Login / Signup

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

Araceli BolívarChajira Garrote AchouFatih TarlakMaría Jesús CantalejoJean Carlos Correia Peres CostaFernando Pérez Rodríguez
Published in: Foods (Basel, Switzerland) (2023)
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 ( μ max ), and maximum cell density ( N max ). Then, the effect of storage temperature on the obtained μ max 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 μ max . Besides, the growth variations among the strains did not follow a regular pattern. The estimated secondary model parameter T min 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.
Keyphrases
  • escherichia coli
  • risk assessment
  • stem cells
  • high resolution
  • mesenchymal stem cells
  • deep learning
  • sensitive detection
  • listeria monocytogenes