title: Stochastic modelling of Listeria monocytogenes single cell growth in cottage cheese with mesophilic lactic acid bacteria from aroma producing cultures.
abstract: A stochastic model was developed for simultaneous growth of low numbers of Listeria monocytogenes and populations of lactic acid bacteria from the aroma producing cultures applied in cottage cheese. During more than two years, different batches of cottage cheese with aroma culture were analysed for pH, lactic acid concentration and initial concentration of lactic acid bacteria. These data and bootstrap sampling were used to represent product variability in the stochastic model. Lag time data were estimated from observed growth data (lactic acid bacteria) and from literature on L. monocytogenes single cells. These lag time data were expressed as relative lag times and included in growth models. A stochastic model was developed from an existing deterministic growth model including the effect of five environmental factors and inter-bacterial interaction [Østergaard, N.B, Eklöw, A and Dalgaard, P. 2014. Modelling the effect of lactic acid bacteria from starter- and aroma culture on growth of Listeria monocytogenes in cottage cheese. International Journal of Food Microbiology. 188, 15-25]. Growth of L. monocytogenes single cells, using lag time distributions corresponding to three different stress levels, was simulated. The simulated growth was subsequently compared to growth of low concentrations (0.4-1.0 CFU/g) of L. monocytogenes in cottage cheese, exposed to similar stresses, and in general a good agreement was observed. In addition, growth simulations were performed using population relative lag time distributions for L. monocytogenes as reported in literature. Comparably good predictions were obtained as for the simulations performed using lag time data for individual cells of L. monocytogenes. Therefore, when lag time data for individual cells are not available, it was suggested that relative lag time distributions for L. monocytogenes can be used as a qualified default assumption when simulating growth of low concentrations of L. monocytogenes.
authors.affiliation: National Food Institute (DTU Food), Technical University of Denmark, Kgs. Lyngby, Denmark.
authors.forename: Nina Bjerre
authors.initials: NB
authors.lastname: Østergaard
authors.affiliation: Department of Applied Mathematics and Computer Science (DTU Compute), Technical University of Denmark, Kgs. Lyngby, Denmark.
authors.forename: Lasse Engbo
authors.initials: LE
authors.lastname: Christiansen
authors.affiliation: National Food Institute (DTU Food), Technical University of Denmark, Kgs. Lyngby, Denmark. Electronic address: pada@food.dtu.dk.
authors.forename: Paw
authors.initials: P
authors.lastname: Dalgaard
mesh_terms: D000465:Algorithms; D002611:Cheese / Q000382:microbiology*; D005516:Food Microbiology; D006863:Hydrogen-Ion Concentration; D019344:Lactic Acid / Q000378:metabolism; D007777:Lactobacillaceae / Q000254:growth & development*; D008089:Listeria monocytogenes / Q000254:growth & development*
chemical_list: D019344:Lactic Acid
keywords: Bacterial interaction; Fresh fermented dairy products; Low contamination levels; Relative lag time; Variability