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This study established microbial growth models for fresh-cut cucumber packaged with different O2 transmission rate (OTR) films. Biaxially oriented polyamide/low-density polyethylene (BOPA/LDPE) film (Ⅰ: OTR5, Ⅳ: OTR48) and polyethylene (PE) film (Ⅱ: OTR2058, Ⅲ: OTR3875) were used to construct a passive modified atmosphere packaging (MAP). Mathematic models have been established to account for dynamic variations in the O2/CO2 concentration and their impacts on Pseudomonas fluorescens growth. The coupling models included: 1) respiration models of cucumber and P. fluorescens based on Michaëlis-Menten equation, 2) coupling gas exchange models based on Fick's law that contained models of P. fluorescens growth and respiration, 3) coupling microbial growth models contained respiration and gas exchange models. Coupling model with Baranyi function successfully fitted variations of O2/CO2 concentration and P. fluorescens growth in the two packaging. In addition, quality properties of packed fresh-cut cucumber were determined. The film Ⅳ (OTR48) as a high barrier film showed the highest inhibition of P. fluorescens growth, adequately retained its colour, firmness and total soluble solid (TSS) concentration in contrast to the PE films packaging. The constructed coupling models can be utilized for assessing the shelf life and microbial growth of fresh-cut vegetables with spoilage dominated by pseudomonads.

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We developed a predictive growth model of Yersinia enterocolitica for fresh Kimchi cabbages as a function of storage temperature (5-20 °C). The Baranyi equation used for primary modeling at these storage temperatures was suitable as a model for obtaining lag time (LT) and specific growth rate (SGR) (R2 = 0.97-0.98). As the temperature increased, the growth of Y. enterocolitica tended to increase, with SGR values of 0.33, 0.40, 0.60 and 0.68 log colony-forming units/h at 8, 11, and 15 °C, and LT values of 5.63, 3.54, 2.23 and 1.09 h, respectively. The secondary model was determined by the non-linear regression analysis. The suitability of the modeling results for the SGR and LT value was verified by determining the mean square error (<0.01), bias factor (0.919-0.999), and accuracy factor (1.032-1.136). The predicted models can be used to predict the growth of Y. enterocolitica in Kimchi cabbage at various temperatures and as an effective tool for maintaining the safe level of Y. enterocolitica in the production, processing, and distribution of fresh agricultural products.

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Isothermal microcalorimetry can provide a general analytical tool for the characterization of bacterial growth. Methodologies and equipment have been studied to expand the application and disseminate the use of the technique. The MCDSC is a microcalorimeter capable of measuring in the range of 0.2 µW that can operate at a temperature range of -20 to 140 °C or under isothermal conditions. Here, we present the first investigation of MCDSC for E. coli growth with the Baranyi and Roberts modeling application. This study presented the calorimetric E. coli fingerprint at MCDSC and compares it with the plate count technique, giving the data more biological meaning. The calorimeter was able to accurately detect growth metabolism and discriminate E. coli at different inoculum densities. Additionally, the MCDSC can offer a new point of view for evaluating microbial growth, such as the significant reduction in error due to dispersed data by the viable counting method.

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The growth kinetics for the total viable count (TVC) in sausages with modified hog casings (treated by surfactant solutions and slush salt with lactic acid), natural hog casings and sheep casings as a function of the storage time (up to 50 days) were studied for the first time. The growth of TVC was fitted by the Baranyi model, and the maximum specific growth rate, lag time and initial and final cell populations were estimated via DMFit. The coefficient of determination of the Baranyi model reached 0.94, 0.77 and 0.86 for sausages stuffed in modified hog casings (MHC), control hog casings (CHC) and natural sheep casings (NSC), respectively. The experimental data for the initial populations were 4.69 ± 0.10 log cfu/g for MHC, 4.79 ± 0.10 log cfu/g for CHC and 3.74 ± 0.14 log cfu/g for NSC, whilst the predicted initial cell populations for MHC, CHC and NSC were 4.81 ± 0.20 log cfu/g, 5.19 ± 0.53 log cfu/g and 3.74 ± 0.54 log cfu/g, respectively. Their shelf lives can also be predicted. The results show that the average pH value of MHC samples (6.96 ± 0.01) was significantly lower than that of CHC (7.09 ± 0.01) and NSC (7.05 ± 0.02) samples at day 50 (p < 0.05). Sausages with CHC possessed a significant higher water holding capacity (99.48 ± 0.14%) at d 29 than those with MHC (97.40 ± 0.46%) and NSC (98.55 ± 0.17%) (p < 0.05). On the last day, the average moisture content for samples with NSC (38.30 ± 3.23%) was significantly higher than that for those with MHC (29.38 ± 2.52%) and CHC (29.15 ± 1.16%) (p < 0.05).

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The effect of ultrasound treatment (100 W, 30 kHz; 50 and 100% amplitudes) on inactivation of Saccharomyces cerevisiae and Byssochlamys fulva in pomegranate juice and shelf life of the juice during storage at different temperatures (5, 15 and 30 °C) for 30 days was modeled using predictive and thermodynamics models. The Baranyi and square root type models were implemented to determine the growth rate of microorganisms. It was predicted that the minimum growth temperature (Tmin) of B. fulva increased by increasing sonication amplitude, however, the Tmin of S. cerevisiae was not function of sonication amplitude. The predicted shelf life was shown to be in good agreement with the measured sensorial shelf life. Increasing the temperature from 5 to 35 °C, reduced the shelf life from 17.5 to 3.5 days for B. fulva and from 15 to 5 days for S. cerevisiae. Moreover, for B. fulva, the activation energy (Ea) decreased from 43.4 to 27.5 kJ/mol by increasing the amplitude, while no significant change was observed for S. cerevisiae. Besides, thermodynamics properties of the shelf life such as enthalpy (ΔH++), entropy (ΔS++) and Gibbs free energy (ΔG++)  were proven to be suitable measures to determine the microbial spoilage reaction.

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This study was performed to develop and validate a predictive growth model of pathogenic Escherichia coli to ensure the safety of fresh-cut produce. Samples were inoculated with a cocktail of seven E. coli strains of five pathotypes (EHEC, Enterohemorrhagic E. coli; ETEC, Enterotoxigenic E. coli; EPEC, Enteropathogenic E. coli; EIEC, Enteroinvasive E. coli, and EAEC, Enteroaggregative E. coli) and stored at 4, 10, 12, 15, 25, 30, and 37°C. Growth of pathogenic E. coli was observed above 12°C. The primary growth model for pathogenic E. coli in fresh-cut produce was developed based on the Baranyi model. The secondary model was developed as a function of temperature for lag phase duration (LPD) and maximum specific growth rate (µmax) based on the polynomial second-order model. The primary and secondary models for pathogenic E. coli were fitted with a high degree of goodness of fit (R2 ≥ 0.99). The bias factor (Bf), accuracy factor (Af), and root mean square error (RMSE) were 0.995, 1.011, and 0.084, respectively. The growth model we developed can provide useful data for assessing the quantitative microbial risk of pathogenic E. coli in fresh-cut produce intended for human consumption. In addition, it is thought to be widely available in industries that produce, process, distribute, and sell fresh-cut produce.

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Morels are gourmet wild edible mushrooms that can grow on several substrates with significant growth rate variations. Such variations have hindered the development of a standardized culture media to promote morel's sustainable production. The aim of this study is developing a novel culture media that takes advantage of coconut water as a complementary component of culture media. Coconut water has been extensively used as a growth-promoting component for plant tissue cultures; however, its application as component of fungi cultivation medium has not been fully developed. This study confirms that coconut water can be efficiently used as culture media component for morels using a kinetic characterization. Morchella sp. kinetic growth is evaluated in different cultures: agar, malt extract agar (MEA), lactose, coconut water (15%) and combinations of them. Kinetic growth parameters (lag phase, λ and maximum specific growth rate, µmax) are estimated using primary modeling methods. Among the selected models, the best fit is achieved using Baranyi's model. A significant increase from 15.8% to 43.4% of the µmax values was observed when culture media (agar, lactose, MEA) is supplemented with coconut water. The largest values of µmax are obtained in MEA-coconut cultures (21.13 ± 0.43-22.57 ± 0.35). Micro-sclerotia and late sclerotia are observed in all cultures containing coconut water justifying the development of a feasible and cost-effective way of culturing morels. The results demonstrate that coconut water can be used for formulation of standard media for morel cultivation leading to a cheap alternative to produce dense mycelium and promote sclerotia formation.

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Campylobacter jejuni and Campylobacter coli continue to be the leading cause of zoonotic gastroenteritis in the European Union, making reliable detection in food important. Low storage temperatures and atmospheric oxygen concentrations during food production can cause sub-lethal damage or transient non-culturability which is why ISO 10272-1:2017 includes an enrichment step to repair cell damage and increase cell concentrations, thereby supporting detection of campylobacters from foods. The aim of this study was to assess the variability in lag-duration of C. jejuni and C. coli during enrichment after different food-relevant stress treatments and evaluate its impact on growth kinetics and reliability of detection outcomes. Therefore, 13 C. jejuni and 10 C. coli strains were subjected to cold stress during refrigerated and frozen storage. Refrigerated storage did not significantly reduce culturability, but frozen storage reduced cell concentrations by 1.6 ± 0.1 log10cfu/ml for both species. Subsequently, cells were enriched following ISO 10272-1:2017-A and cell concentrations were determined over time and lag-duration and growth rate were determined by fitting the Baranyi-model. Without prior stress treatment, mean lag-duration for C. jejuni and C. coli was 2.5 ± 0.2 h and 2.2 ± 0.3 h, respectively. Refrigerated storage increased lag-duration for C. jejuni to 4.6 ± 0.4 h and for C. coli to 5.0 ± 0.4 h and frozen storage increased lag-duration to 5.0 ± 0.3 h and 6.1 ± 0.4 h for C. jejuni and C. coli, respectively. Comparison of strain- and biological variability showed that differences in recovery after cold stress can be attributed mainly to strain variability since strain variability after refrigeration and freeze stress increased respectively 3-fold and 4-fold while biological variability remained constant. A subset of strains was also subjected to oxidative stress that reduced cell concentrations by 0.7 ± 0.2 log10 cfu/ml and comparison of recovery patterns after oxidative and freeze stress indicated that recovery behaviour was also dependent on the stress applied. A scenario analysis was conducted to evaluate the impact of heterogeneity in outgrowth kinetics of single cells on the reliability of detection outcomes following ISO protocol 10272-1:2017. This revealed that a 'worst-case'-scenario for successful detection by a combination of the longest lag-duration of 7.6 h and lowest growth rate of 0.47 h-1 still resulted in positive detection outcomes since the detection limit was reached within 32.5 h. This suggests that other factors such as competitive microbiota can act as a causative factor in false-negative outcomes of tested food samples.

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Listeria monocytogenes is a hardy psychrotrophic pathogen that has been linked to several cheese-related outbreaks in the United States, including a recent outbreak in which a fresh cheese (queso fresco) was implicated. The purpose of this study was to develop primary, secondary, and tertiary predictive models for the growth of L. monocytogenes in queso fresco and to validate these models using nonisothermal time and temperature profiles. A mixture of five strains of L. monocytogenes was used to inoculate pasteurized whole milk to prepare queso fresco. Ten grams of each fresh cheese sample was vacuum packaged and stored at 4, 10, 15, 20, 25, and 30°C. From samples at each storage temperature, subsamples were removed at various times and diluted in 0.1% peptone water, and bacteria were enumerated on Listeria selective agar. Growth data from each temperature were fitted using the Baranyi model as the primary model and the Ratkowsky model as the secondary model. Models were then validated using nonisothermal conditions. The Baranyi model was fitted to the isothermal growth data with acceptable goodness of fit statistics (R2 = 0.928; root mean square error = 0.317). The Ratkowsky square root model was fitted to the specific growth rates at different temperatures (R2 = 0.975). The tertiary model developed from these models was validated using the growth data with two nonisothermal time and temperature profiles (4 to 20°C for 19 days and 15 to 30°C for 11 days). Data for these two profiles were compared with the model prediction using an acceptable prediction zone analysis; >70% of the growth observations were within the acceptable prediction zone (between -1.0 and 0.5 log CFU/g). The model developed in this study will be useful for estimating the growth of L. monocytogenes in queso fresco. These predictions will help in estimation of the risk of listeriosis from queso fresco under extended storage and temperature abuse conditions.

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Egg products are widely consumed in Korea and continue to be associated with risks of Staphylococcus aureus-induced food poisoning. This prompted the development of predictive mathematical models to understand growth kinetics of S. aureus in egg products in order to improve the production of domestic food items. Egg products were inoculated with S. aureus and observe S. aureus growth. The growth kinetics of S. aureus was used to calculate lag-phase duration (LPD) and maximum specific growth rate (µmax) using Baranyi model as the primary growth model. The secondary models provided predicted values for the temperature changes and were created using the polynomial equation for LPD and a square root model for µmax. In addition, root mean square errors (RMSE) were analyzed to evaluate the suitability of the mathematical models. The developed models demonstrated 0.16-0.27 RMSE, suggesting that models properly represented the actual growth of S. aureus in egg products.

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A model was developed to predict the growth of Bacillus cereus from spores during cooling of cooked pasta. Cooked pasta was inoculated with a cocktail of four strains of heat-shocked (80 °C/10 min) B. cereus spores to obtain a final spore concentration of approximately 2 log CFU/g. Thereafter, growth was determined at isothermal temperatures starting at 10 °C and every three degrees up to 49 °C. Samples were removed periodically and plated on mannitol egg yolk polymyxin agar. The plates were incubated for 24 hr at 30 °C. Baranyi, Huang, and modified Gompertz primary growth models were used to fit growth data. The modified Ratkowsky secondary model was used to fit growth rates determined by the primary growth models with respect to temperature. All three primary models fitted the growth data well. The modified Ratkowsky secondary model adequately fit growth rates generated by the three primary models (R2 values ranging from 0.96 to 0.98). After acceptable prediction zone (APZ) validation and goodness of fit statistical analyses, it was determined that the Baranyi primary growth model was best suited for these data. For both single-rate exponential cooling and biphasic linear cooling model validation, all Baranyi model predictions (n = 24 and 28, respectively) fell within the APZ (-1.0 to 0.5 log CFU/g). The model will assist institutional food service settings to determine the safety of cooked pasta subjected to longer cooling times or stored at improper temperatures. PRACTICAL APPLICATION: Predictive model can be used to estimate extent of microbial growth during cooling of cooked pasta and in designing HACCP program and setting of critical control levels. Retail food industry would need fewer challenge studies to validate the safety of their products. The model will provide regulatory agencies and food industry with an objective means of assessing the microbial risk and ensuring that the public is not at risk of acquiring food poisoning.

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Bacillus cereus is frequently implicated in foodborne outbreaks associated with the consumption of cooked rice. The main contributing factors leading to outbreaks is rice cooked in large quantities and subsequently, inadequately chilled or stored at room temperatures for a prolonged period of time prior to consumption. Bacillus cereus growth in cooked rice inoculated with approximately 2 log CFU/g of heat-shocked (80 °C/10 min) spores at several isothermal conditions (between 10 and 49 °C) was quantified. B. cereus populations were determined by plating on mannitol egg yolk polymyxin agar and incubating at 30 °C for 24 h. Primary growth models, namely Baranyi, Huang, modified Gompertz, and logistic models were fitted to growth data. Specific growth rates from all four primary models were used to fit the modified Ratkowsky square-root model with respect to temperature. All four primary models were well fitted by the modified Ratkowsky model (R2 values from 0.90-0.99). Based on the goodness of fit secondary model statistics (R2, SSE, RMSE), the Baranyi model performed the best and was chosen for tertiary modeling. Acceptable prediction zone (APZ) analysis was performed for validation of the Baranyi model predictions during single rate exponential and biphasic linear cooling temperature profiles. For single rate cooling, 23 of the 24 predictions fell within the APZ (-1.0 to 0.5 log CFU/g). For biphasic linear cooling, 26 of the 28 predictions fell within the APZ. The developed dynamic model can be used to predict potential B. cereus growth from spores in cooked rice during chilling and thus, support the disposition of product subject to cooling deviations.

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Cut produce continues to constitute a significant portion of the fresh fruit and vegetables sold directly to consumers. As such, the safety of these items during storage, handling, and display remains a concern. Cut tomatoes, cut leafy greens, and cut melons, which have been studied in relation to their ability to support pathogen growth, have been specifically identified as needing temperature control for safety. Data are needed on the growth behavior of foodborne pathogens in other types of cut produce items that are commonly offered for retail purchase and are potentially held without temperature control. This study assessed the survival and growth of Listeria monocytogenes in cut produce items that are commonly offered for retail purchase, specifically broccoli, green and red bell peppers, yellow onions, canned green and black olives, fresh green olives, cantaloupe flesh and rind, avocado pulp, cucumbers, and button mushrooms. The survival of L. monocytogenes strains representing serotypes 1/2a, 1/2b, and 4b was determined on the cut produce items for each strain individually at 5, 10, and 25°C for up to 720 h. The modified Baranyi model was used to determine the growth kinetics (the maximum growth rates and maximum population increases) in the L. monocytogenes populations. The products that supported the most rapid growth of L. monocytogenes, considering the fastest growth and resulting population levels, were cantaloupe flesh and avocado pulp. When stored at 25°C, the maximum growth rates for these products were 0.093 to 0.138 log CFU/g/h and 0.130 to 0.193 log CFU/g/h, respectively, depending on the strain. Green olives and broccoli did not support growth at any temperature. These results can be used to inform discussions surrounding whether specific time and temperature storage conditions should be recommended for additional cut produce items.

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Haloarchaea are salt-loving halophilic microorganisms that inhabit marine environments, sea water, salterns, and lakes. The resistance of haloarchaea to physical extremities that challenge organismic survival is ubiquitous. Metal and antibiotic resistance of haloarchaea has been on an upsurge due to the exposure of these organisms to metal sinks and drug resistance genes augmented in their natural habitats due to anthropogenic activities and environmental pollution. The efficacy of silver nanoparticles (SNPs) as a potent and broad spectrum inhibitory agent is known, however, there are no reports on the inhibitory activity of SNPs against haloarchaea. In the present study, we have investigated the antimicrobial potentials of SNPs synthesized using aqueous leaf extract of Cinnamomum tamala against antibiotic resistant haloarchaeal isolates Haloferax prahovense RR8, Haloferax lucentense RR15, Haloarcula argentinensis RR10 and Haloarcula tradensis RR13. The synthesized SNPs were characterized by UV-Vis spectroscopy, scanning electron microscopy, energy dispersive X-ray spectroscopy, dynamic light scattering, X-ray diffraction and Fourier transform infrared spectroscopy. The SNPs demonstrated potent antimicrobial activity against the haloarchaea with a minimum inhibitory concentration of 300-400 µg/ml. Growth kinetics of haloarchaea in the presence of SNPs was studied by employing the Baranyi mathematical model for microbial growth using the DMFit curve fitting program. The C. tamala SNPs also demonstrated cytotoxic activity against human lung adenocarcinoma epithelial cell line (A540) and human breast adenocarcinoma cell line (MCF-7). The mechanism of inhibition of haloarchaea by the SNPs was investigated. The plausible mechanism proposed is the alterations and disruption of haloarchaeal membrane permeability by turbulence, inhibition of respiratory dehydrogenases and lipid peroxidation causing cellular and DNA damage resulting in cell death.

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AIMS: To gain an understanding of the growth kinetics of Staphylococcus aureus to ensure the safety of pork, and to develop a predictive growth model of Staph. aureus in raw pork, ham and sausage pork under specific storage time and temperature conditions. METHODS AND RESULTS: Growth of Staph. aureus was evaluated at 5-40°C using 5-6 replicates in each sampling time in order to capture experimental variability. Growth curves were fit to Baranyi model to estimate Lag time (λ) and maximum growth rate (µmax). The effect of temperature on λ and µmax was modelled using natural logarithm of λ and square root of µmax. The variability between repetitions was higher at 15, 20 and 40°C than observed at 25, 30 and 35°C. After only 3 and 2 days of storage at 5 and 10°C, respectively, Staph. aureus populations decreased to limit of detection (≤1 log CFU g(-1) ). Staphylococcus aureus populations on ham presented higher µmax in comparison to those grown on raw pork and sausage. Linear regression lines showed that Staph. aureus populations in ham grew faster than those observed in sausage and raw pork. Staph. aureus presented a theoretical minimum growth temperature (Tmin ) depending on the processed pork products, which were different from in raw pork. CONCLUSION: Staphylococcus aureus model predicts faster growth in ham compared to raw pork and sausage. The validation of models showed good predictions, suggesting that the developed models are useful in estimating growth kinetics of Staph. aureus in different pork products. SIGNIFICANCE AND IMPACT OF THIS STUDY: Established here is a data-driven, in silico model on Staph. aureus growth kinetics on different pork products. The model is extensively validated by experiments and simulations and further supported by comparisons to previous modelling efforts in other species.

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The purpose of this study was to develop predictive models for the growth of Listeria monocytogenes in pork Bulgogi at various storage temperatures. A two-strain mixture of L. monocytogenes (ATCC 15313 and isolated from pork Bulgogi) was inoculated on pork Bulgogi at 3 Log CFU/g. L. monocytogenes strains were enumerated using general plating method on Listeria selective medium. The inoculated samples were stored at 5, 15, and 25℃ for primary models. Primary models were developed using the Baranyi model equations, and the maximum specific growth rate was shown to be dependent on storage temperature. A secondary model of growth rate as a function of storage temperature was also developed. As the storage temperature increased, the lag time (LT) values decreased dramatically and the specific growth rate of L. monocytogenes increased. The mathematically predicted growth parameters were evaluated based on the modified bias factor (B f ), accuracy factor (A f ), root mean square error (RMSE), coefficient of determination (R (2)), and relative errors (RE). These values indicated that the developed models were reliably able to predict the growth of L. monocytogenes in pork Bulgogi. Hence, the predictive models may be used to assess microbiological hygiene in the meat supply chain as a function of storage temperature.