Background: Candida utilis
is widely used in bioindustry, and its cell mass needs to be produced in a
cost effective way. Process optimization based on the experimental results is the major way to reduce
the production cost. However, this process is expensive, time consuming and labor intensive.
Mathematical modeling is a useful tool for process analysis and optimization. Furthermore, sufficient
information can be obtained with fewer experiments by using the mathematical modeling, and some
results can be predicted even without doing experiments.
Results: In the present study, we performed the mathematical modeling and simulation for the cell
mass production of
Candida utilis based on limited batch and repeated fedbatch experiments. The
model parameters were optimized using genetic algorithm (GA), and the processes were analyzed.
Conclusions: Taken together, this newly developed method is efficient, labor saving and cost
effective.
