Growth and inactivation models to be used in quantitative risk assessments

J Food Prot. 1998 Nov;61(11):1541-9. doi: 10.4315/0362-028x-61.11.1541.

Abstract

In past years many models describing growth and inactivation of microorganisms have been developed. This study is a discussion of the growth and inactivation models that can be used in a stepwise procedure for quantitative risk assessment. First, rough risk assessments are performed in which orders of magnitude for microbial processes are estimated by the use of simple models. This method provides an efficient way to find the main determinants of risk. Second, the main determinants of risk are studied more accurately and quantitatively. It is best to compare several models at this level, as no model is expected to be able accurately to predict microbial responses under all circumstances. By comparing various models the main determinants of risk are studied from several points of view, and risks can be assessed on a broad basis. If, however, process variations have a more profound effect on risk than the differences between models, it is most efficient to use the simplest model available. If relevant, the process variations can be stochastically described in the third level of detail. Stochastic description of the process parameters will however not change the conclusion on the usefulness of simple models in quantitative risk assessments. The proposed stepwise procedure that starts simply before going into detail provides a structured method of risk assessment and prevents the researcher from getting caught in too much complexity. This simplicity is necessary because of the complex nature of food safety. The principal aspects are highlighted during the procedure and many factors can be omitted since their quantitative effect is negligible.

MeSH terms

  • Bacillus cereus / growth & development
  • Bacillus cereus / isolation & purification
  • Bacteria / growth & development*
  • Food Handling
  • Food Microbiology*
  • Forecasting
  • Mathematics
  • Models, Biological*
  • Risk Assessment / methods
  • Solanum tuberosum / microbiology
  • Temperature