Food Science and Biotechnology

Korean Society of Food Science and Technology (한국식품과학회)
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Predictive Modeling for Microbial Risk Assessment (MRA) from the Literature Experimental Data

  • Bahk, Gyung-Jin (Department of Food and Nutrition, Kunsan National University)
  • Published : 2009.02.28
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Abstract

One of the most important aspects of conducting this microbial risk assessment (MRA) is determining the model in microbial behaviors in food systems. However, to fully these modeling, large expenditures or newly laboratory experiments will be spent to do it. To overcome these problems, it has to be considered to develop the new strategies that can be used data in the published literatures. This study is to show whether or not the data set from the published experimental data has more value for modeling for MRA. To illustrate this suggestion, as example of data set, 4 published Salmonella survival in Cheddar cheese reports were used. Finally, using the GInaFiT tool, survival was modeled by nonlinear polynomial regression model describing the effect of temperature on Weibull model parameters. This model used data in the literatures is useful in describing behavior of Salmonella during different time and temperature conditions of cheese ripening.

Keywords

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