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Fundamental Food Microbiology, Third Edition - Fuad Fathir

Fundamental Food Microbiology, Third Edition - Fuad Fathir

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541<br />

APPENDIX B<br />

Predictive Modeling of Microbial Growth<br />

in <strong>Food</strong><br />

I. IMPORTANCE<br />

Every year, more than 12,000 new food products are introduced to U.S. consumers<br />

in addition to the existing more than 100,000 food items. Some of these products<br />

obviously have limited shelf life because of the possibility of microbial growth under<br />

the conditions in which they are stored and handled following production. The initial<br />

microbial population in many of these products may include both spoilage and<br />

pathogenic types. To ensure stability and safety, it is important that proper control<br />

measures are used to prevent growth of the microorganisms from the time of production<br />

to the time of consumption of these products. 1,2<br />

Among the thousands of new products marketed every year, some are definitely<br />

produced to satisfy consumers looking for foods that are healthy, natural, low-fat,<br />

low-salt, tasty, convenient, do not contain harsh preservatives, are not given harsh<br />

treatment, have long storage life, and are safe. To produce these new types of foods<br />

(such as the new-generation refrigerated foods) with desirable safety, stability, and<br />

acceptance quality, the influence of many parameters, such as different ingredients<br />

at different concentrations under different processing and storage conditions and at<br />

different A w, pH and other intrinsic and extrinsic factors, on microbial growth and<br />

destruction in foods has to be determined.<br />

It is almost impossible to conduct such microbiological studies for each product<br />

by the methods traditionally used to ensure safety and stability of food products.<br />

However, with the aid of computers, mathematical models can be developed to<br />

determine the influence of combinations of several parameters on microbial growth.<br />

Although they may not be accurate, they can be effective to obtain first-hand<br />

information very rapidly, helpful to eliminate many of the less important possibilities,<br />

and select a few that appear more promising. This information can then be<br />

used to conduct a modest traditional study that is feasible both experimentally and<br />

economically.

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