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ARS Home » Northeast Area » Wyndmoor, Pennsylvania » Eastern Regional Research Center » Residue Chemistry and Predictive Microbiology Research » Research » Publications at this Location » Publication #372957

Research Project: Development, Evaluation, and Validation of Technologies for the Detection and Characterization of Chemical Contaminants in Foods

Location: Residue Chemistry and Predictive Microbiology Research

Title: Modeling the inactivation of escherichia coli O157:H7 and salmonella typhimurium in juices by pulsed electric fields: The role of the energy density

Author
item OLIVERIRA, GABRIELLA - Purdue University
item Jin, Zhonglin
item CAMPANELLA, OSVALDO - Ohio University

Submitted to: Journal of Food Process Engineering
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/26/2020
Publication Date: 10/1/2020
Citation: Oliverira, G.M., Jin, Z.T., Campanella, O.H. 2020. Modeling the inactivation of escherichia coli O157:H7 and salmonella typhimurium in juices by pulsed electric fields: The role of the energy density. Journal of Food Process Engineering. https://doi.org/10.1016/j.jfoodeng.2020.110001.
DOI: https://doi.org/10.1016/j.jfoodeng.2020.110001

Interpretive Summary: Escherichia coli O157:H7 and Salmonella Typhimurium are the safety concern in juice products. This study modeled the inactivation rate of these pathogens in juices treated by pulsed electric fields using one integrated energy density parameter. The developed model is suitable for precisely estimating the inactivation rate of foodborne pathogens of concern in juices by PEF processing and provides valuable information for PEF system manufacturers and users.

Technical Abstract: his study was to integrate electric field intensity, pulse repetition rate, treatment time, and food electrical conductivity into one energy density parameter and correlate it with the inactivation rate of Escherichia coli O157:H7 and Salmonella Typhimurium. A continuous bench scale PEF system (OSU-4H) was used to treat juice samples with the combinations of 5 electric field strengths and 5 pulse repetition rates. Nonlinear survival curves were modeled by a differential equation that was numerically solved using the Runge-Kutta method. The developed model successfully described the survival kinetics of the involved pathogens. The model was validated with different juices and PEF treatments and demonstrated that it was able to satisfactorily predict the experimental data as well as data from literature. These predictions suggest that the model is suitable for precisely estimating the inactivation rate of foodborne pathogens of concern in juices by PEF processing.