Modeling the Growth of Six Listeria monocytogenes Strains in Smoked Salmon Pâté.

In this study, the growth of six L. monocytogenes strains isolated from different fish products was quantified and modeled in smoked salmon pâté at a temperature ranging from 2 to 20 °C. The experimental data obtained for each strain was fitted to the primary growth model of Baranyi and Roberts to estimate the following kinetic parameters: lag phase (λ), maximum specific growth rate (µmax), and maximum cell density (Nmax). Then, the effect of storage temperature on the obtained µmax values was modeled by the Ratkowsky secondary model. In general, the six L. monocytogenes strains showed rapid growth in salmon pâté at all storage temperatures, with a relatively short lag phase λ, even at 2 °C. The growth behavior among the tested strains was similar at the same storage temperature, although significant differences were found for the parameters λ and µmax. Besides, the growth variations among the strains did not follow a regular pattern. The estimated secondary model parameter Tmin ranged from -4.25 to -3.19 °C. This study provides accurate predictive models for the growth of L. monocytogenes in fish pâtés that can be used in shelf life and microbial risk assessment studies. In addition, the models generated in this work can be implemented in predictive modeling tools and repositories that can be reliably and easily used by the fish industry and end-users to establish measures aimed at controlling the growth of L. monocytogenes in fish-based pâtés.

Comparison of modelling approaches for the prediction of kinetic growth parameters of Pseudomonas spp. in oyster mushroom (Pleurotus ostreatus).

In predictive microbiology, primary and secondary models can be used to predict microbial growth, usually in a two-step modelling approach. The inverse dynamic modelling approach is an alternative method to direct modelling methods, in which the primary and secondary models are fitted simultaneously from non-isothermal data, minimising experimental effort and costs. Thus, the main aim of the present study was to compare the prediction capabilities of the mathematical modelling approaches used for calculating growth kinetics of microorganisms in predictive food microbiology field. For this purpose, the bacterial growth data of Pseudomonas spp. in oyster mushroom (Pleurotus ostreatus) subjected to isothermal and non-isothermal storage temperatures were collected from previously published growth curves. Temperature-dependent kinetic growth parameters (maximum specific growth rate 'µmax' and lag phase duration 'λ') were described as a function of storage temperature using the direct two-step, direct one-step and inverse dynamic modelling approach based on Baranyi and Huang models. The fitting capability of the modelling approaches was separately compared, and the one-step modelling approach for the direct methods provided better goodness of fit results regardless of used primary models, which leads the Huang model with being RMSE = 0.226 and R2adj = 0.949 became best for direct methods. Like seen in direct methods, the Huang model gave better goodness of fit results than Baranyi model for inverse method. Results revealed there was no significant difference (p > 0.05) between the growth kinetic parameters obtained from direct one-step modelling approach and inverse modelling approaches based on the Huang model. Satisfactorily statistical indexes show that the inverse dynamic modelling approach can be reliably used as an alternative way of describing the growth behaviour of Pseudomonas spp. in oyster mushroom in a fast and minimum labour effort.

A new expanded modelling approach for investigating the bioprotective capacity of Latilactobacillus sakei CTC494 against Listeria monocytogenes in ready-to-eat fish products.

Understanding the role of food-related factors on the efficacy of protective cultures is essential to attain optimal results for developing biopreservation-based strategies. The aim of this work was to assess and model growth of Latilactobacillus sakei CTC494 and Listeria monocytogenes CTC1034, and their interaction, in two different ready-to-eat fish products (i.e., surimi-based product and tuna pâté) at 2 and 12 °C. The existing expanded Jameson-effect and a new expanded Jameson-effect model proposed in this study were evaluated to quantitatively describe the effect of microbial interaction. The inhibiting effect of the selected lactic acid bacteria strain on the pathogen growth was product dependent. In surimi product, a reduction of lag time of both strains was observed when growing in coculture at 2 °C, followed by the inhibition of the pathogen when the bioprotective L. sakei CTC494 reached the maximum population density, suggesting a mutualism-antagonism continuum phenomenon between populations. In tuna pâté, L. sakei CTC494 exerted a strong inhibition of L. monocytogenes at 2 °C (<0.5 log increase) and limited the growth at 12 °C (<2 log increase). The goodness-of-fit indexes indicated that the new expanded Jameson-effect model performed better and appropriately described the different competition patterns observed in the tested fish products. The proposed expanded competition model allowed for description of not only antagonistic but also mutualism-based interactions based on their influence on lag time.

Evaluation of the effect of Lactobacillus sakei strain L115 on Listeria monocytogenes at different conditions of temperature by using predictive interaction models.

In this study, the inhibitory capacity of Lactobacillus sakei strain L115 against Listeria monocytogenes has been assayed at 4, 8, 11, 15 and 20 °C in broth culture. Besides, the use of predictive microbiology models for describing growth of both microorganisms in monoculture and coculture has been proposed. A preliminary inhibitory test confirmed the ability of Lb. sakei strain L115 to prevent the growth of a five-strain cocktail of L. monocytogenes. Next, the growth of microorganisms in isolation, i.e. in monoculture, was monitored and kinetic parameters maximum specific growth rate (µsp;max) and maximum population density (Nmax) were estimated by fitting the Baranyi model to recorded data. Inhibition coefficients (α) were calculated for the two kinetic parameters tested (µsp:max and Nmax) to quantify the percentage of reduction of growth when the microorganisms were in coculture in comparison with monoculture. The kinetic parameters were input into three interaction models, developed based on modifications of the Baranyi growth model, namely Jameson effect, new modified version of the Jameson effect and Lotka-Volterra models. Two approaches were utilized for simulation, one using the monoculture µsp;max, under the hypothesis that the growth potential is similar under monoculture and coculture conditions provided the environmental conditions are not modified, and the other one, based on adjusting the monoculture kinetic parameter by applying the corresponding α to reproduce the observed µsp;max under coculture conditions, assuming, in this approach, that the existence of a heterogeneous population can change the growth potential of each microbial population. It was observed that in coculture, µsp;max of L. monocytogenes decreased (e.g., α = 31% at 4 °C) and the Nmax was much lower than that of monoculture (e.g., α = 36% at 4 °C). The best simulation performance was achieved applying α to adjust the estimated monoculture growth rate, with the modified Jameson and Lotka-Volterra models showing better fit to the observed microbial interaction data as demonstrated by the fact that 100% data points fell within the acceptable simulation zone (±0.5 log CFU/mL from the simulated data). More research is needed to clarify the mechanisms of interaction between the microorganisms as well as the role of temperature.

Modelling the interaction of the sakacin-producing Lactobacillus sakei CTC494 and Listeria monocytogenes in filleted gilthead sea bream (Sparus aurata) under modified atmosphere packaging at isothermal and non-isothermal conditions.

The objective of this work was to quantitatively evaluate the effect of Lactobacillus sakei CTC494 (sakacin-producing bioprotective strain) against Listeria monocytogenes in fish juice and to apply and validate three microbial interaction models (Jameson, modified Jameson and Lotka Volterra models) through challenge tests with gilthead sea bream (Sparus aurata) fillets under modified atmosphere packaging stored at isothermal and non-isothermal conditions. L. sakei CTC494 inhibited L. monocytogenes growth when simultaneously present in the matrix (fish juice and fish fillets) at different inoculation ratios pathogen:bioprotector (i.e. 1:1, 1:2 and 1:3). The higher the inoculation ratio, the stronger the inhibition of L. monocytogenes growth, with the ratio 1:3 yielding no growth of the pathogen. The maximum population density (Nmax) was the most affected parameter for L. monocytogenes at all inoculation ratios. According to the microbiological and sensory analysis outcomes, an initial inoculation level of 4 log cfu/g for L. sakei CTC494 would be a suitable bioprotective strategy without compromising the sensory quality of the fish product. The performance of the tested interaction models was evaluated using the Acceptable Simulation Zone approach. The Lotka Volterra model showed slightly better fit than the Jameson-based models with 75-92% out of the observed counts falling into the Acceptable Simulation Zone, indicating a satisfactory model performance. The evaluated interaction models could be used as predictive modelling tool to simulate the simultaneous behaviour of bacteriocin-producing Lactobacillus strains and L. monocytogenes; thus, supporting the design and optimization of bioprotective culture-based strategies against L. monocytogenes in minimally processed fish products.

Modelling the growth of Listeria monocytogenes in Mediterranean fish species from aquaculture production.

Over the last couple of decades, several studies have evaluated growth dynamics of L. monocytogenes in lightly processed and ready-to-eat (RTE) fishery products mostly consumed in Nordic European countries. Other fish species from aquaculture production are of special interest since their relevant consumption patterns and added value in Mediterranean countries, such as sea bream and sea bass. In the present study, the growth of L. monocytogenes was evaluated in fish-based juice (FBJ) by means of optical density (OD) measurements in a temperature range 2-20 °C under different atmosphere conditions (i.e. reduced oxygen and aerobic). The Baranyi and Roberts model was used to estimate the maximum growth rate (µmax) from the observed growth curves. The effect of storage temperature on µmax was modelled using the Ratkowsky square root model. The developed models were validated using experimental growth data for L. monocytogenes in sea bream and sea bass fillets stored under static and dynamic temperature conditions. Overall, models developed in FBJ provided fail-safe predictions for L. monocytogenes growth. For the model generated under reduced oxygen conditions, bias and accuracy factor for growth rate predictions were 1.15 and 1.25, respectively, showing good performance to adequately predict L. monocytogenes growth in Mediterranean fish products. The present study provides validated predictive models for L. monocytogenes growth in Mediterranean fish species to be used in microbial risk assessment and shelf-life studies.