Extracting survival parameters from isothermal, isobaric, and "iso-concentration" inactivation experiments by the "3 end points method"

M. G. Corradini, M. D. Normand, C. Newcomer, D. W. Schaffner, M. Peleg

Research output: Contribution to journalReview articlepeer-review

18 Scopus citations


Theoretically, if an organism's resistance can be characterized by 3 survival parameters, they can be found by solving 3 simultaneous equations that relate the final survival ratio to the lethal agent's intensity. (For 2 resistance parameters, 2 equations will suffice.) In practice, the inevitable experimental scatter would distort the results of such a calculation or render the method unworkable. Averaging the results obtained with more than 3 final survival ratio triplet combinations, determined in four or more treatments, can remove this impediment. This can be confirmed by the ability of a kinetic inactivation model derived from the averaged parameters to predict survival patterns under conditions not employed in their determination, as demonstrated with published isothermal survival data of Clostridium botulinum spores, isobaric data of Escherichia coli under HPP, and Pseudomonas exposed to hydrogen peroxide. Both the method and the underlying assumption that the inactivation followed a Weibull-Log logistic (WeLL) kinetics were confirmed in this way, indicating that when an appropriate survival model is available, it is possible to predict the entire inactivation curves from several experimental final survival ratios alone. Where applicable, the method could simplify the experimental procedure and lower the cost of microbial resistance determinations. In principle, the methodology can be extended to deteriorative chemical reactions if they too can be characterized by 2 or 3 kinetic parameters.

Original languageEnglish (US)
Pages (from-to)R1-R11
JournalJournal of Food Science
Issue number1
StatePublished - Jan 2009

All Science Journal Classification (ASJC) codes

  • Food Science


  • Kinetics
  • Nonlinear inactivation
  • Predictive microbiology
  • Thermal processing
  • Weibull-Log logistic (WeLL) model


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