Unveiling the matrix effect on Bacillus licheniformis and Bacillus subtilis spores heat inactivation between plant-based milk alternatives, bovine milk and culture medium.

This study examined the inactivation of spores of Bacillus licheniformis and Bacillus subtilis in four pea-based milk alternatives, semi-skimmed bovine milk and Brain Heart Infusion (BHI) broth to assess the matrix impact on the thermal inactivation of bacterial spores. Heat inactivation was performed with the method of capillary tubes in temperature range 97-110 °C. A four-parameter non-linear model, including initial level, shoulder duration, inactivation rate and tailing, was fitted to the data obtained. D-values were estimated and secondary ZT-value models were developed for both species. A secondary model for the shoulder length of B. licheniformis in a plant-based milk alternative formulation was built too. Models were validated at a higher temperature, 113.5 °C. D-values in the different matrices ranged between 2.3 and 8.2 min at 97 °C and 0.1-0.3 min at 110 °C for B. licheniformis. D-values for B. subtilis ranged between 3.9 and 6.3 min at 97 °C and 0.2-0.3 min at 110 °C. ZT-values in the different matrices ranged between 7.3 and 8.9 °C and 8.9-10.0 °C for B. licheniformis and B. subtilis, respectively. Significant differences in inactivation parameters were found within the pea-based formulations as well as when compared to bovine milk. Heat resistance was higher in pea-based matrices. Shoulders observed were temperature- and matrix-dependent, while no such trend was found for the tailings. These results provide insights, useful on designing safe thermal processing, limiting spoilage in plant-based milk alternatives and thus, reducing global food waste.

The Gamma concept approach as a tool to predict fresh produce supporting or not the growth of L. monocytogenes.

Challenge tests are commonly employed to evaluate the growth behavior of L. monocytogenes in food matrices; they are known for being expensive and time-consuming. An alternative could be the use of predictive models to forecast microbial behavior under different conditions. In this study, the growth behavior of L. monocytogenes in different fresh produce was evaluated using a predictive model based on the Gamma concept considering pH, water activity (aw), and temperature as input factors. An extensive literature search resulted in a total of 105 research articles selected to collect growth/no growth behavior data of L. monocytogenes. Up to 808 L. monocytogenes behavior values and physicochemical characteristics were extracted for different fruits and vegetables. The predictive performance of the model as a tool for identifying the produce commodities supporting the growth of L. monocytogenes was proved by comparing with the experimental data collected from the literature. The model provided satisfactory predictions on the behavior of L. monocytogenes in vegetables (>80% agreement with experimental observations). For leafy greens, a 90% agreement was achieved. In contrast, the performance of the Gamma model was less satisfactory for fruits, as it tends to overestimate the potential of acid commodities to inhibit the growth of L. monocytogenes.

Heat resistance of five spoilage microorganisms in a carbonated broth.

Despite their acidic pH, carbonated beverages can be contaminated by spoilage microorganisms. Thermal treatments, before and/or after carbonation, are usually applied to prevent the growth of these microorganisms. However, the impact of CO2 on the heat resistance of spoilage microorganisms has never been studied. A better understanding of the combined impact of CO2 and pH on the heat resistance of spoilage microorganisms commonly found in carbonated beverages might allow to optimize thermal treatment. Five microorganisms were selected for this study: Alicyclobacillus acidoterrestris (spores), Aspergillus niger (spores), Byssochlamys fulva (spores), Saccharomyces cerevisiae (vegetative cells), and Zygosaccharomyces parabailii (vegetative cells). A method was developed to assess the impact of heat treatments in carbonated media on microbial resistance. The heat resistances of the five studied species are coherent with the literature, when data were available. However, neither the dissolved CO2 concentration (from 0 to 7 g/L), nor the pH (from 2.8 to 4.1) have an impact on the heat resistance of the selected microorganisms, except for As. niger, for which the presence of dissolved CO2 reduced the heat resistance. This study improved our knowledge about the heat resistance of some spoilage microorganisms in presence of CO2.

Modeling the Thermal Inactivation of Monascus ruber Ascospores Isolated from Green Olive (Arauco Cultivar) Storage Brine: An Alternative Strategy to Reduce Antifungal Chemical Agents.

Monascus ruber is an important fungus that causes spoilage in table olives, resulting in the darkening of the brine, the softening of the fruit, increased pH, and apparent mycelial growth. This study aimed to evaluate this resistance, providing a model to determine the optimal processing conditions for mitigating fungal contamination and prolonging shelf life without antifungal agents while optimizing pasteurization to reduce energy consumption. The resistance in brine (3.5% NaCl; pH 3.5) from Arauco cultivar green olives imported from Argentina was assessed. Four predictive models (log linear, log linear + shoulder, log linear + tail, log linear + shoulder + tail) estimated kinetic parameters for each survival curve. Log linear + shoulder + tail provided the best fit for 70 °C and 75 °C, with low RMSE (0.171 and 0.112) and high R2 values (0.98 and 0.99), respectively, while the log linear model was used for 80 °C. Decimal reduction times at 70, 75, and 80 °C were 24.8, 5.4, and 1.6 min, respectively, with a z-value of 8.2 °C. The current regulatory processes are insufficient to eliminate M. ruber at requisite levels, considering reduced antifungal agents.

A secondary model for the effect of pH on the variability in growth fitness of Listeria innocua strains.

Variability in microbial growth is a keystone of modern Quantitative Microbiological Risk Assessment (QMRA). However, there are still significant knowledge gaps on how to model variability, with the most common assumption being that variability is constant. This is implemented by an error term (with constant variance) added on top of the secondary growth model (for the square root of the growth rate). However, this may go against microbial ecology principles, where differences in growth fitness among bacterial strains would be more prominent in the vicinity of the growth limits than at optimal growth conditions. This study coins the term "secondary models for variability", evaluating whether they should be considered in QMRA instead of the constant strain variability hypothesis. For this, 21 strains of Listeria innocua were used as case study, estimating their growth rate by the two-fold dilution method at pH between 5 and 10. Estimates of between-strain variability and experimental uncertainty were obtained for each pH using mixed-effects models, showing the lowest variability at optimal growth conditions, increasing towards the growth limits. Nonetheless, the experimental uncertainty also increased towards the extremes, evidencing the need to analyze both sources of variance independently. A secondary model was thus proposed, relating strain variability and pH conditions. Although the modelling approach certainly has some limitations that would need further experimental validation, it is an important step towards improving the description of variability in QMRA, being the first model of this type in the field.

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

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

Chilled Pacu (Piaractus mesopotamicus) fillets: Modeling Pseudomonas spp. and psychrotrophic bacteria growth and monitoring spoilage indicators by 1H NMR and GC-MS during storage.

This study aimed to assess the growth of Pseudomonas spp. and psychrotrophic bacteria in chilled Pacu (Piaractus mesopotamicus), a native South American fish, stored under chilling conditions (0 to 10 °C) through the use of predictive models under isothermal and non-isothermal conditions. Growth kinetic parameters, maximum growth rate (µmax, 1/h), lag time (tLag, h), and (Nmax, Log10 CFU/g) were estimated using the Baranyi and Roberts microbial growth model. Both kinetic parameters, growth rate and lag time, were significantly influenced by temperature (P < 0.05). The square root secondary model was used to describe the bacteria growth as a function of temperature. Secondary models, √µ = 0.016 (T + 10.13) and √µ =0.017 (T + 9.91) presented a linear correlation with R2 values >0.97 and were further validated under non-isothermal conditions. The model's performance was considered acceptable to predict the growth of Pseudomonas spp. and psychrotrophic bacteria in refrigerated Pacu fillets with bias and accuracy factors between 1.24 and 1.49 (fail-safe) and 1.45-1.49, respectively. Fish biomarkers and spoilage indicators were assessed during storage at 0, 4, and 10 °C. Volatile organic compounds, VOCs (1-hexanol, nonanal, octenol, and indicators 2-ethyl-1-hexanol) showed different behavior with storage time (P > 0.05). 1H NMR analysis confirmed increased enzymatic and microbial activity in Pacu fillets stored at 10 °C compared to 0 °C. The developed and validated models obtained in this study can be used as a tool for decision-making on the shelf-life and quality of refrigerated Pacu fillets stored under dynamic conditions from 0 to 10 °C.

Predicting the impact of temperature and relative humidity on Salmonella growth and survival in sliced chard, broccoli and red cabbage.

This study assessed the fate of a Salmonella enterica cocktail (S. Typhimurium, S. Enteritidis, S. Newport, S. Agona and S. Anatum; initial counts 3.5 log CFU/g) in minimally processed sliced chard, broccoli and red cabbage at 16 conditions of different temperature (7, 14, 21 and 37 °C) and relative humidity (RH; 15, 35, 65 and 95%) over six days (144 h). Linear regression was used to estimate the rate change of Salmonella in cut vegetables as a function of temperature and relative humidity (RH). R2 value of 0.85, 0.87, and 0.78 were observed for the rates of change in chard, broccoli, and red cabbage, respectively. The interaction between temperature and RH was significant in all sliced vegetables. Higher temperatures and RH values favored Salmonella growth. As temperature or RH decreased, the rate of S. enterica change varied by vegetable. The models developed here can improve risk management of Salmonella in fresh cut vegetables.

Quantitative microbial risk assessment of Salmonella in fresh chicken patties.

Quantitative microbial risk assessment (QMRA) has witnessed rapid development within the context of food safety in recent years. As a means of contributing to these advancements, a QMRA for Salmonella spp. in fresh chicken patties for the general European Union (EU) population was developed. A two-dimensional (Second Order) Monte-Carlo simulation method was used for separating variability and uncertainty of model's parameters. The stages of industrial processing, retail storage, domestic storage, and cooking in the domestic environment were considered in the exposure assessment. For hazard characterization, a dose-response model was developed by combining 8 published dose-response models using a Pert distribution for describing uncertainty. The QMRA model predicted a mean probability of illness of 1.19*10-4 (5.28*10-5 - 3.57*10-4 95 % C.I.), and a mean annual number of illnesses per 100,000 people of 2.13 (0.96 - 6.59 95 % C.I.). Moreover, sensitivity analysis was performed, and variability in cooking preferences was found to be the most influential model parameter (r = -0.39), followed by dose-response related variability (r = 0.22), and variability in the concentration of Salmonella spp. at the time of introduction at the processing facility (r = 0.11). Various mitigation strategy scenarios were tested, from which, "increasing the internal temperature of cooking" and "decreasing shelf life" were estimated to be the most effective in reducing the predicted risk of illness. Salmonella-related illnesses exhibit particularly high severity, making them some of the most prominent zoonotic diseases in the EU. Regular monitoring of this hazard in order to further highlight its related parameters and causes is a necessary procedure. This study not only provides an updated assessment of Salmonella spp. risk associated with chicken patties, but also facilitates the identification of crucial targets for scientific investigation and implementation of real-world intervention strategies.

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

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

Optimal experimental design (OED) for the growth rate of microbial populations. Are they really more "optimal" than uniform designs?

Secondary growth models from predictive microbiology can describe how the growth rate of microbial populations varies with environmental conditions. Because these models are built based on time and resource consuming experiments, model-based Optimal Experimental Design (OED) can be of interest to reduce the experimental load. In this study, we identify optimal experimental designs for two common models (full Ratkowsky and Cardinal Parameters Model (CPM)) for a different number of experiments (10-30). Calculations are also done fixing one or more model parameters, observing that this decision strongly affects the layout of the OED. Using in silico experiments, we conclude that OEDs are more informative than conventional (equidistant) designs with the same number of experiments. However, OEDs cluster the experiments near the growth limits (Xmin and Xmax) resulting in impractical designs with aggregated experimental runs ~10 times longer than conventional designs. To mitigate this, we propose a novel optimality criterion (i.e., the objective function) that accounts for the aggregated time. The novel criterion provides a reduction in parameter uncertainty with respect to the conventional design, without an increase in the experimental load. These results underline that an OED is only based on information theory (Fisher information), so the results can be impractical when actual experimental limitations are considered. The study also emphasizes that most OED schemes identify where to measure, but do not give an indication on how many experiments should be made. In this sense, numerical simulations can estimate the parameter uncertainty that would be obtained for a particular experimental design (OED or not). These results and methodologies (available in Open Code) can guide the design of future experiments for the development of secondary growth models.

A stochastic approach for modelling the in-vitro effect of osmotic stress on growth dynamics and persistent cell formation in Listeria monocytogenes.

Persistent bacteria (or persisters) can be defined as a microbial subpopulation that, exposed to bactericidal treatment, is killed more slowly than the rest of the population they are part of. They stochastically originate in response to environmental stressors or spontaneously without external signals. When transferred into a fresh medium, persisters can resume active replication although they spend more time adapting to the new conditions remaining in the lag phase longer. They were studied for decades for their ability to survive antibiotic treatments while studies on their formation in food and potential impact on their safety are lacking. The most common food preservation techniques may act as stressors that trigger the formation of persistent bacteria able to survive bactericidal treatments and grow later in foods during storage. This study aimed to investigate a possible relationship between exposure to different salt concentrations (osmotic stress) and the amount of persisters triggered in a strain of Listeria monocytogenes. Furthermore, we described this phenomenon from a mathematical perspective through predictive microbiology models commonly used in the food field. The lag time distribution of a L. monocytogenes ATCC 7644 strain grown in broth with additional 2 %, 4 % and 6 % NaCl was evaluated using the software ScanLag. It uses office scanners to automatically record the colony growth on agar plates and evaluate the frequency distribution of their appearance times (lag phase) by automated image analysis. The same broth cultures were diluted to equalize salt concentration and transferred into a fresh broth to evaluate how the previous salt exposure impacted their growth kinetics. The observed growth curves were reproduced using predictive models in which the mean duration of the lag phase of the whole population took into account the occurrence of persisters with a longer lag phase. The models were solved first using a deterministic approach and then a stochastic one introducing a stochastic term that mimics the variability of lag phase duration due to the persisters occurrence. Results showed that the growth of L. monocytogenes in broth with additional NaCl might trigger the formation of persistent cells whose number increased consistently with salt concentrations. The proposed predictive approach reproduced the observed real curves in strong agreement, especially through the stochastic resolution of the models. Persistence is currently a neglected bacterial defence strategy in the food sector but the persisters' formation during production cannot be excluded; therefore, further insights on the topic are certainly desirable.

Inter-strain variability on the cardinal parameters (pH and Aw) of clinical and food isolates of Listeria monocytogenes using turbidimetric measurements.

Listeria monocytogenes is a foodborne pathogen which, in 2021, was considered the fifth most commonly reported zoonosis in humans in the European Union (EU). Ready-to-eat (RTE) fishery products, deli meats or soft cheeses have been mostly involved in food safety alerts and outbreaks in the last years. Hurdle technology by food industries has been widely used to enhance the safety of foods. Among the barriers, the application of acid and osmotic stress during processing is extensively used worldwide. This study aims to gain knowledge about the inter-strain variability of twenty-six clinical and food L. monocytogenes isolates with the estimation of their cardinal parameters using turbidimetric measurements. To analyse the data and to obtain the estimated cardinal values, a common statistical procedure was set up. The estimation of cardinal parameters showed a high inter-strain variability of L. monocytogenes, and no correlation was observed between Aw min and pHmin values for the studied strains. By grouping the strains in clinical, meat and fish origin, it was observed that strains from the meat group presented the lowest average pHmin values (4.57), thus showing potential acid adaptation. This work contributes to gain knowledge of the inter-strain variability of L. monocytogenes in relation with pH and Aw cardinal values, as well as provide a starting point for future validation studies in fish and meat food matrices.

Quantitative tools in microbial and chemical risk assessment.

The EU-FORA programme 'Quantitative tools in microbial and chemical risk assessment' was dedicated to training on predictive microbiology fundamentals, implementation of different modelling strategies, design of experiments and software tools such as MATLAB, GInaFiT and DMFit. The fellow performed MATLAB training on maximum specific growth rate (µmax) determination according to the Ratkowsky model. GInaFiT training on different models for bacterial inactivation and DMFit training on growth parameters of Vibrio parahaemolyticus were also carried out. Optical density measurements of V. parahaemolyticus bacterial cultures were performed. The obtained kinetics of optical density measurements were used to estimate µmax. Hereafter, Minimum inhibitory concentrations and non-inhibitory concentrations of aminoglycoside antibiotics were estimated based on the quantification of the fractional areas of the optical density vs time. It can be concluded that the results of the quantitative characterisation of V. parahaemolyticus are reliable and can be used for exposure assessments. Also, the turbidimetric assay can be applied for successful estimation of minimum inhibitory concentrations and non-inhibitory concentrations.

Salmonella and Salmonellosis: An Update on Public Health Implications and Control Strategies.

Salmonellosis is globally recognized as one of the leading causes of acute human bacterial gastroenteritis resulting from the consumption of animal-derived products, particularly those derived from the poultry and pig industry. Salmonella spp. is generally associated with self-limiting gastrointestinal symptoms, lasting between 2 and 7 days, which can vary from mild to severe. The bacteria can also spread in the bloodstream, causing sepsis and requiring effective antimicrobial therapy; however, sepsis rarely occurs. Salmonellosis control strategies are based on two fundamental aspects: (a) the reduction of prevalence levels in animals by means of health, biosecurity, or food strategies and (b) protection against infection in humans. At the food chain level, the prevention of salmonellosis requires a comprehensive approach at farm, manufacturing, distribution, and consumer levels. Proper handling of food, avoiding cross-contamination, and thorough cooking can reduce the risk and ensure the safety of food. Efforts to reduce transmission of Salmonella by food and other routes must be implemented using a One Health approach. Therefore, in this review we provide an update on Salmonella, one of the main zoonotic pathogens, emphasizing its relationship with animal and public health. We carry out a review on different topics about Salmonella and salmonellosis, with a special emphasis on epidemiology and public health, microbial behavior along the food chain, predictive microbiology principles, antimicrobial resistance, and control strategies.

Unveiling Fresh-Cut Lettuce Processing in Argentine Industries: Evaluating Salmonella Levels Using Predictive Microbiology Models.

A survey was performed to gather information on the processing steps, conditions, and practices employed by industries processing ready-to-eat (RTE) leafy vegetables in Argentina. A total of seven industries participated in the survey. A cluster analysis of the data obtained was performed to identify homogeneous groups among the participating industries. The data collected were used as inputs of two predictive microbiology models to estimate Salmonella concentrations after chlorine washing, during storage and distribution of final products, and to rank the different practices according to the final estimated Salmonella levels. Six different clusters were identified by evaluating the parameters, methods, and controls applied in each processing step, evidencing a great variability among industries. The disinfectant agent applied by all participating industries was sodium hypochlorite, though concentrations and application times differed among industries from 50 to 200 ppm for 30 to 110 s. Simulations using predictive models indicated that the reductions in Salmonella in RTE leafy vegetables would vary in the range of 1.70-2.95 log CFU/g during chlorine-washing depending on chlorine concentrations applied, washing times, and vegetable cutting size, which varied from 9 to 16 cm2 among industries. Moreover, Salmonella would be able to grow in RTE leafy vegetables during storage and distribution, achieving levels of up to 2 log CFU/g, considering the storage and transportation temperatures and times reported by the industries, which vary from 4 to 14 °C and from 18 to 30 h. These results could be used to prioritize risk-based sampling programs by Food Official Control or determine more adequate process parameters to mitigate Salmonella in RTE leafy vegetables. Additionally, the information gathered in this study is useful for microbiological risk assessments.

Disentangling the contributions of initial heterogeneities and dynamic stress adaptation to nonlinearities in bacterial survival curves.

The deviations from log-linearity that are often observed in bacterial survivor curves can be explained using different arguments, both biological and experimental. In this study, we used Bacillus subtilis as a model organism to demonstrate that the generally accepted vitalistic arguments (initial heterogeneities in the stress resistance of the cells in the population) may fail to describe microbial inactivation in some situations. In this sense, we showed how dynamic stress acclimation during an isothermal treatment provides an alternative explanation for survivor curves with an upwards curvature. We also provided an innovative experimental approach based on preadaptation experiments to evaluate which hypothesis is more suitable for the bacterial response. Furthermore, we used our experimental results to define bounds for the possible stress acclimation that may take place during dynamic treatments, concluding that the magnitude of stress acclimation may be larger for dynamic treatments than for isothermal experiments. We also evaluated the contribution of the SigB general stress response system to heat resistance by comparing the heat survival of wt and the ΔsigB mutant. Both strains survived better in 51, 52.5 and 55 °C when cells were pre-adapted at 48 °C than non-pre-adapted cells. However, ΔsigB was less resistant to heat than wt due to the missing SigB general stress system. Although these conclusions were based on B. subtilis as a model organism, this study can be the first step towards the development of a novel methodology able to estimate dynamic effects using only isothermal experiments. This would improve the models developed within the predictive microbiology community, improving our ability to predict microbial inactivation during industrial treatments, which are most often dynamic.

Modeling naturally-occurring Vibrio parahaemolyticus in post-harvest raw shrimps.

There is little known about the growth and survival of naturally-occurring Vibrio parahaemolyticus in harvested raw shrimps. In this study, the fate of naturally-occurring V. parahaemolyticus in post-harvest raw shrimps was investigated from 4℃ to 30℃ using real-time PCR combined with propidium monoazide (PMA-qPCR). The Baranyi-model was used to fit the growth and survival data. A square root model and non-linear Arrhenius model was then used to quantify the parameters derived from the Baranyi-model. The results showed that naturally-occurring V. parahaemolyticus were slowly inactivated at 4℃ and 7℃ with deactivation rates of 0.019 Log CFU/g/h and 0.025 Log CFU/g/h. Conversely, at 15, 20, 25, and 30 °C, the average maximum growth rates (µmax) of naturally-occurring V. parahaemolyticus were determined to be 0.044, 0.105, 0.179 and 0.336 Log CFU/g/h, accompanied by the average lag phases (λ) of 15.5 h, 7.3 h, 4.4 h and 3.7 h. The validation metrics, Af and Bf, for both the square root model and non-linear, indicating that the model had a good ability to predict the growth behavior of naturally-occurring V. parahaemolyticus in post-harvest raw shrimps. Furthermore, a comparative exploration between the growth of artificially contaminated V. parahaemolyticus in cooked shrimps and naturally-occurring V. parahaemolyticus in post-harvest raw shrimps revealed intriguing insights. While no substantial distinction in deactivation rates emerged at 4 °C and 7 °C (P > 0.05), a discernible disparity in growth rates was observable at 15 °C, 20 °C, 25 °C, and 30 °C, with the former surpassing the latter. Which indicated the risk of V. parahaemolyticus using models derived from cooked shrimps may be biased. Our study also unveiled a discernible seasonal effect. The µmax and λ of V. parahaemolyticus in shrimps harvested in summer were similar to those harvested in autumn, while the initial and maximum bacterial concentration harvested in summer were higher than those harvested in autumn. This predictive microbiology model of naturally-occurring V. parahaemolyticus in raw shrimps provides relevance to modelling growth in situ.

Assessing Listeria monocytogenes growth kinetics in rice pudding at different storage temperatures.

Rice pudding is a popular artisanal dairy dessert highly consumed in the main rice-producing countries, including Egypt. This study aimed to evaluate and model the growth of Listeria monocytogenes in rice pudding dessert stored at different temperatures (4-25 °C) over its shelf-life. Lab-scale rice pudding samples were prepared following a traditional Egyptian recipe and inoculated with a three-strain cocktail of L. monocytogenes (ca. 3 × 102 cfu/g). Inoculated rice pudding samples (pH = 6.67 ± 0.06 and aw = 0.99 ± 0.002) were stored at different isothermal conditions (4, 8, 12, 18, and 25 °C) and microbiologically analysed for up to 30 days for pathogen quantification by plate count methodology. Global regression analysis was used to fit the Baranyi model coupled with the Ratkowsky model to growth data, relating L. monocytogenes concentrations (N, log cfu/g) with storage temperature (°C) and times (d). Model validation was performed using published independent data. L. monocytogenes growth potential increased by increasing storage temperature. The estimated Ratkowsky model parameters were b = 0.0819 ± 0.0017 log cfu/d·°C and Tmin = -3.28 ± 0.20 °C. The indices RMSE = 0.39 and R2adj = 0.97 indicated a good agreement between the experimental data and the model predictions. The estimated maximum growth rate (µmax) values ranged between 0.355 and 5.363 log cfu/d from 4 to 25 °C. The model was successfully validated using published L. monocytogenes Scott A and California strains growth data in rice pudding samples stored at 5, 12 and 22 °C, as evidenced by the assessed statistical indices. The predictive model developed and validated in this study will aid in decision-making regarding the microbiological safety of rice pudding dessert with respect to L. monocytogenes growth, considering a wide range of storage temperatures.

Ambient temperature, refrigerator food load, and door openings effect on a preservation performance indicator based on chicken temperature data and predictive microbiology.

Home preservation depends on the food matrix, refrigerator design/technology, consumer actions, and ambient temperature. Storing different food matrices in product-relevant refrigerator locations generating different temperature histories can be used to develop an indicator of how refrigerator technology, consumer habits, and environment conditions impact the refrigerator food preservation performance. In this study, poultry, particularly prone to spoilage reflecting its pH, nutrient availability, and high aw, was used to evaluate refrigerator preservation performance as affected by compressor technology (single [SS] and variable speed [VS]), ambient temperature (21.1°C [LT] and 32.2°C [HT]), and refrigerator load (22.5 kg [RL] and 39 kg [HL]). Time-temperature values collected for chicken breast stored in a drawer independently controlled at 0°C in a refrigerator set 5°C, and a Pseudomonas predictive microbiology model, were used to estimate a normalized refrigerator performance indicator (RPI). Values <1, ∼1, and >1 described excellent, good, or poor performance, respectively. A first analysis revealed that up to 54% of chicken breast temperatures were above its recommended refrigerated storage value. When ignoring variability sources, SS technology yielded RPI values ranging 0.61-0.70, whereas the more energy efficient VS compressor yielded values ranging 0.86-1.14. The higher and wider VS RPI range reflects a compressor control logic optimized for energy efficiency compliance while disregarding effects on food preservation. When considering the variability of model parameters and temperature measurements through one-sided 95% confidence intervals yielded RPI reaching 1.16. Although the independently controlled drawer preservation performance was near optimal, it can improve by considering energy use and preservation impact when optimizing the compressor speed control protocol. PRACTICAL APPLICATION: Worldwide poultry meat consumption has reached 15 kg per person. Refrigeration is widely used for its safety and quality preservation. Efficiency regulations decreased the energy use of residential refrigerators by nearly tenfold even though their size increased by 50% in the last half century. In this study, we provide quantitative evidence that their preservation performance must be improved. This is particularly true for upper end units typically equipped with quieter and more energy-efficient variable speed compressors. The same methodology can be used to evaluate the preservation performance of the storage units, trucks, and display cases used for refrigerated products.