acidified sweet IMFs were developed with the variables aw (0.65-0.80), pH (2.5-4.0), ethanol (0-14.5% (w/w) in water phase) and time (0-90 days). Two different strains of Z. rouxii previously found to show pronounced resistance to the investigated variables were included in model development, to account for strain differences. For both strains data sets with and without the presence of sorbic acid (250 ppm on product basis) were built. Incorporation of time as an exploratory variable in the models gave the possibility to predict the growth/no growth boundaries at each time between 0 and 90 days without decreasing the predictive power of the models. The influence of ethanol and aw on the growth/no growth boundary of Z. rouxii was most pronounced in the first 30 days and 60 days of incubation, respectively. The effect of pH was almost negligible in the range of 2.5-4.0. The presence of low levels of sorbic acid (250 ppm) eliminated growth of both strains at all conditions tested. The two strains tested have previously been shown to have similar tolerance towards the single stress factors included in the study, but when the stress factors were combined the two strains showed difference in their ability to grow illustrating the importance of including more strains when developing growth/no growth models. The developed models can be useful tools for development of new acidic sweet IMFs.

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.

Effect of Satureja thymbra essential oil on growth-no growth interfaces of Listeria monocytogenes Scott A and Salmonella Enteritidis PT4, at various temperatures, pH, and water activities

Antimicrobial efficacy of Satureja thymbra essential oil against Listeria monocytogenes Scott A and Salmonella ser. Enteritidis PT4 was evaluated in vitro by modeling the growth boundaries at various temperatures, pH, and NaCl concentrations. Growth-no growth (turbidity) data were modeled by logistic polynomial regression. The concordance indices and the Hosmer- Lemeshow statistics of both logistic models indicated a good fit to the observed data. Salmonella Enteritidis was more sensitive at increasing salt content as compared with L. monocytogenes. On the other hand, pH changes had greater effect on growth initiation of L. monocytogenes than they had on growth initiation of Salmonella Enteritidis. Presence of essential oil up to 0.06% (vol/vol) had no or little effect on growth initiation of both microorganisms tested, while the concentration of 0.1% (vol/vol) essential oil exhibited great inhibition on growth initiation, especially when it was combined with increased salt content and low temperatures. The antimicrobial potency of S. thymbra essential oil was more pronounced when multiple hurdles were applied. Modeling the growth boundaries offers a useful tool to food microbiologists for assessing the antimicrobial activity in a range of food preservation conditions as compared with the conventional MIC determination.

Modelling the effect of temperature and water activity on the growth rate and growth/no growth interface of Byssochlamys fulva and Byssochlamys nivea

The purpose of the present study was to apply a modelling approach to define the growth rate and growth/no growth interface of Byssochlamys fulva and Byssochlamys nivea on a synthetic medium as a function of temperature and water activity. Both fungal species were grown on malt extract agar at different temperatures (10, 15, 20, 25, 30, 35, 40 and 45 degrees C) and a(w) levels (0.88, 0.90, 0.92, 0.94, 0.96 and 0.99) for a period of 30 days. Growth responses were evaluated over time in terms of colony diameter changes. Growth data were fitted to the primary model of Baranyi and the resulting growth rates were further modeled as a function of temperature and water activity using the cardinal model with inflection (CMI) (Rosso et al., 1993). A logistic regression quadratic polynomial model was also employed to predict the probability of growth over storage time. Estimated parameters for minimum, maximum and optimum temperatures for growth were 9.1 degrees C, 46.4 degrees C and 32.1 degrees C for B. fulva and 10.5 degrees C, 43.2 degrees C and 32.1 degrees C for B. nivea. The respective values for a(w) were 0.893, 0.993 and 0.985 for B. fulva and 0.892, 0.992 and 0.984 for B. nivea. No growth was observed at 0.88 a(w) regardless of temperature for both species, whereas B. nivea ascospores could not grow at 10 and 45 degrees C irrespective of a(w). Regarding growth boundaries, the degree of agreement between predictions and observations was >98% concordant for both species. The erroneously predicted growth cases were 1.4-4.2% false positive and 2.1-3.5% false negative for B. nivea and B. fulva, respectively. The developed logistic model was validated with two literature data sets as well as with data from independent experiments carried out on fruit juices. Validation results showed that agreement with literature data for growth was 25 out of 36 (69.4%) cases, whereas validation on fruit juice data failed in only 6 cases (5 false positives and 1 false negative) out of 128 cases.

Safety-based shelf life model for frankfurters based on time to detect Listeria monocytogenes with initial inoculum below detection limit

The growth of Listeria monocytogenes inoculated on frankfurters at four inoculum levels (0.1, 0.04, 0.01, and 0.007 CFU/g) was examined at 4, 8, and 12 degrees C until the time L. monocytogenes populations reached a detectable limit of at least 2 CFU/g. A scaled-down assumption was made to simulate a 25-g sample from a 100-lb batch size in a factory setting by using a 0.55-g sample from a 1,000-g batch size in a laboratory. Samples of 0.55 g were enriched in PDX-LIB selective medium, and presumptive results were confirmed on modified Oxford agar. Based on the time to detect (TTD) from each inoculum level and at each temperature, a shelf life model was constructed to predict the detection or risk levels reached by L. monocytogenes on frankfurters. The TTD increased with reductions in inoculum size and storage temperature. At 4 degrees C the TTDs (+/- standard error) observed were 42.0 +/- 1.0, 43.5 +/- 0.5, 50.7 +/- 1.5, and 55.0 +/- 3.0 days when the inoculum sizes were 0.1, 0.04, 0.01, and 0.007 CFU/g, respectively. From the same corresponding inoculum sizes, the TTDs at 8 degrees C were 4.5 +/- 0.5, 6.5 +/- 0.5, 7.0 +/- 1.0, and 8.5 +/- 0.5 days. Significant differences (P < 0.05) between TTDs were observed only when the inoculum sizes differed by at least 2 log. On a shelf life plot of 1n (TTD) versus temperature, the Q10 (increase in TTD for a 10 degrees C increase in temperature) values ranged from 24.5 to 44.7 and with no significant influence from the inoculum densities. When the observed TTDs were compared with the expected detection times based on the data obtained from a study with an inoculum size of 10 to 20 CFU/g, significant deviations were noted at lower inoculum levels. These results can be valuable in designing a safety-based shelf life model for frankfurters and in performing quantitative risk assessment of listeriosis at low and practical contamination levels.

Growth/no growth models describing the influence of pH, lactic and acetic acid on lactic acid bacteria developed to determine the stability of acidified sauces

Growth/no growth models were developed for two spoilage bacteria typical for acidified sauces, L. plantarum and L. fructivorans. Influencing factors embedded in the model are also those typically encountered in these acidified sauces. The pH was varied between 3.0 and 5.0 (5 levels), and the acetic and lactic acid concentration ranged from 0 to 3% (6 levels). Modified MRS broth was inoculated at a high inoculation level (10(6) CFU/ml), incubated at 30 degrees C and growth was assessed by optical density measurements. All combinations of environmental conditions were tested in twelvefold yielding precise values for the probability of growth. Data were modelled by means of ordinary logistic regression. A comparison was made between a model containing the total acid concentrations as explanatory variables, on the one hand, and a model differentiating between the dissociated and undissociated concentrations, on the other hand. Results showed that (i) L. plantarum and L. fructivorans behave differently, resulting in a clearly distinct growth/no growth interface, (ii) there was no great difference between the established models with different explanatory variables, (iii) in some cases, growth/no growth boundaries at very low probabilities (which are more practical in industry) show illogical behaviour. The results of this study were also compared with the CIMSCEE code, which is often used by food producers to determine the stability of their acidified food products.

Influence of pH, water activity and acetic acid concentration on Listeria monocytogenes at 7 degrees C: data collection for the development of a growth/no growth model

Growth/no growth models can be used to determine the chance that microorganisms will grow in specific environmental conditions. As a consequence, these models are of interest in the assessment of the safety of foods which can be contaminated with food pathogens. In this paper, growth/no growth data for Listeria monocytogenes (in a monoculture and in a mixed strain culture) are presented. The data were gathered at 7 degrees C in Nutrient Broth with different combinations of environmental factors pH (5.0-6.0, six levels), water activity (0.960-0.990, six levels) and acetic acid concentration (0-0.8% (w/w), five levels). This combination of environmental factors for the development of a growth/no growth model was based on the characteristics of sauces and mayonnaise based salads. The strains used were chosen from screening experiments in which the pH, water activity and acetic acid resistance of 26 L. monocytogenes strains (LFMFP culture collection) was determined at 30 degrees C in Brain Heart Infusion broth. The screening showed that most L. monocytogenes strains were not able to grow at a(w)<0.930, pH<4.3 or a total acetic acid concentration >0.4% (w/w). Among these strains, the ones chosen were the most resistant to one of these factors in the hope that, if the resulting model predicted no growth at certain conditions for those more resistant strains, then these predictions would also be valid for the less resistant strains. A mixed strain culture was also examined to combine the strains that were most resistant to one of the factors. A full factorial design with the selected strains was tested. The experiments were performed in microtiter plates and the growth was followed by optical density measurements at 380 nm. The plates were inoculated with 6 log CFU/ml and twenty replicates were made for each treatment combination. These data were used (1) to determine the growth/no growth boundary and (2) to estimate the influence of the environmental conditions on the time to detection. From the monoculture and mixed strain data, the growth boundary of L. monocytogenes is shown not to be a straight cut-off but a rather narrow transition zone. The experiments also showed that in the studied region, a(w) did not have a pronounced influence on the position of the growth/no growth boundary while a low concentration of acetic acid (0.2% (w/w)) and a pH decrease from 6.0 to 5.8 was sufficient to significantly reduce the possibility of growth. The determination of the time to detection showed a significant increase at the combinations of environmental conditions near the 'no growth zone'. For example, at 0.2% (w/w) acetic acid, there was an increase from +/-10 days to 30 days by lowering pH from 5.8 to 5.6 at a(w) values of 0.985 and 0.979, while at pH 5.4 less than 50% growth occurred for all a(w) values.