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Numerical analysis of rectangular type batch ohmic heater to identify the cold point.

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  • 1Department of Landscape Architecture and Rural Systems Engineering, and Research Institute for Agriculture and Life Sciences Seoul National University Seoul Republic of Korea.

Food Science & Nutrition
|January 30, 2020
PubMed
Summary

This study precisely simulated ohmic heating pasteurization of orange juice, accurately predicting temperature distribution and Escherichia coli O157:H7 inactivation. A cold spot in larger batches required longer treatment times for pathogen reduction.

Keywords:
E. coli O157:H71Ohmic heatercold pointnumerical simulationorange juice

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Area of Science:

  • Food Science and Technology
  • Bioprocess Engineering
  • Computational Modeling

Background:

  • Ohmic heating offers rapid and volumetric pasteurization for liquid foods like orange juice.
  • Accurate modeling is crucial for optimizing process parameters and ensuring microbial inactivation.
  • Escherichia coli O157:H7 is a significant foodborne pathogen requiring effective inactivation strategies.

Purpose of the Study:

  • To develop and validate a time-dependent numerical model for simulating ohmic heating in orange juice.
  • To precisely predict temperature distribution and Escherichia coli O157:H7 inactivation kinetics.
  • To investigate the impact of sample size on pasteurization efficacy and identify potential cold spots.

Main Methods:

  • Utilized a finite element method (FEM) model incorporating Java-based pathogen inactivation codes.
  • Simultaneously solved electric heating, k-ε turbulent flow, and heat transfer equations.
  • Incorporated natural heat losses as boundary conditions and validated against experimental data.

Main Results:

  • Simulated temperature distribution and E. coli O157:H7 inactivation showed excellent agreement with experimental data (within 6.0% relative error).
  • Identified a critical cold point in the bottom corner of the heating vessel.
  • Observed that larger orange juice sample volumes exacerbated the cold point problem, necessitating extended treatment times.

Conclusions:

  • The developed numerical model accurately predicts ohmic heating performance in orange juice.
  • The cold point phenomenon is a critical factor affecting pasteurization uniformity and efficacy, especially in larger volumes.
  • Optimized treatment times are essential to achieve a 5-log reduction of E. coli O157:H7, particularly considering geometric effects.