ABSTRACT
At temperatures above the optimum for growth of a micro-
organism, growth rate declines until, at some elevated
temperature, the microorganism begins to die. Heat may
be used to create shelf-stable, i.e., able to be stored at
ambient temperatures, or pasteurized foods, i.e., able to be
stored for a longer period than the fresh product when
combined with other preservation methods, such as refrig-
eration. To design thermal processes for foods that will
inactivate microorganisms causing foodborne illness or
spoilage, it is necessary to know the heating rate of a food
product and the heat resistance of the target microorgan-
isms in the food. Factors influencing heat resistance of
microorganisms include the microbial population itself,
the food product, and the heating environment. While sur-
vivor curves are often linear, there are factors that may
cause deviations in the linearity of these curves. Potential
implications of using a log-linear model with non-linear
survivor curve data include overestimation of the D-value
of a target microorganism leading to a thermal process
design that overcooks a food or underestimation of a
D-value creating the potential for survival of target path-
ogenic or spoilage microorganisms. Moreover, log-linear
models are unable to accurately predict the effects of tem-
perature increases at lower temperatures where growth
is first promoted, then inhibited, and finally cells are
inactivated. Today, several models have been developed
to describe non-linear survival curves.
