* Modeling tools to aid decision making
relevant to validating
reduction of free chlorine variability.
* Modeling tools will provide guidance
for experiments at pilot
and commercial scale in hopes
to minimize future expense.
* Guidance for equipment design such
as free chlorine probe validation.
* Focus on the future - developing real-time
sanitization control processes.
Munther said the model is expected to link easy-to-measure water quality parameters, such as total dissolved solids and turbidity, to organic load and chlorine decay that occur during the recirculated wash process.
Daniel first learned about CPS and its mission by searching online and was encouraged by CPS funded scientist Yaguang (Sunny) Luo (USDA-ARS) to apply for a grant. The reason for taking a smaller scale approach and starting with a "proof of concept" project was to identify the fundamental dynamics involved at the lab scale/pilot scale before tackling the full commercial problem. This is a typical scientific approach.
Ultimately, the group hopes to develop optimal sanitizer strategies that are easily automatable and adjustable to specific commodities and washing practices. The information could help fresh-cut processors reduce fluctuations in free chlorine levels or as an initial step in developing the "brains" for the next generation of online chlorine controllers.
For the current one-year project, titled "Mathematical modeling tools for practical chlorine control in produce wash process," Munther's group focused on cut green cabbage and cut carrots. But he said the tool is being designed so it can be tailored to wash processes for other types of cut produce.
Much of the current knowledge about free chlorine in wash water has been described from experiments and through correlative studies, he explained. But the wash process involves a highly dynamic environment influenced by rapid changes in water chemistry.
"The information and research that's been done so far is essential. But it alone is really difficult to use to make real-time corrective measures in such a dynamic situation as produce washing," Munther said. "Instead of just correlating things on the surface, can we describe the dynamic relationships that give you a functional understanding of what's going on?" questioned Munther. "You have a given free chlorine concentration, a produce dwell time in the wash water of 30 seconds to one minute, and an extremely high rate of product coming in. How fast is the chlorine depleted over time? Can we use math to describe the chemistry that's causing the free chlorine decay?"
Co-PIs Srinivasan and Kothapalli, associate professors of mathematics and of chemical and biomedical engineering, respectively, have been conducting laboratory experiments and using the data to validate the predictive model. Dr. Yaguang (Sunny) Luo, a research food technologist with the U.S. Department of Agriculture Agricultural Research Service in Beltsville, Maryland, also is providing the Cleveland State University group with data for model validation as well as experimental design advice.