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Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:   No Citation available.
Authors:   Anandakumar Palanichamy, Digvir S Jayas, Richard A Holley
Keywords:   microbial modeling, predictive microbiology, food safety engineering

Abstract Government policies developed after seeing a series of food borne outbreaks caused by pathogenic microorganisms require the meat industry to ensure reduction or elimination of those organisms in meat products. For this, Industry needs to take up an extensive amount of work to generate and accumulate data on behavior of microorganisms in the food product. It is expensive, time consuming and laborious. Predictive microbial modeling is a rapidly emerging food safety engineering technique to model the effects of various environmental conditions in growth or survival of microorganisms during manufacturing of food. This technique can serve better in meat industry for ensuring food safety. In this paper, literature on microbial modeling techniques for meat industry is reviewed and the origin, history and development of various models; the superior performance, advantages and disadvantages of artificial neural network (ANN) based models; necessity of modeling with sufficient data; and necessity of developing tertiary models for industrial applications are outlined.

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