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.

Impact of food model (micro)structure on the microbial inactivation efficacy of cold atmospheric plasma.

The large potential of cold atmospheric plasma (CAP) for food decontamination has recently been recognized. Room-temperature gas plasmas can decontaminate foods without causing undesired changes. This innovative technology is a promising alternative for treating fresh produce. However, more fundamental studies are needed before its application in the food industry. The impact of the food structure on CAP decontamination efficacy of Salmonella Typhimurium and Listeria monocytogenes was studied. Cells were grown planktonically or as surface colonies in/on model systems. Both microorganisms were grown in lab culture media in petri dishes at 20°C until cells reached the stationary phase. Before CAP treatment, cells were deposited in a liquid carrier, on a solid(like) surface or on a filter. A dielectric barrier discharge reactor generated helium-oxygen plasma, which was used to treat samples up to 10min. Although L. monocytogenes is more resistant to CAP treatment, similar trends in inactivation behavior as for S. Typhimurium are observed, with log reductions in the range [1.0-2.9] for S. Typhimurium and [0.2-2.2] for L. monocytogenes. For both microorganisms, cells grown planktonically are easily inactivated, as compared to surface colonies. More stressing growth conditions, due to cell immobilization, result in more resistant cells during CAP treatment. The main difference between the inactivation support systems is the absence or presence of a shoulder phase. For experiments in the liquid carrier, which exhibit a long shoulder, the plasma components need to diffuse and penetrate through the medium. This explains the higher efficacies of CAP treatment on cells deposited on a solid(like) surface or on a filter. This research demonstrates that the food structure influences the cell inactivation behavior and efficacy of CAP, and indicates that food intrinsic factors need to be accounted when designing plasma treatment.

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.

Modeling growth rates as a function of temperature: model performance evaluation with focus on the suboptimal temperature range.

Secondary models, describing the microbial growth rate as a function of temperature, are evaluated with focus on model performance in the suboptimal temperature region. Escherichia coli K12 MG1655 is considered as the case study. A large set of square root of µ(max)(T)-estimates is fitted with (1) the cardinal temperature model with inflection (CTMI, Rosso et al., 1993), (2) the square root model (SQRT, Ratkowsky et al., 1983), and (3) the CTMI adapted to describe the particular behavior of Listeria at suboptimal temperatures (aCTMI, Le Marc et al., 2002). Compared to the CTMI and the SQRT, a more accurate description of the µ(max)(T)-relation is obtained with the aCTMI, certainly at temperatures below 30 °C. Also, the T(min) estimate is more realistic, i.e., ≈6 °C, compared to 8-8.5 °C for the CTMI and SQRT. Use of the aCTMI improved square root of µ(max)(T)-data description which points at the existence of two phases in the suboptimal temperature region of E. coli K12. The alternation of the square root of µ(max)(T) is most likely related to the cold shock response. These results reveal a possible shortcoming of the model structure of commonly used secondary models describing the temperature effect on the microbial growth rate.

Monitoring the intracellular pH of Zygosaccharomyces bailii by green fluorescent protein.

It is generally known that intracellular pH (pH(i)) plays a vital role in cell physiology and that pH(i) homeostasis is essential for normal cellular functions. Therefore, it is desirable to know the pH(i) during cell life cycle or under various growth conditions. Different methods to measure pH(i) have been developed and among these methods, the use of pH-sensitive green fluorescent protein (GFP) as a pH(i) indicator is a promising technique. By using this approach, not only can more accurate pH(i) results be obtained but also long-term experiments on pH(i) can be performed. In this study, the wild type Zygosaccharomyces bailii, a notorious food spoilage yeast, was transformed with a plasmid encoding a pH-sensitive GFP (i.e. pHluorin), enabling the pH(i) of the yeast to be determined based on cellular fluorescent signals. After the transformation, growth and pH(i) of the yeast were investigated in four different acidic conditions at 22°C during 26days. From the experimental results, the transformation effectiveness was verified and a good correlation between yeast growth and pH(i) was noticed. Particularly, it was observed that the yeast has an ability to tolerate a significant pH(i) drop during exponential phase and a subsequent pH(i) recovery in stationary phase, which may underlie the exceptional acid resistance of the yeast. This was the first time that a GFP-based approach for pH(i) measurement was applied in Z. bailii and that the pH(i) of the yeast was monitored during such a long period (26days). It can be expected that greater understanding of the physiological properties and mechanisms behind the special acid resistance of the yeast will be obtained from further studies on this new yeast strain.

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.

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.

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.

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.

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.

The importance of expressing antimicrobial agents on water basis in growth/no growth interface models: a case study for Zygosaccharomyces bailii.

In a previous study on Zygosaccharomyces bailii, three growth/no growth models have been developed, predicting growth probability of the yeast at different conditions typical for acidified foods (Dang, T.D.T., Mertens, L., Vermeulen, A., Geeraerd, A.H., Van Impe, J.F., Debevere, J., Devlieghere, F., 2010. Modeling the growth/no growth boundary of Z. bailii in acidic conditions: A contribution to the alternative method to preserve foods without using chemical preservatives. International Journal of Food Microbiology 137, 1-12). In these broth-based models, the variables were pH, water activity and acetic acid, with acetic acid concentration expressed in volume % on the total culture medium (i.e., broth). To continue the previous study, validation experiments were performed for 15 selected combinations of intrinsic factors to assess the performance of the model at 22°C (60days) in a real food product (ketchup). Although the majority of experimental results were consistent, some remarkable deviations between prediction and validation were observed, e.g., Z. bailii growth occurred in conditions where almost no growth had been predicted. A thorough investigation revealed that the difference between two ways of expressing acetic acid concentration (i.e., on broth basis and on water basis) is rather significant, particularly for media containing high amounts of dry matter. Consequently, the use of broth-based concentrations in the models was not appropriate. Three models with acetic acid concentration expressed on water basis were established and it was observed that predictions by these models well matched the validation results; therefore a "systematic error" in broth-based models was recognized. In practice, quantities of antimicrobial agents are often calculated based on the water content of food products. Hence, to assure reliable predictions and facilitate the application of models (developed from lab media with high dry matter contents), it is important to express antimicrobial agents' concentrations on a common basis-the water content. Reviews over other published growth/no growth models in literature are carried out and expressions of the stress factors' concentrations (on broth basis) found in these models confirm this finding.

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.

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.

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.

Estimating distributions out of qualitative and (semi)quantitative microbiological contamination data for use in risk assessment.

A framework using maximum likelihood estimation (MLE) is used to fit a probability distribution to a set of qualitative (e.g., absence in 25 g), semi-quantitative (e.g., presence in 25 g and absence in 1g) and/or quantitative test results (e.g., 10 CFU/g). Uncertainty about the parameters of the variability distribution is characterized through a non-parametric bootstrapping method. The resulting distribution function can be used as an input for a second order Monte Carlo simulation in quantitative risk assessment. As an illustration, the method is applied to two sets of in silico generated data. It is demonstrated that correct interpretation of data results in an accurate representation of the contamination level distribution. Subsequently, two case studies are analyzed, namely (i) quantitative analyses of Campylobacter spp. in food samples with nondetects, and (ii) combined quantitative, qualitative, semiquantitative analyses and nondetects of Listeria monocytogenes in smoked fish samples. The first of these case studies is also used to illustrate what the influence is of the limit of quantification, measurement error, and the number of samples included in the data set. Application of these techniques offers a way for meta-analysis of the many relevant yet diverse data sets that are available in literature and (inter)national reports of surveillance or baseline surveys, therefore increases the information input of a risk assessment and, by consequence, the correctness of the outcome of the risk assessment.

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.

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.

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.