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MATHEMATICAL MODELING OF MICROBIAL GROWTH: A REVIEW
Author(s) -
SKINNER GUY E.,
LARKIN JOHN W.,
RHODEHAMEL E. JEFFERY
Publication year - 1994
Publication title -
journal of food safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.427
H-Index - 43
eISSN - 1745-4565
pISSN - 0149-6085
DOI - 10.1111/j.1745-4565.1994.tb00594.x
Subject(s) - regression analysis , econometrics , probabilistic logic , mathematical model , regression , statistical model , bacterial growth , computer science , square root , product (mathematics) , statistics , mathematics , bacteria , genetics , biology , geometry
The use of mathematical modeling of microbiological behavior to predict and evaluate food safety or shelf life is receiving considerable interest. Researchers are attempting to use mathematical equations that incorporate such critical growth factors as pH, a w , and NaCl content to predict microbial growth and/or toxin production in order to replace traditional time‐intensive challenge studies. Predictive equations can be divided into probabilistic, regression, Arrhenius, and square root models. Models vary greatly in theory and complexity. Predictive models are used to monitor processes ranging from temperature during distribution to inventory control. They have been shown to be useful in product development and shelf‐life estimation when safety is not an issue. Most models are generated by regression analysis of data obtained from laboratory experiments. Statistically based models, even when conservatively derived, are not appropriate as the only criterion for evaluating food safety.