563
Appendix A: Predictive
Modeling of Microbial
Growth in Food
importance
Every year, more than 12,000 new food products are introduced to U.S. consumers in addition
to more than 100,000 existing food items. Some of these products obviously have limited shelf
life because of the possibility of microbial growth under the conditions in which they are stored
and handled following production. The initial microbial population in many of these products
may include both spoilage and pathogenic types. To ensure stability and safety, it is important
that proper control measures are used to prevent growth of the microorganisms from the time of
production to the time of consumption of these products. 1,2
Among the thousands of new products marketed every year, some are definitely produced to
satisfy consumers looking for foods that are healthy, natural, low-fat, low-salt, tasty, convenient,
do not contain harsh preservatives, are not given harsh treatment, have long storage life, and are
safe. To produce these new types of foods (such as the new-generation refrigerated foods) with
desirable safety, stability, and acceptance quality, the influence of many parameters, such as different ingredients at different concentrations under different processing and storage conditions and
at different A W , pH, and other intrinsic and extrinsic factors, on microbial growth and destruction
in foods has to be determined.
It is almost impossible to conduct such microbiological studies for each product by the methods traditionally used to ensure safety and stability of food products. However, with the aid of
computers, mathematical models can be developed to determine the influence of combinations of
several parameters on microbial growth. Although they may not be accurate, they can be effective to obtain first-hand information very rapidly, helpful to eliminate many of the less important
possibilities, and select a few that appear more promising. This information can then be used to
conduct a modest traditional study that is feasible both experimentally and economically.
Appendix A: Predictive
Modeling of Microbial
Growth in Food
importance
Every year, more than 12,000 new food products are introduced to U.S. consumers in addition
to more than 100,000 existing food items. Some of these products obviously have limited shelf
life because of the possibility of microbial growth under the conditions in which they are stored
and handled following production. The initial microbial population in many of these products
may include both spoilage and pathogenic types. To ensure stability and safety, it is important
that proper control measures are used to prevent growth of the microorganisms from the time of
production to the time of consumption of these products. 1,2
Among the thousands of new products marketed every year, some are definitely produced to
satisfy consumers looking for foods that are healthy, natural, low-fat, low-salt, tasty, convenient,
do not contain harsh preservatives, are not given harsh treatment, have long storage life, and are
safe. To produce these new types of foods (such as the new-generation refrigerated foods) with
desirable safety, stability, and acceptance quality, the influence of many parameters, such as different ingredients at different concentrations under different processing and storage conditions and
at different A W , pH, and other intrinsic and extrinsic factors, on microbial growth and destruction
in foods has to be determined.
It is almost impossible to conduct such microbiological studies for each product by the methods traditionally used to ensure safety and stability of food products. However, with the aid of
computers, mathematical models can be developed to determine the influence of combinations of
several parameters on microbial growth. Although they may not be accurate, they can be effective to obtain first-hand information very rapidly, helpful to eliminate many of the less important
possibilities, and select a few that appear more promising. This information can then be used to
conduct a modest traditional study that is feasible both experimentally and economically.