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

Abstract

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.

Prediction of Pseudomonas spp. Population in Food Products and Culture Media Using Machine Learning-Based Regression Methods

“…The maximum specific growth rate (µ max ), which is one of the most important growth kinetic parameters, can be modelled with respect to environmental factors such as temperature, NaCl concentration, water activity, and pH. Among these factors, temperature plays a key role in affecting microbial growth behaviour in food [5]. Temperature variables ranged from 2 to 11 • C for beef, 0 to 25 • C for culture medium, 0.1 to 10.4 • C for pork, and 1 to 7 • C for poultry, which means 5618 collected growth data points were in the range of 0 to 25 • C which are real temperatures to which food products are subject to in storage, delivery, and retail marketing processes.…”

“…The prevalent and traditional modelling technique in predictive microbiology is the two-step modelling approach, which involves fitting the primary and secondary models sequentially. Initially, the primary model is fitted to growth data points, and then the resulting growth kinetic parameters are integrated into the secondary model, considering environmental factors such as temperature [5]. Nevertheless, the two-step modelling approach has its limitations.…”

Electromagnetic fields effects on microbial growth in cocoa fermentation: A controlled experimental approach using established growth models

“…Kinetic information on specific growth rates, lag phases, biomass yields, and substrate consumption rates under different environmental conditions helps construct mathematical models that optimize and predict bioprocess outcomes [ 5 ]. In the food industry, selection of appropriate models depends on the characteristics of the microorganism and the food matrix, and their accuracy should be validated with experimental data [ 6 , 7 ]. Comparative analysis of different mathematical models has shown that specific models are suitable for different types of microorganisms and food matrices [ 6 , 8 ].…”

Listeria in Food: Prevalence and Control

“…In this regard, Posada-Izquierdo et al [ 5 ] modeled the effect of salt concentration on autochthonous isolated L. monocytogenes strains in an artisanal fresh cheese. Finally, Bolívar et al [ 6 ] quantified and modeled the growth dynamics of six L. monocytogenes strains isolated from different fish products in salmon pâté. Both studies have demonstrated the growth potential of the pathogen under all tested conditions, providing interesting data about its kinetic behavior in RTE food products with significant consumption and commercial value.…”