P3-101 A Dimensional Analysis Approach to Modeling Bacterial Pathogen Transfer during Conveying, Washing, and Slicing of Fresh-cut Produce

Wednesday, July 31, 2013
Exhibit Hall (Charlotte Convention Center)
Beatriz Mazón, Michigan State University, East Lansing, MI
Bradley Marks, Michigan State University, East Lansing, MI
Introduction: Pathogen transfer data to/from fresh produce during postharvest processes are increasingly being reported in the literature.  However, data are presented as product/process-specific cases, with little or no generalizable results extendable to the broader, biologically complex problem.  A well-constructed model could enable improved process design and analysis.

Purpose: To apply a dimensional analysis approach, with similarity criteria, to formulate a novel model for bacterial pathogen transfer during produce conveying, washing, and slicing.

Methods: The Buckingham Pi Theorem was applied to formulate a generalized model for bacterial transfer occurring between fresh produce and wash/conveying water or equipment contact surfaces.  Initially, 11 candidate variables (product and process) were identified for equipment contact events (slicing, shredding, and conveying), and 21 were identified for water washing/conveying. Based on expert knowledge, variables unlikely to significantly affect transfer were excluded, to yield 6 and 9 variables for equipment contact events and water washing/conveying processes, respectively.  Application of the Buckingham Pi Theorem accounted for the fundamental units of each variable and the total number of variables in each process to reduce the model to a smaller number of dimensionless (Pi) terms.

Results: The resulting models included two and five dimensionless (Pi) terms, respectively, for the equipment contact and water wash/conveying processes. Each dimensionless term in the resulting models (like, for example, a Reynolds number in fluid flow) can be applied to determine relative impact of key variables on transfer. For example, one Pi term relates friction force at the surface, contact time, and the initial bacterial population on the donor surface to resulting transfer.  For the water transfer events, the Pi terms relate water velocity and product dimensions, which can illustrate the general dependency of transfer on fluid shear.  

Significance: This novel approach to modeling bacterial transfer will enable optimized designs of future transfer experiments, in order to yield data that improve the utility of the generalized transfer model for process improvement and risk modeling.