Thermal Food Processing

Simulating Thermal Food Processes Using Deterministic Models 93
the retort, the cooling process is simulated by simply changing the boundary
conditions from retort temperature T R to cooling temperature T C at the surface
nodes and continuing with the computer iterations described above.
The temperature at the can center can be calculated after each time interval
to produce a predicted heat penetration curve upon which the process lethality,
F, can be calculated. When the numerical computer model is used to calculate
the process time required at a given retort temperature to achieve a specified
lethality, F, the computer follows a programmed search routine of assumed
process times that quickly converges on the precise time at which cooling should
begin in order to achieve the specified F value. Thus, the model can be used to
determine the process time required for any given set of constant or variable retort
temperature conditions.
3.7 PROCESS OPTIMIZATION
3.7.1 OBJECTIVE FUNCTIONS
The principle objective of thermal process optimization is to maximize product
quality and profits while minimizing undesirable changes and cost. At all times,
a minimal process must be maintained to exclude the danger from microorganisms
of public health and spoilage concern. Five elements common to all
optimization problems are performance or objective function (quality factors,
nutrients, texture, and sensory characteristics), decision variables (retort temperature
and process time), constraints (practical limits for temperatures and
required minimal lethality), mathematical model (analytical, finite differences,
and finite element), and optimization technique (search, response surface, and
linear or nonlinear programming).
Optimization theory makes use of the different temperature sensitivities of
microbial and quality factor destruction rates. Microorganisms have lower decimal
reduction times (less resistant to heat) and a lower Z value (more sensitive
to temperature) than most quality factors. Hence, a higher temperature will result
in preferential destruction of microorganisms over the quality factor. Especially
applied to liquid product, either in a batch mode (in-container) or in continuous
aseptic systems, the higher temperature with shorter time offers a great potential
for quality optimization. However, for conduction-heating foods, one of the major
limitations is the slower heating. All higher temperatures do not necessarily favor
the best quality retention because they also expose the product nearer the surface
to more severe temperatures than the product at the center, which might result in
diminished overall quality.
3.7.2 THERMAL DEGRADATION OF QUALITY FACTORS
Optimum combinations of retort temperature and process time that maximize
quality or nutrient retention can be found if the kinetic parameters describing the
thermal degradation kinetics of the quality factors are known. Using the numerical
computer simulation (deterministic) models described earlier, process times