An introduction to predictive microbiology and the development and use of probability models withClostridium botulinum
Summary
Traditionally, food microbiologists have relied on empirical studies to assess the microbiological safety of a particular food. However, these studies are time-consuming and, because only one or two inhibitory factors are usually dealt with, they are often of limited value. Today, the food industry is constantly developing new products with new formulations and alternative packaging strategies, resulting in a wide diversity of factors to be studied. It is therefore advantageous to develop mathematical models describing microbial growth which may be used to predict how changes in formulations or storage conditions may affect microbial growth. A brief overview of the basic concepts and steps of modeling procedures will be presented, along with some of the difficulties encountered therein. The safety of foods with respect toClostridium botulinum depends on the probability (P) of growth or of toxigenesis, andP has been the dependent variable in several models. The development of these probability models will be discussed.
Key words
Probability models Clostridium botulinum Irradiation Polynomial equationsPreview
Unable to display preview. Download preview PDF.
References
- 1.Dodds, K.L. 1989. Combined effect of water activity and pH on inhibition of toxin production byClostridium botulinum in cooked, vacuum-packed potatoes. Appl. Environ. Microbiol. 55: 656–660.Google Scholar
- 2.Farber, J.M. 1986. Predictive modeling of food deterioration and safety. In: Foodborne Microorganisms and Their Toxins: Developing Methodology (Pierson, M.D. and N.J. Stern, eds), pp. 57–90, Marcel Dekker, New York.Google Scholar
- 3.Hauschild, A.H. 1982. Assessment of botulism hazards from cured meat products. Food Technol. 36(12): 95–104.Google Scholar
- 4.Hauschild, A.H. 1989.Clostridium botulinum. In: Foodborne Bacterial Pathogens (Doyle, M.P., ed.), pp. 111–189, Marcel Dekker, New York.Google Scholar
- 5.Lambert, A.D., J.P. Smith and K.L. Dodds. 1991a. Effect of headspace CO2 concentration on toxin production byClostridium botulinum in MAP, irradiated fresh pork. J. Food Protect. 54: 588–592.Google Scholar
- 6.Lambert, A.D., J.P. Smith and K.L. Dodds. 1991b. Effect of initial O2 and CO2 and low-dose irradiation on toxin production byClostridium botulinum in MAP fresh pork. J. Food Protect. 54: 939–944.Google Scholar
- 7.Lambert, A.D., J.P. Smith and K.L. Dodds. 1991c. Combined effect of modified atmosphere packaging and low-dose irradiation on toxin production byClostridium botulinum in fresh pork. J. Food Protect. 54: 94.Google Scholar
- 8.Pivnick, H. and A. Petrasovits. 1973. A rationale for the safety of canned shelf-stable cured meat. Protection=Destruction+Inhibition. In: 19th Meeting European Meat Researchers, Sept. 1973, p. 1086, Paris.Google Scholar
- 9.Ratkowsky, D.A., J. Olley, T.A. McMeekin and A. Ball. 1982. Relationship between temperature and growth rate of bacterial cultures. J. Bacteriol. 149: 1–5.Google Scholar
- 10.Riemann, H. 1967. The effect of the number of spores on growth and toxin formation byC. botulinum type E in inhibitory environments. In: Botulism 1966 (Ingram, M. and T.A. Roberts, eds), pp. 150–168, Chapman & Hall, London.Google Scholar
- 11.Roberts, T.A., A.M. Gibson and A. Robinson. 1981. Prediction of toxin production byClostridium botulinum in pasteurized pork slurry. J. Food Technol. 16: 337–355.Google Scholar
- 12.Zwietering, M.H., I. Jongenburger, F.M. Rombouts and K. van't Riet. 1990. Modeling of the bacterial growth curve. Appl. Environ. Microbiol. 56: 1875–1881.Google Scholar