A predictive model for the combined effect of pH, sodium chloride and storage temperature on the growth of Brochothrix thermosphacta

Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models

Predictive microbiology is a rapidly evolving field that has gained significant interest over the years due to its diverse application in food safety. Predictive models are widely used in food microbiology to estimate the growth of microorganisms in food products. These models represent the dynamic interactions between intrinsic and extrinsic food factors as mathematical equations and then apply these data to predict shelf life, spoilage, and microbial risk assessment. Due to their ability to predict the microbial risk, these tools are also integrated into hazard analysis critical control point (HACCP) protocols. However, like most new technologies, several limitations have been linked to their use. Predictive models have been found incapable of modeling the intricate microbial interactions in food colonized by different bacteria populations under dynamic environmental conditions. To address this issue, researchers are integrating several new technologies into predictive models to improve efficiency and accuracy. Increasingly, newer technologies such as whole genome sequencing (WGS), metagenomics, artificial intelligence, and machine learning are being rapidly adopted into newer-generation models. This has facilitated the development of devices based on robotics, the Internet of Things, and time-temperature indicators that are being incorporated into food processing both domestically and industrially globally. This study reviewed current research on predictive models, limitations, challenges, and newer technologies being integrated into developing more efficient models. Machine learning algorithms commonly employed in predictive modeling are discussed with emphasis on their application in research and industry and their advantages over traditional models.

The pathogenic and spoilage bacteria associated with red meat and application of different approaches of high CO2 packaging to extend product shelf-life

With the fast-global development of packaging techniques, the potential antimicrobial effect of CO₂, as a safe, cheap and readily available gas, makes it the integral component for packaging of meat products. The associated spoilage and/or pathogenic bacteria on raw meat may respond in different ways to elevated CO₂ concentrations. The growth of some aerobic Gram-negative bacteria such as Pseudomonas spp. is significantly inhibited but some LAB bacteria may be allowed to grow faster and dominate the product. The antimicrobial efficacy of enriched CO₂ packaging is attributed to the rate of CO₂ solubility in the product which is itself affected by the level of headspace CO₂, product pH, temperature and the ratio of headspace gas to product (G:P). This review, first, explores the varied range of beef and sheep meat spoilage and pathogenic bacteria and the intrinsic and extrinsic parameters that may influence the pattern of microbial growth and meat spoilage rate during storage. Then, the antimicrobial mechanism of elevated CO₂ packaging will be discussed and the different approaches of achieving enriched CO₂ packaging i.e. the traditional technique of flushing a desired gas mixture and/or using the new commercially developed CO₂ emitters will then be compared in terms of their strengths, limitations and technical mode of action.

Salmonella Prevalence Alone Is Not a Good Indicator of Poultry Food Safety

Salmonella is a leading cause of foodborne illness (i.e., salmonellosis) outbreaks, which on occasion are attributed to ground turkey. The poultry industry uses Salmonella prevalence as an indicator of food safety. However, Salmonella prevalence is only one of several factors that determine risk of salmonellosis. Consequently, a model for predicting risk of salmonellosis from individual lots of ground turkey as a function of Salmonella prevalence and other risk factors was developed. Data for Salmonella contamination (prevalence, number, and serotype) of ground turkey were collected at meal preparation. Scenario analysis was used to evaluate effects of model variables on risk of salmonellosis. Epidemiological data were used to simulate Salmonella serotype virulence in a dose-response model that was based on human outbreak and feeding trial data. Salmonella prevalence was 26% (n = 100) per 25 g of ground turkey, whereas Salmonella number ranged from 0 to 1.603 with a median of 0.185 log per 25 g. Risk of salmonellosis (total arbitrary units (AU) per lot) was affected (p ≤ 0.05) by Salmonella prevalence, number, and virulence, by incidence and extent of undercooking, and by food consumption behavior and host resistance but was not (p > 0.05) affected by serving size, serving size distribution, or total bacterial load of ground turkey when all other risk factors were held constant. When other risk factors were not held constant, Salmonella prevalence was not correlated (r = -0.39; p = 0.21) with risk of salmonellosis. Thus, Salmonella prevalence alone was not a good indicator of poultry food safety because other factors were found to alter risk of salmonellosis. In conclusion, a more holistic approach to poultry food safety, such as the process risk model developed in the present study, is needed to better protect public health from foodborne pathogens like Salmonella.

Kinetics of α‑dicarbonyl compounds formation in glucose-glutamic acid model of Maillard reaction

As a potential health hazard, α-dicarbonyl compounds have been detected in the thermally processed foods. In order to investigate the formation kinetics of α-dicarbonyl compounds, liquid chromatography-electrospray tandem mass spectrometry was employed to determine the content of α-dicarbonyl compounds in glucose-only and glucose-glutamic acid (glucose-Glu) thermal reaction models. The 3-deoxyglucosone content was significantly higher than 6 α-dicarbonyl compounds at 90-110℃, 0-6 hr in the two tested systems. The glutamic acid promoted the content accumulation of 1-deoxyglucosone, diacetyl, methylglyoxal, and glyoxal, whereas inhibited the content of 3-deoxyglucosone and 3,4-dideoxyglucosone. Three-fifths of the tested compounds content increased linearly with time increasing, but in glucose-only system, the 1-deoxyglucosone content increased logarithmically at 95-110℃ over reaction time. The formation of glucose (100-110℃, glucose-only and glucose-Glu), 5-hydroxymethylfurfural (100-110℃, glucose-only), 1-deoxyglucose (105-110℃, glucose-Glu), 3,4-dideoxyglucosone (110℃, glucose-Glu), glyoxal (95-110℃, glucose-Glu) and diacetyl (90-95℃, glucose-Glu) could be well fitted by exponential equation. Shortening the heating time and reducing heating temperature (except glyoxal in glucose-only system) were the effective methods to decrease α-dicarbonyl compounds content in the two tested systems. Additionally, high temperature could also reduce α-dicarbonyl compounds content, such as 3-deoxyglucosone (≥110℃, glucose-only), 1-deoxyglucosone (≥110℃, glucose-only), glucosone (≥110℃, glucose-only; ≥100℃, glucose-Glu), methyloxyl (≥110℃, glucose-only; ≥100℃, glucose-Glu), diacetyl (≥110℃, glucose-only), and glyoxal (≥100℃, glucose-Glu).

The complex multicellular morphology of the food spoilage bacteria Brochothrix thermosphacta strains isolated from ground chicken

Herein we describe a highly structured, filamentous growth phenotype displayed by an isolate of the food spoilage microorganism Brochothrix thermosphacta. The growth morphology of this B. thermosphacta strain (strain BII) was dependent on environmental factors such as the growth media, incubation temperatures, and the inoculum concentration. Inoculation of cultures in highly dilute suspensions resulted in the formation of isolated, tight aggregates resembling fungal growth in liquid media. This same strain also formed stable, mesh-like structures in 6-well tissue culture plates under specific growth conditions. The complex growth phenotype does not appear to be unique to strain BII but was common among B. thermosphacta strains isolated from chicken. Light and electron micrographs showed that the filaments of multiple BII cells can organize into complex, tertiary structures resembling multistranded cables. Time-lapse microscopy was employed to monitor the development of such aggregates over 18 h and revealed growth originating from short filaments into compact ball-like clusters that appeared fuzzy due to protruding filaments or cables. This report is the first to document this complex filamentous growth phenotype in a wild-type bacterial isolate of B. thermosphacta.

Kinetics of 5-hydroxymethylfurfural formation in the sugar-amino acid model of Maillard reaction

BACKGROUND

As a potential health hazard, 5-hydroxymethylfurfural (HMF) has been detected in thermally processed foods high in sugar and amino acids. In order to analyze HMF quantitatively and investigate the kinetics of its formation, high-performance liquid chromatography was employed to determine the content of HMF in six sugar-amino acid thermal reaction models.

RESULTS

In thermal reaction models, formation of HMF was significantly affected by sugar and amino acid composition, pH value and heating conditions. HMF formation increased with increasing sugar and amino acid (cysteine excepted) content, temperature and reaction time. A maximum amount of HMF of 1.50 g kg^-1 was detected in the sucrose-glutamic acid model at 110 °C and 6 h. Low pH value and added acidic amino acids promoted the formation of HMF, especially in the sucrose-containing system.

CONCLUSION

HMF formation followed first-order kinetics in four models, including the model of glucose-cysteine, glucose-glutamic acid, glucose-leucine and sucrose-leucine. In contrast, HMF formation followed zero-order kinetics in the model of sucrose-glutamic acid. The quantity of HMF increased as the quantity of sugar and amino acid increased (cysteine excepted) in six tested models. © 2018 Society of Chemical Industry.

Reducing Salt in Raw Pork Sausages Increases Spoilage and Correlates with Reduced Bacterial Diversity

Raw sausages are perishable foodstuffs; reducing their salt content raises questions about a possible increased spoilage of these products. In this study, we evaluated the influence of salt reduction (from 2.0% to 1.5% [wt/wt]), in combination with two types of packaging (modified atmosphere [50% mix of CO2-N2] and vacuum packaging), on the onset of spoilage and on the diversity of spoilage-associated bacteria. After 21 days of storage at 8°C, spoilage was easily observed, characterized by noticeable graying of the products and the production of gas and off-odors defined as rancid, sulfurous, or sour. At least one of these types of spoilage occurred in each sample, and the global spoilage intensity was more pronounced in samples stored under modified atmosphere than under vacuum packaging and in samples with the lower salt content. Metagenetic 16S rRNA pyrosequencing revealed that vacuum-packaged samples contained a higher total bacterial richness (n = 69 operational taxonomic units [OTUs]) than samples under the other packaging condition (n = 46 OTUs). The core community was composed of 6 OTUs (Lactobacillus sakei, Lactococcus piscium, Carnobacterium divergens, Carnobacterium maltaromaticum, Serratia proteamaculans, and Brochothrix thermosphacta), whereas 13 OTUs taxonomically assigned to the Enterobacteriaceae, Enterococcaceae, and Leuconostocaceae families comprised a less-abundant subpopulation. This subdominant community was significantly more abundant when 2.0% salt and vacuum packaging were used, and this correlated with a lower degree of spoilage. Our results demonstrate that salt reduction, particularly when it is combined with CO2-enriched packaging, promotes faster spoilage of raw sausages by lowering the overall bacterial diversity (both richness and evenness).

IMPORTANCE

Our study takes place in the context of raw meat product manufacturing and is linked to a requirement for salt reduction. Health guidelines are calling for a reduction in dietary salt intake. However, salt has been used for a very long time as a hurdle technology, and salt reduction in meat products raises the question of spoilage and waste of food. The study was conceived to assess the role of sodium chloride reduction in meat products, both at the level of spoilage development and at the level of bacterial diversity, using 16S rRNA amplicon sequencing and raw pork sausage as a meat model.

Thymus Vulgaris (Red Thyme) and Caryophyllus Aromaticus (Clove) Essential Oils to Control Spoilage Microorganisms in Pork Under Modified Atmosphere

In recent years, it has been confirmed that essential oils (EOs) exert antimicrobial activity as they are able to inhibit cell growth and inactivate microbial cells. The application of biopreservation strategies by means of EOs opens up interesting perspectives in the food industry, including meat production. The paper aims to evaluate the effects of Thymus vulgaris (red thyme) and Caryophyllus aromaticus (cloves) EOs on the development of the spoilage population of fresh pork packaged under modified atmosphere (MAP). In particular, the research was focused on Brochothrix thermosphacta, a specific spoilage microorganism of fresh meat packed in anaerobic conditions or under MAP. Amongst seven EOs, those that showed the highest antimicrobial activity on 5 B. thermosphacta strains in vitro were: cloves [minimum inhibitory concentration (MIC) 0.6-2.5 mg/mL], savory (MIC 2.5-5.0 mg/mL), and red thyme (MIC 2.5 to 20 mg/mL). Red thyme and cloves EOs were selected for meat treatment, by increasing the dose at 20 and 40 mg/mL respectively, to take into account the matrix effect that can reduce EO availability. In spite of the minor efficacy observed in vitro, 40 mg/mL red thyme EO strongly limited the growth of B. thermosphacta in pork samples up to day 6 of storage [below 3.0 Log colony forming unit (CFU)/g, starting from 2.0 Log CFU/g at time 0], and exerted an antimicrobial effect also on the aerobic mesophilic count. Good results were obtained also with 20 mg/mL red thyme EO. The control of B. thermosphacta growth through EOs encourages research on alternative methods for extending the shelf life of fresh meat under MAP.

Optimal resting-growth strategies of microbial populations in fluctuating environments

Bacteria spend most of their lifetime in non-growing states which allow them to survive extended periods of stress and starvation. When environments improve, they must quickly resume growth to maximize their share of limited nutrients. Cells with higher stress resistance often survive longer stress durations at the cost of needing more time to resume growth, a strong disadvantage in competitive environments. Here we analyze the basis of optimal strategies that microorganisms can use to cope with this tradeoff. We explicitly show that the prototypical inverse relation between stress resistance and growth rate can explain much of the different types of behavior observed in stressed microbial populations. Using analytical mathematical methods, we determine the environmental parameters that decide whether cells should remain vegetative upon stress exposure, downregulate their metabolism to an intermediate optimum level, or become dormant. We find that cell-cell variability, or intercellular noise, is consistently beneficial in the presence of extreme environmental fluctuations, and that it provides an efficient population-level mechanism for adaption in a deteriorating environment. Our results reveal key novel aspects of responsive phenotype switching and its role as an adaptive strategy in changing environments.

Development of a microbial model for the combined effect of temperature and pH on spoilage of ground meat, and validation of the model under dynamic temperature conditions

The changes in microbial flora and sensory characteristics of fresh ground meat (beef and pork) with pH values ranging from 5.34 to 6.13 were monitored at different isothermal storage temperatures (0 to 20 degrees C) under aerobic conditions. At all conditions tested, pseudomonads were the predominant bacteria, followed by Brochothrix thermosphacta, while the other members of the microbial association (e.g., lactic acid bacteria and Enterobacteriaceae) remained at lower levels. The results from microbiological and sensory analysis showed that changes in pseudomonad populations followed closely sensory changes during storage and could be used as a good index for spoilage of aerobically stored ground meat. The kinetic parameters (maximum specific growth rate [mu(max)] and the duration of lag phase [lambda]) of the spoilage bacteria were modeled by using a modified Arrhenius equation for the combined effect of temperature and pH. Meat pH affected growth of all spoilage bacteria except that of lactic acid bacteria. The "adaptation work," characterized by the product of mu(max) and lambda(mu(max) x lambda) was found to be unaffected by temperature for all tested bacteria but was affected by pH for pseudomonads and B. thermosphacta. For the latter bacteria, a negative linear correlation between ln(mu(max) x lambda) and meat pH was observed. The developed models were further validated under dynamic temperature conditions using different fluctuating temperatures. Graphical comparison between predicted and observed growth and the examination of the relative errors of predictions showed that the model predicted satisfactorily growth under dynamic conditions. Predicted shelf life based on pseudomonads growth was slightly shorter than shelf life observed by sensory analysis with a mean difference of 13.1%. The present study provides a "ready-to-use," well-validated model for predicting spoilage of aerobically stored ground meat. The use of the model by the meat industry can lead to effective management systems for the optimization of meat quality.

Quantifying the robustness of a broth-based Escherichia coli O157:H7 growth model in ground beef

The robustness of a microbial growth model must be assessed before the model can be applied to new food matrices; therefore, a methodology for quantifying robustness was developed. A robustness index (RI) was computed as the ratio of the standard error of prediction to the standard error of calibration for a given model, where the standard error of calibration was defined as the root mean square error of the growth model against the data (log CFU per gram versus time) used to parameterize the model and the standard error of prediction was defined as the root mean square error of the model against an independent data set. This technique was used to evaluate the robustness of a broth-based model for aerobic growth of Escherichia coli 0157:H7 (in the U.S Department of Agriculture Agricultural Research Service Pathogen Modeling Program) in predicting growth in ground beef under different conditions. Comparison against previously published data (132 data sets with 1,178 total data points) from experiments in ground beef at various experimental conditions (4.8 to 45 degrees C and pH 5.5 to 5.9) yielded RI values ranging from 0.11 to 2.99. The estimated overall RI was 1.13. At temperatures between 15 and 40 degrees C, the RI was close to and smaller than 1, indicating that the growth model is relatively robust in that temperature range. However, the RI also was related (P < 0.05) to temperature. By quantifying the predictive accuracy relative to the expected accuracy, the RI could be a useful tool for comparing various models under different conditions.

Predictive modeling of microorganisms: LAG and LIP in monotonic growth

The variety of models that are currently being used in "Predictive Microbiology" or "Microbial Ecology" aiming at reproducing the growth curve of microorganisms motivates this study. It is widely agreed that no model can reproduce generically and consistently the "LAG Phase" of microorganism growth. To promote the objective of "predictive modeling", we present here a model that was derived from first biological and physical principles, which is shown to reproduce qualitatively as well as quantitatively all typical features captured experimentally in microorganism growth. In particular, this paper focuses on capturing and controlling of the "LAG Phase" a typical phase in microorganisms growth, at the initial growth stages, as well as the inflection point on the "ln curve" of the cell concentration, i.e. a Logarithmic Inflection Point referred here as "LIP". The proposed model also captures the Logistic Growth curve as a special case. Comparison of the solutions obtained from the proposed model with experimental data confirms its quantitative validity, as well as its ability to recover a wide range of qualitative features captured in experiments.

Predictive modelling of growth and measurement of enzymatic synthesis and activity by a cocktail of Brochothrix thermosphacta

The possibility was examined of developing a predictive model that combined microbial growth (increase in cellular number) and extracellular enzyme activity of a cocktail of three strains of Brochothrix thermosphacta. Estimations of growth and enzyme activity were made within a three-dimensional matrix of conditions: temperature 2-20 degrees C, pH value 4.0-7.5 and water activity (a(w)) 0.95-0.995. A model which predicted growth based on increases in cell number was constructed. No extracellular lipases were detected, but slight proteolytic reactions were observed. Although it was not possible to model protease activity, the growth model and information relating to enzyme activity will be made freely available in a database on the Internet.

Time–temperature profiles of chilled ready-to-eat foods in school catering and probabilistic analysis of Listeria monocytogenes growth

The purpose of this study was to evaluate the chill chain in school catering by monitoring time-temperature profiles. Chilled ready-to-eat foods have been chosen as subject of this study because of their high risk due to their production, storage and distribution steps, separated in time, followed by consumption without any further thermal treatment. In order to integrate the effects of storage duration and storage temperature, a quantitative criterion, namely "TTE" or "Time-Temperature Equivalent", was proposed. To illustrate the sanitary consequences of the recorded thermal history, Listeria monocytogenes growth was predicted based on reference growth curves in chilled ready-to-eat food products. The study of five centralised kitchens and 11 school-lunch canteens demonstrated in general a satisfactory maintenance of the chill chain. However, the coincidence of extended storage duration (due to weekends) and temperature abuse was observed and could lead to a significant microbial development.

Development and validation of experimental protocols for use of cardinal models for prediction of microorganism growth in food products

An experimental protocol to validate secondary-model application to foods was suggested. Escherichia coli, Listeria monocytogenes, Bacillus cereus, Clostridium perfringens, and Salmonella were observed in various food categories, such as meat, dairy, egg, or seafood products. The secondary model validated in this study was based on the gamma concept, in which the environmental factors temperature, pH, and water activity (aw) were introduced as individual terms with microbe-dependent parameters, and the effect of foodstuffs on the growth rates of these species was described with a food- and microbe-dependent parameter. This food-oriented approach was carried out by challenge testing, generally at 15 and 10 degrees C for L. monocytogenes, E. coli, B. cereus, and Salmonella and at 25 and 20 degrees C for C. perfringens. About 222 kinetics in foods were generated. The results were compared to simulations generated by existing software, such as PMP. The bias factor was also calculated. The methodology to obtain a food-dependent parameter (fitting step) and therefore to compare results given by models with new independent data (validation step) is discussed in regard to its food safety application. The proposed methods were used within the French national program of predictive microbiology, Sym'Previus, to include challenge test results in the database and to obtain predictive models designed for microbial growth in food products.

Validation of a polynomial regression model: the thermal inactivation of Bacillus subtilis spores in milk

AIMS

The predicted survival of Bacillus subtilis 168 spores from a polynomial regression equation was validated in milk.

METHODS AND RESULTS

Bias factor suggested as an index of model performance was used to validate the polynomial model predictions in ultrahigh temperature (UHT) treated and sterilized whole and skim milk. Model predictions were fail safe, predicting higher D-values (decimal reduction times) in buffer than actually noted in milk.

CONCLUSIONS

The D-values for spores were lower in milk as compared with those predicted in potassium phosphate buffer contrary to the popular expectation of better spore survival in complex food systems. The Bias factor, a quantitative measure of the model performance, indicated that on average the model predictions exceed the observations by 40% in the case of whole milk and by 60% in the case of skim milk.

SIGNIFICANCE AND IMPACT OF THE STUDY

The present work is an attempt to ascertain the extent of reliability that one can safely place in polynomial model predictions, without compromising on the safety or palatability of foods where it is eventually intended to be applied. The work has also highlighted the differences in the thermal inactivation pattern of spores in buffer and in milk with a possible influence of the various constituents of milk. The work will assist the dairy industry to better design thermal processes to ensure longer shelf life of dairy foods.

Predictive modelling of growth and enzyme production and activity by a cocktail of Pseudomonas spp., Shewanella putrefaciens and Acinetobacter sp

The possibility was examined of developing a predictive model that combined microbial growth (increase in cellular number) with extracellular lipolytic and proteolytic enzyme activity of a cocktail of four strains of Pseudomonas spp. and one strain each of Acinetobacter sp. and Shewanella putrefaciens. Environmental conditions within the following matrix of conditions were examined: temperature 2-20 degrees C, pH value 4.0-7.5 and water activity (a(w)) 0.95-0.995 and a model was constructed, which predicted growth based on increase in cell number. Data on lipase production and protease activity were generated and will be available as a database, but no function could be identified, which was a good fit to these data, since most enzymatic production and activity occurred, as expected, during transition from exponential to stationary phase. Even at lower cell numbers, in more unfavourable conditions, hydrolysing effects were detectable, which made it difficult to construct a model combining both microbiological and enzymatic data.

Antibacterial activity of 11 essential oils against Bacillus cereus in tyndallized carrot broth

The antibacterial activity of 11 essential oils from aromatic plants against the strain INRA L2104 of the foodborne pathogen Bacillus cereus grown in carrot broth at 16 degrees C was studied. The quantity needed by the essential oils of nutmeg, mint, clove, oregano, cinnamon, sassafras, sage, thyme or rosemary to produce 14-1110% relative extension of the lag phase was determined. Total growth inhibition of bacterial spores was observed for some of the antimicrobial agents assayed. The addition of 5 microl cinnamon essential oil per 100 ml of broth in combination with refrigeration temperatures of <or=8 degrees C produced the conditions necessary to inhibit the growth of B. cereus for at least 60 days in a model, refrigerated minimally processed food product, made with carrots and tyndallized. This is especially important considering that the psychrotrophic enterotoxigenic strain of B. cereus INRA TZ415 was able to grow in this substrate at low temperatures in the absence of any essential oil. Furthermore, the study of the sensory characteristics of the final product suggests that the use of cinnamon essential oil can be considered as an alternative to "traditional food preservatives".

Modeling microbial growth within food safety risk assessments

Risk estimates for food-borne infection will usually depend heavily on numbers of microorganisms present on the food at the time of consumption. As these data are seldom available directly, attention has turned to predictive microbiology as a means of inferring exposure at consumption. Codex guidelines recommend that microbiological risk assessment should explicitly consider the dynamics of microbiological growth, survival, and death in foods. This article describes predictive models and resources for modeling microbial growth in foods, and their utility and limitations in food safety risk assessment. We also aim to identify tools, data, and knowledge sources, and to provide an understanding of the microbial ecology of foods so that users can recognize model limits, avoid modeling unrealistic scenarios, and thus be able to appreciate the levels of confidence they can have in the outputs of predictive microbiology models. The microbial ecology of foods is complex. Developing reliable risk assessments involving microbial growth in foods will require the skills of both microbial ecologists and mathematical modelers. Simplifying assumptions will need to be made, but because of the potential for apparently small errors in growth rate to translate into very large errors in the estimate of risk, the validity of those assumptions should be carefully assessed. Quantitative estimates of absolute microbial risk within narrow confidence intervals do not yet appear to be possible. Nevertheless, the expression of microbial ecology knowledge in "predictive microbiology" models does allow decision support using the tools of risk assessment.

Influence of pH and temperature on growth of Bacillus cereus in vegetable substrates

Bacillus cereus is a food-borne pathogen which most often contaminates foods of plant origin. Spores of psychrotrophic strains have the ability to germinate and grow at refrigeration temperatures in different vegetable substrates, such as carrot broth, zucchini broth, and cooked carrot purée. In some circumstances, factors such as pH, heat treatment, and storage temperature play a fundamental role in controlling the growth of these psychrotrophic strains and in extending the shelf life of refrigerated, minimally processed vegetable-based products in relation to pathogenic spore-forming bacteria. The combination of mild acidification (pH 5.0) and refrigeration (</=8 degrees C) inhibited B. cereus growth for at least 60 days in vegetable substrates similar to those mentioned above. This protection was maintained even when the temperature to which the food was exposed reached 12 degrees C. Psychrotrophic strains of B. cereus were inhibited in carrot broth by heating at 90 degrees C for 7.5 min, if the broth was refrigerated at a temperature of 8 degrees C or lower. If the vegetable product was exposed to temperatures of mild abuse (12 degrees C), it was necessary to implement a more drastic heat treatment (90 degrees C for 30 min).

Growth pH does not affect the initial physiological state parameter (pO) of Listeria monocytogenes

It has proven difficult to develop adequate mathematical models for the lag phase (lambda) which characterizes the adaptation period prior to the initiation of exponential growth by microorganisms. This is due, in part, to our incomplete understanding of the nature of the initial physiological state of cells (defined as h0 or p0 depending on the model), and changes taking place during adaptation. The objectives of the present study were to characterize p0 using data from growth of Listeria monocytogenes in an automated turbidimetric instrument (Bioscreen), and to determine the influence of limiting growth pH. A model was developed for individual cells which combined a continuous adaptation phase (defined by p0) with a discrete step marking the transition to a continuous exponential growth phase (the CDC model). Parameters of the new model were: p0; the specific growth rate (mu); the initial cell number (N0); and the maximum cell density (Nmax). Progressive reduction of the growth pH in the Bioscreen to 4.7 decreased the p. It was noted that the regression lines for all trials at all pH values appeared to have a common x-intercept (20.086+/-1.092), and it was deduced that, when the Bioscreen detection limit (15.07 In cfu well(-1)) was subtracted, the resulting value represented the "true" value for the initial physiological state of the cells.

Stochastic modelling of bacterial lag phase

In order to study the lag distribution of the individual cells in a bacterial population, a stochastic birth model is used in this study. An integral formula is applied to transform the assumed lag distribution into a growth function describing the transition between lag and exponential phase of the cell population. By means of this formula, it is pointed out that traditional viable count curves are not suitable to identify the distribution of individual cells' lag time.

Debating the biological reality of modelling preservation

Predictive food microbiology is a rapidly developing science and has made great advances. The aim is to debate a number of issues in modelling preservation: (1) inoculum and prehistory effects on lag times and process susceptibility; (2) mechanistic vs. empirical modelling; and (3) concluding remarks (the Species concept, methodology and biovariability). Increasing the awareness in these issues may bridge the gap between the complex reality in food microbial physiology and the application potential of predictive models. The challenge of bringing integrated preservation or risk analysis further and developing ways to truly model and link biological susceptibility distributions from raw ingredients via process survival to outgrowth probabilities in the final product remains.