perceived need to reduce nitrite levels in cured meats such as hams and to
assess quantitatively the relative importance of factors contributing to
their safety.
In the original work, the probability of toxin production,p, (the
proportion of samples containing toxin within each treatment combina-
tion) was fitted to a logistic model to describe the relationship between
the probability of toxin production and the level of factors/variables
present (Figure 3.15). Any factor which tends to decreasemin Figure 3.15
reduces the probability of toxin production. Of the different factors
included in the model, it can be seen that nitrite, incubation temperature
and salt are more important in preventing toxin production than the
others and that they are acting independently; there is no evidence of
synergistic interactions between them.
Here the logistic equation is being used simply as a regression equa-
tion, a common practice in modelling situations where there are two
possible outcomes to an event,e.g.pass/fail, toxin production/no toxin
production. Its use in this context should not be confused with its use to
represent the microbial growth curve (Section 3.1).
Figure 3.15 Logistic model for probability of toxin production byClostridium botulinum
types A and B in pasteurized pork slurry in the pH range 5.5 to 6.3
Chapter 3 55