Temperature effect on bacterial growth rate: quantitative microbiology approach including cardinal values and variability estimates to perform growth simulations on/in food

Int J Food Microbiol. 2005 Apr 15;100(1-3):179-86. doi: 10.1016/j.ijfoodmicro.2004.10.015. Epub 2004 Nov 24.

Abstract

Temperature effect on growth rates of Listeria monocytogenes, Salmonella, Escherichia coli, Clostridium perfringens and Bacillus cereus, was studied. Growth rates were obtained in laboratory medium by using a binary dilutions method in which 15 optical density curves were generated to determine one mu value. The temperature was in the range from 2 to 48 degrees C, depending on the bacterial species. Data were analysed after a square root transformation. No large difference between the strains of a same species was observed, and therefore all the strains of a same species were analysed together with the same secondary model. The variability of the residual error, including both measurements errors and biological strain difference, was homogenous for sub-optimal temperature values. To represent this variability in bacterial kinetic simulation, the 95% confidence interval based on an asymptotic Normal distribution, around the growth rate value was determined. With this modelling approach, the behaviour of bacterial species on food, irrespective of the strain or the laboratory, was described. This growth simulation with confidence limits has several applications, such as to facilitate comparisons between a challenge-test and simulation results, and, to appreciate if the temperature change has or has not a significant effect on a bacterial growth profile, with regard to the uncontrolled factors. The integration of this piece of work in the Sym'Previus software is now in process. Results obtained in five French laboratories will be extended by working on new food and new microbial species and improved by further work on variability estimation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Bacillus cereus / growth & development
  • Bacteria / growth & development*
  • Clostridium perfringens / growth & development
  • Computer Simulation
  • Dairy Products / microbiology
  • Escherichia coli / growth & development
  • Food Microbiology*
  • Kinetics
  • Listeria monocytogenes / growth & development
  • Meat / microbiology
  • Models, Biological*
  • Predictive Value of Tests
  • Salmonella / growth & development
  • Seafood / microbiology
  • Software
  • Species Specificity
  • Temperature*