Short communication: determination of lactoferrin in Feta cheese whey with reversed-phase high-performance liquid chromatography.

In the current paper, a method is introduced to determine lactoferrin in sweet whey using reversed-phase HPLC without any pretreatment of the samples or use of a separation technique. As a starting point, the most common HPLC protocols for acid whey, which included pretreatment of the whey along with a sodium dodecyl sulfate-PAGE step, were tested. By skipping the pretreatment and the separation steps while altering the gradient profile, different chromatographs were obtained that proved to be equally efficient to determine lactoferrin. For this novel 1-step reversed-phase HPLC method, repeatability was very high over a wide range of concentrations (1.88% intraday to 5.89% interday). The limit of detection was 35.46µg/mL [signal:noise ratio (S/N)=3], whereas the limit of quantification was 50.86µg/mL (S/N=10). Omitting the pretreatment step caused a degradation of the column's lifetime (to approximately 2,000 samples). As a result, the lactoferrin elution time changed, but neither the accuracy nor the separation ability of the method was significantly influenced. We observed that this degradation could be easily avoided or detained by centrifuging the samples to remove fat or by extensive cleaning of the column after every 5 samples.

Behavior of Escherichia coli in a heterogeneous gelatin-dextran mixture.

In a gelatin-dextran mixture, changing the (relative and/or absolute) concentration of the components leads to the formation of different microstructures. Confocal laser scanning microscopy illustrated that the nature of the microstructure determines the location and morphology of Escherichia coli colonies. Observations indicate that bacterial growth preferentially occurs in the dextran phase, regardless of the microstructure.

Quantification of the influence of trimethylamine-N-oxide (TMAO) on the heat resistance of Escherichia coli K12 at lethal temperatures.

AIM: To quantify the influence of trimethylamine-N-oxide (TMAO) on the heat resistance of Escherichia coli K12 MG1655 cells at static temperatures. METHODS AND RESULTS: Stationary-phase E. coli cells were inactivated at 52, 54 and 58°C. The heat resistance is described as reduction in the inactivation rate, k(max) , and/or an increase in the time for one decimal reduction, D, and/or an increase in the time for the fourth decimal reduction, t(4D) . CONCLUSIONS: Resistance of E. coli changed - increased - at all temperatures under study. Generally, the addition of TMAO to the growth medium protected E. coli cells, leading to an increase in their heat resistance, i.e. reduced k(max) and increased D and t(4D) values are obtained. SIGNIFICANCE AND IMPACT OF THE STUDY: Additional knowledge on the reaction of E. coli to heat in the presence of the organic osmolyte TMAO at lethal temperatures is provided. This work contributes to an improved understanding of the level of the resistance of bacteria to heat in the presence of osmolytes.

Escherichia coli population heterogeneity: subpopulation dynamics at super-optimal temperatures.

In the past years, we explored the dynamics of Escherichia coli K12 at super-optimal temperatures under static and dynamic temperature conditions (Van Derlinden et al. (2008b, 2009, 2010). Disturbed sigmoid growth curves, i.e., a sequence of growth, inactivation and re-growth, were observed, especially close to the maximum growth temperature. Based on the limited set of experiments (i.e., 2 static temperatures and 2 dynamic temperature profiles), the irregular growth curves were explained by postulating the co-existence of two subpopulations: a more resistant, growing population and a temperature sensitive, inactivating population. In this study, the dynamics of the two subpopulations are studied rigorously at 11 constant temperature levels in the region between 45°C and 46°C, with at least five repetitions per temperature. At all temperatures, the total population follows a sequence of growth, inactivation and re-growth. The sequence of different stages in the growth curves can be explained by the two subpopulations. The first growth phase and the inactivation phase reflect the presence of the sensitive subpopulation. Hereafter, the population's dynamics are dominated by the growth of the resistant subpopulation. Generally, cell counts are characterized by a large variability. The dynamics of the two subpopulations are carefully analyzed using a heterogeneous subpopulation type model to study the relation between the kinetic parameters of the two subpopulations and temperature, and to evaluate if the fraction d of resistant cells varies with temperature. Results indicate that the growth rate of the sensitive subpopulation decreases with increasing temperature within the range of 45-46°C. Furthermore, results point in the direction that the duration of this initial growth phase is approximately constant, i.e., around 2h. Possibly, the stress resistance of the cells decreases after a certain period because the metabolism is fully adapted to exponential growth. Also, the growth rate of the resistant subpopulation decreases with increasing temperature. Due to the extreme variability in the cell density data, derivation of accurate relations was not possible. From the heterogeneous model implementations, given the experimental set-up, both a constant d value and a temperature dependent d value seem plausible.

Hierarchical Bayesian analysis of censored microbiological contamination data for use in risk assessment and mitigation.

Microbiological contamination data often is censored because of the presence of non-detects or because measurement outcomes are known only to be smaller than, greater than, or between certain boundary values imposed by the laboratory procedures. Therefore, it is not straightforward to fit distributions that summarize contamination data for use in quantitative microbiological risk assessment, especially when variability and uncertainty are to be characterized separately. In this paper, distributions are fit using Bayesian analysis, and results are compared to results obtained with a methodology based on maximum likelihood estimation and the non-parametric bootstrap method. The Bayesian model is also extended hierarchically to estimate the effects of the individual elements of a covariate such as, for example, on a national level, the food processing company where the analyzed food samples were processed, or, on an international level, the geographical origin of contamination data. Including this extra information allows a risk assessor to differentiate between several scenario's and increase the specificity of the estimate of risk of illness, or compare different scenario's to each other. Furthermore, inference is made on the predictive importance of several different covariates while taking into account uncertainty, allowing to indicate which covariates are influential factors determining contamination.

Analysis of the lag phase to exponential growth transition by incorporating inoculum characteristics.

During the last decade, individual-based modelling (IbM) has proven to be a valuable tool for modelling and studying microbial dynamics. As each individual is considered as an independent entity with its own characteristics, IbM enables the study of microbial dynamics and the inherent variability and heterogeneity. IbM simulations and (single-cell) experimental research form the basis to unravel individual cell characteristics underlying population dynamics. In this study, the IbM framework MICRODIMS, i.e., MICRObial Dynamics Individual-based Model/Simulator, is used to investigate the system dynamics (with respect to the model and the system modelled). First, the impact of the time resolution on the simulation accuracy is discussed. Second, the effect of the inoculum state and size on emerging individual dynamics, such as individual mass, individual age and individual generation time distribution dynamics, is studied. The distributions of individual characteristics are more informative during the lag phase and the transition to the exponential growth phase than during the exponential phase. The first generation time distributions are strongly influenced by the inoculum state. All inocula with a pronounced heterogeneity, except the inocula starting from a uniform distribution, exhibit commonly observed microbial behaviour, like a more spread first generation time distribution compared to following generations and a fast stabilisation of biomass and age distributions.

Towards the quantification of the effect of acid treatment on the heat tolerance of Escherichia coli K12 at lethal temperatures.

The aim of this work is to investigate the effect of acid treatment -before and during heat inactivation- on the heat resistance of Escherichia coli K12 MG1655 cells at lethal temperatures. E. coli cells were grown in Brain Heart Infusion broth until they reached the stationary phase (≈10(9) cfu/mL). Approximately 30 min before thermal inactivation the early stationary phase cells were added in Brain Heart Infusion broth with a specific pH value, achieved with addition of either acetic (50% (v/v)), lactic (50% (v/v)) or hydrochloric acid (30% (v/v)), and inactivation experiments took place at 54 °C and 58 °C. The inactivation dynamics are analysed using the inactivation model of Geeraerd et al. (2000). This enables to define the induced thermotolerance of E. coli as a prolongation of the shoulder and/or a reduction of the inactivation rate. Generally, addition of acids increased the heat resistance of E. coli. The induced resistance depends on the type of acid and on the quantity added, i.e. different levels of acidification lead to a different level of heat resistance. This work provides additional knowledge on the reaction of bacterial cultures to heat after acid treatment -before and during heat treatment- and, therefore, it contributes to an improved understanding of the effect of acid exposure on the bacterial heat resistance.

On the critical evaluation of growth/no growth assessment of Zygosaccharomyces bailii with optical density measurements: liquid versus structured media.

Growth/no growth (G/NG) studies that include the effect of medium structure have typically been performed for (pathogenic) bacteria and on the basis of gelatin/agar as a gelling agent. In this study, the growth potential of the spoilage yeast Zygosaccharomyces bailii was investigated in two model systems that resemble the macroscopic physicochemical and rheological properties of acidic sauces. In a Carbopol model system, the effect of pH (3.5-4.5), glycerol concentration (17-32%), acetic acid concentration (1.5-2.0%) and medium structure (3 levels) was investigated. In xanthan gum, the behavior of the yeast was studied at different levels of pH (3.5-4.5), NaCl concentration (0.5-13.5%), acetic acid concentration (0-2.0%) and medium structure (2 levels). Rheologically, viscoelastic moduli failed to discriminate between different forms of microbial growth, whereas yield stress data appeared to provide a better indication. In general, G/NG results revealed an unexpected increase of growth probability as a function of medium structure, both at 22 and 30 °C. Whether this behavior is the result of an underlying growth-promoting mechanism could not be explained from a macroscopic point of view (e.g., macrorheology, a(w)), but may be more related to the local microscopic properties of the gels. In a second part of this study, the potential use and information content of optical density measurements for G/NG data collection in structured media were critically evaluated and confronted with their practical relevance to the food industry.

Photocatalytic inactivation of dual- and mono-species biofilms by immobilized TiO2.

Biofilms formed by different bacterial species are likely to play key roles in photocatalytic resistance. This study aims to evaluate the efficacy of a photocatalytic immobilized nanotube system (TiO2-NT) (IS) and suspended nanoparticles (TiO2-NP) (SS) against mono- and dual-species biofilms developed by Gram-negative and Gram-positive strains. Two main factors were corroborated to significantly affect the biofilm resistance during photocatalytic inactivation, i.e., the biofilm-growth conditions and biofilm-forming surfaces. Gram-positive bacteria showed great photosensitivity when forming dual-species biofilms in comparison with the Gram-positive bacteria in single communities. When grown onto TiO2-NT (IS) surfaces for immobilized photocatalytic systems, mono- and dual-species biofilms did not exhibit differences in photocatalytic inactivation according to kinetic constant values (p > 0.05) but led to a reduction of ca. 3-4 log10. However, TiO2-NT (IS) surfaces did affect biofilm colonization as the growth of mono-species biofilms of Gram-negative and Gram-positive bacteria is significantly (p ≤ 0.05) favored compared to co-culturing; although, the photocatalytic inactivation rate did not show initial bacterial concentration dependence. The biofilm growth surface (which depends on the photocatalytic configuration) also favored resistance of mono-species biofilms of Gram-positive bacteria compared to that of Gram-negative in immobilized photocatalytic systems, but opposite behavior was confirmed with suspended TiO2 (p ≤ 0.05). Successful efficacy of immobilized TiO2 for inactivation of mono- and dual-species biofilms was accomplished, making it feasible to transfer this technology into real scenarios in water treatment and food processing.

Simultaneous versus sequential optimal experiment design for the identification of multi-parameter microbial growth kinetics as a function of temperature.

Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable.

Quantifying the heterogeneous heat response of Escherichia coli under dynamic temperatures.

AIMS: Non-sigmoid growth curves of Escherichia coli obtained at constant temperatures near the maximum growth temperature (T(max)) were previously explained by the coexistence of two subpopulations, i.e. a stress-sensitive and a stress-resistant subpopulation. Mathematical simulations with a heterogeneous model support this hypothesis for static experiments at 45 degrees C. In this article, the behaviour of E. coli, when subjected to a linearly increasing temperature crossing T(max), is studied. METHODS AND RESULTS: Subpopulation dynamics are studied by culturing E. coli K12 MG1655 in brain heart infusion broth in a bioreactor. The slowly increasing temperature (degrees C h(-1)) starting from 42 degrees C results in growth up to 60 degrees C, a temperature significantly higher than the known T(max). Given some additional presumptions, mathematical simulations with the heterogeneous model can describe the dynamic experiments rather well. CONCLUSIONS: This study further confirms the existence of a stress-resistant subpopulation and reveals the unexpected growth of E. coli at temperatures significantly higher than T(max). SIGNIFICANCE AND IMPACT OF THE STUDY: The growth of the small stress-resistant subpopulation at unexpectedly high temperatures asks for a revision of currently applied models in food safety and food quality strategies.

Heat stress adaptation of Escherichia coli under dynamic conditions: effect of inoculum size.

AIMS: When subjected to dynamic temperatures surpassing the expected maximum growth temperature, Escherichia coli K12 MG1655 shows disturbed growth curves. These irregular population dynamics were explained by considering two subpopulations, i.e. a thermoresistant and a thermosensitive one (Van Derlinden et al. 2010a). In this paper, the influence of the initial cell concentration on the subpopulations' dynamics is evaluated. METHODS AND RESULTS: Experiments were performed in a bioreactor with the temperature increasing from 42 to 65.2 °C (1 and 4 °C h(-1)) with varying initial cell concentrations [6, 12 and 18 ln(CFU ml(-1))]. When started from the highest cell concentration, the population was characterized by a higher overall maximum growth temperature and a higher inactivation temperature. For all experimental set-ups, resistant cells were still growing at the final temperature of 65.2 °C. CONCLUSIONS: The initial cell concentration had no effect on temperature resistance. The increase in temperature resistance of the sensitive subpopulation was because of the change of the physiological state to the stationary phase. SIGNIFICANCE AND IMPACT OF THE STUDY: A higher initial cell concentration leads to higher heat stress adaptation when cultures reach a maximum cell concentration. The observed growth at a temperature of 65.2 °C is very important for food safety and the temperature treatment of micro-organisms.

The development of Escherichia coli and Listeria monocytogenes variants resistant to high-pressure carbon dioxide inactivation.

AIMS: The objective of this study was to investigate whether bacterial cells could develop resistance (as a part of their adaptation strategy) to high-pressure CO(2) (HPCD) inactivation. METHODS AND RESULTS: Alternating cycles of exposure to pressurized CO(2) (10.5 MPa, 35 degrees C, 400 min(-1), 70% working volume ratio during 10 min) and re-growth of the surviving subpopulation were used to investigate possible increases in the resistance of Escherichia coli and Listeria monocytogenes to HPCD. The results show an increased resistance of both pathogens tested after seven cycles of inactivation. Increase in the resistance after 15 cycles resulted in a difference of 2.4 log CFU ml(-1) in log N(0)/N(i) when parental (N(0)) and treated cultures (N(i)) of E. coli and L. monocytogenes were compared. CONCLUSIONS: Current findings indicate the ability of micro-organisms to adapt to HPCD preservation technology. SIGNIFICANCE AND IMPACT OF THE STUDY: The occurrence of HPCD-resistant micro-organisms could pose a new hazard to the safety and stability of HPCD-processed foods.

On the selection of relevant environmental factors to predict microbial dynamics in solidified media.

Several studies have shown that food structure causes slower growth rates and narrower growth boundaries of bacteria compared to laboratory media. In predictive microbiology, both a(w) or corresponding solute concentration (mainly NaCl) have been used as a growth influencing factor for kinetic models or growth/no growth interface models. The majority of these models have been based on data generated in liquid broth media with NaCl as the predominant a(w) influencing solute. However, in complex food systems, other a(w) influencing components might be present, next to NaCl. In this study, the growth rate of Salmonella typhimurium was studied in the growth region and the growth/no growth response was tested in Tryptic Soy Broth at 20 degrees C at varying gelatin concentration (0, 10, 50 g L(-1) gelatin), pH (3.25-5.5) and water activity (a(w)) (0.929-0.996). From the viewpoint of water activity, the results suggest that NaCl is the main a(w) affecting compound. However, gelatin seemed to have an effect on medium a(w) too. Moreover, there is also an interaction effect between NaCl and gelatin. From the microbial viewpoint, the results confirmed that the a(w) decreasing effect of gelatin is less harmful to cells than the effect of Na(+) ions. The unexpected shift of the growth/no growth interface to more severe conditions when going from a liquid medium to a medium with 10 g L(-1) gelatin is more pronounced when formulating the models in terms of a(w) than in terms of NaCl concentrations. At 50 g L(-1) gelatin, the model factored with NaCl concentration shifts to milder conditions (concordant to literature results) while the model with a(w) indicates a further shift to more severe conditions, which is due to the water activity lowering effect of gelatin and the interaction between gelatin and NaCl. The results suggest that solute concentration should be used instead of a(w), both for kinetic models in the growth region and for growth/no growth interface models, if the transferability of models to solid foods is to be increased.

Membrane permeabilization and cellular death of Escherichia coli, Listeria monocytogenes and Saccharomyces cerevisiae as induced by high pressure carbon dioxide treatment.

In this study, the relationship between (irreversible) membrane permeabilization and loss of viability in Escherichia coli, Listeria monocytogenes and Saccharomyces cerevisiae cells subjected to high pressure carbon dioxide (HPCD) treatment at different process conditions including temperature (35-45 degrees C), pressure (10.5-21.0 MPa) and treatment time (0-60 min) was examined. Loss of membrane integrity was measured as increased uptake of the fluorescent dye propidium iodide (PI) with spectrofluorometry, while cell inactivation was determined by viable cell count. Uptake of PI by all three strains indicated that membrane damage is involved in the mechanism of HPCD inactivation of vegetative cells. The extent of membrane permeabilization and cellular death increased with the severity of the HPCD treatment. The resistance of the three tested organisms to HPCD treatment changed as a function of treatment time, leading to significant tailing in the survival curves, and was dependent on pressure and temperature. The results in this study also indicated a HPCD-induced damage on nucleic acids during cell inactivation. Transmission electron microscopy showed that HPCD treatment had a profound effect on the intracellular organization of the micro-organisms and influenced the permeability of the bacterial cells by introducing pores in the cell wall.

Towards a low complexity carbon removal model for the optimal design of compact decentralised wastewater treatment systems.

On-site decentralised wastewater treatment systems can provide a financially attractive alternative to a sewer connection in locations far from existing sewer networks. Operational problems and shortcomings in the design of these systems still occur frequently. The aim of this paper is to provide a low complexity (i.e. easy to calibrate) but still accurate mathematical model that can be used to optimise the operational design of compact individual wastewater treatment systems. An integrated hydraulic and biological carbon removal model of a biofilm-based compact decentralised treatment system is developed. The procedure for drafting the model is generic and can be used for similar types of wastewater treatment systems since (i) the hydraulic model is based on an N-tanks-in-series model inferred from tracer test experiments and (ii) (biofilm) respirometry experiments are exploited to determine the biodegradation kinetics of the biomass. Based on the preliminary validation results of the integrated model, the carbon removal in the system can be predicted quite accurately. While some adjustments could further improve the modelling strategy, the here presented results can already assist the manufacturers of compact treatment systems in efficiently (re)designing their systems.

Design of an experimental viscoelastic food model system for studying Zygosaccharomyces bailii spoilage in acidic sauces.

Within the field of predictive microbiology, the number of studies that quantify the effect of food structure on microbial behavior is very limited. This is mainly due to impracticalities related to the use of a nonliquid growth medium. In this study, an experimental food model system for studying yeast spoilage in acid sauces was developed by selecting a suitable thickening/gelling agent. In a first step, a variety of thickening/gelling agents was screened, with respect to the main physicochemical (pH, water activity, and acetic acid and sugar concentrations) and rheological (weak gel viscoelastic behavior and presence of a yield stress) characteristics of acid sauces. Second, the rheological behavior of the selected thickening/gelling agent, Carbopol 980, was extensively studied within the following range of conditions: pH 4.0 to 5.0, acetic acid concentration of 0 to 1.0% (vol/vol), glycerol concentration of 0 to 15% (wt/vol), and Carbopol concentration of 1.0 to 1.5% (wt/vol). Finally, the applicability of the model system was illustrated by performing growth experiments in microtiter plates for Zygosaccharomyces bailii at 0, 0.5, 1.0, and 1.5% (wt/vol) Carbopol, 5% (wt/vol) glycerol, 0% (vol/vol) acetic acid, and pH 5.0. A shift from planktonic growth to growth in colonies was observed when the Carbopol concentration increased from 0.5 to 1.0%. The applicability of the model system was illustrated by estimating mu(max) at 0.5% Carbopol from absorbance detection times.

Evaluation of a mathematical model structure describing the effect of (gel) structure on the growth of Listeria innocua, Lactococcus lactis and Salmonella Typhimurium.

AIMS: To evaluate a novel secondary model structure (Int J Food Microbiol 2008; 128: 67) that describes the effect of medium structure on the maximum specific growth rate (mu(max)) of Salmonella Typhimurium on the growth of S. Typhimurium, Listeria innocua, Lactococcus lactis and Listeria monocytogenes. METHODS AND RESULTS: In the present study, the novel secondary model is validated for S. Typhimurium in more realistic media, namely, pasteurized milk and a cheese mimicking medium. The predictions were accurate. Next, the secondary model structure was evaluated in a two step and a global regression procedure on literature data. On the one hand, the growth of two other micro-organisms, namely L. innocua and L. lactis, in monoculture for varying gelatine concentrations was tested and on the other hand the growth rate of L. monocytogenes was fitted in a broth of which the viscosity was altered with polyvinylpyrrolidone. The model was able to describe the effect of increasing gelatine concentration or viscosity accurately. CONCLUSIONS: The proposed secondary model structure is able to describe the effect of gelatine concentration on the mu(max) of the micro-organisms tested in this study. SIGNIFICANCE AND IMPACT OF THE STUDY: In predictive microbiology, much attention has been paid to the effect of food structure on the mu(max) of bacteria. However, to the authors' knowledge, a lack of secondary models still exists to describe this effect. Although the proposed model is empirical, the model parameters have clear biological meaning. The predictive power of the model to describe the effect of food structure is clearly illustrated.

Unravelling Escherichia coli dynamics close to the maximum growth temperature through heterogeneous modelling.

AIMS: Previous work showed that the exponential phase of Escherichia coli K12 MG1655, grown in Brain Heart Infusion broth at temperatures close to its maximum growth temperature, is disturbed. Based on plate count data, microscopic images and literature, the existence of a heat-resistant subpopulation was hypothesized. Here, this hypothesis is mathematically explored via a heterogeneous model. METHODS AND RESULTS: A heat-sensitive and a heat-resistant subpopulation are considered. A large fraction of the population is inactivated, while the remaining smaller fraction is able to resist (or adapt to) the inimical temperature and grows. A heterogeneous model that encloses a growth model (resistant population) and an inactivation model (sensitive population) is used to describe the global population dynamics. Most experimental data can be predicted when taking parameter uncertainty via Monte Carlo simulation into account. CONCLUSIONS: The heterogeneous model accurately describes disturbed growth curves at superoptimal temperatures, except for high initial cell densities. SIGNIFICANCE AND IMPACT OF THE STUDY: This study strengthens the hypothesis of the existence of a (small) heat-resistant subpopulation in typical inoculum cultures of E. coli K12 MG1655.

Extracting information on the evolution of living- and dead-cell fractions of Salmonella Typhimurium colonies in gelatin gels based on microscopic images and plate-count data.

AIMS: The aim of this study was to extract information on cell number and colony volume dynamics of Salmonella Typhimurium colonies. METHODS AND RESULTS: Both cell number and colony volume of Salmonella Typhimurium in gelatin were monitored during the exponential and the stationary phase with varying pH and water activity, by plate counts and microscopic image analysis respectively. The exponential growth rates of cell numbers and colony volumes were correlated. The exponential growth rate of cell numbers was estimated based on this correlation and a secondary model that describes the effect of pH and water activity on the growth rate of the colony volumes. During the stationary phase, the cell number was constant, while colony volume increased, thus indicating the formation of a dead fraction. Models were developed to describe the living and dead population. CONCLUSIONS: By comparing colony volumes and cell numbers, the formation of dead fraction can be noticed from the beginning of the stationary phase, which indicates that the stationary phase is a dynamic - including both cell death and cell growth - rather than a static phase. SIGNIFICANCE AND IMPACT OF THE STUDY: This study was the first to investigate the proportion of living and dead bacteria within a stationary colony quantitatively.