Skip to main content
NCBI home page
Emerging Infectious Diseases logoLink to Emerging Infectious Diseases
. 1997 Oct-Dec;3(4):541–549. doi: 10.3201/eid0304.970419

Quantitative microbiology: a basis for food safety.

T A McMeekin 1, J Brown 1, K Krist 1, D Miles 1, K Neumeyer 1, D S Nichols 1, J Olley 1, K Presser 1, D A Ratkowsky 1, T Ross 1, M Salter 1, S Soontranon 1
PMCID: PMC2640082  PMID: 9366608

Abstract

Because microorganisms are easily dispersed, display physiologic diversity, and tolerate extreme conditions, they are ubiquitous and may contaminate and grow in many food products. The behavior of microbial populations in foods (growth, survival, or death) is determined by the properties of the food (e.g., water activity and pH) and the storage conditions (e.g., temperature, relative humidity, and atmosphere). The effect of these properties can be predicted by mathematical models derived from quantitative studies on microbial populations. Temperature abuse is a major factor contributing to foodborne disease; monitoring temperature history during food processing, distribution, and storage is a simple, effective means to reduce the incidence of food poisoning. Interpretation of temperature profiles by computer programs based on predictive models allows informed decisions on the shelf life and safety of foods. In- or on-package temperature indicators require further development to accurately predict microbial behavior. We suggest a basis for a "universal" temperature indicator. This article emphasizes the need to combine kinetic and probability approaches to modeling and suggests a method to define the bacterial growth/no growth interface. Advances in controlling foodborne pathogens depend on understanding the pathogens' physiologic responses to growth constraints, including constraints conferring increased survival capacity.

Full Text

The Full Text of this article is available as a PDF (55.0 KB).

Selected References

These references are in PubMed. This may not be the complete list of references from this article.

  1. Alber S. A., Schaffner D. W. Evaluation of data transformations used with the square root and schoolfield models for predicting bacterial growth rate. Appl Environ Microbiol. 1992 Oct;58(10):3337–3342. doi: 10.1128/aem.58.10.3337-3342.1992. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Chen J., Griffiths M. W. Luminescent Salmonella strains as real time reporters of growth and recovery from sublethal injury in food. Int J Food Microbiol. 1996 Aug;31(1-3):27–43. doi: 10.1016/0168-1605(96)00941-5. [DOI] [PubMed] [Google Scholar]
  3. Clavero M. R., Beuchat L. R. Survival of Escherichia coli O157:H7 in broth and processed salami as influenced by pH, water activity, and temperature and suitability of media for its recovery. Appl Environ Microbiol. 1996 Aug;62(8):2735–2740. doi: 10.1128/aem.62.8.2735-2740.1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Csonka L. N. Physiological and genetic responses of bacteria to osmotic stress. Microbiol Rev. 1989 Mar;53(1):121–147. doi: 10.1128/mr.53.1.121-147.1989. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Dufrenne J., Delfgou E., Ritmeester W., Notermans S. The effect of previous growth conditions on the lag phase time of some foodborne pathogenic micro-organisms. Int J Food Microbiol. 1997 Jan;34(1):89–94. doi: 10.1016/s0168-1605(96)01170-1. [DOI] [PubMed] [Google Scholar]
  6. Genigeorgis C. A. Factors affecting the probability of growth of pathogenic microorganisms in foods. J Am Vet Med Assoc. 1981 Dec 15;179(12):1410–1417. [PubMed] [Google Scholar]
  7. Gill C. O., Greer G. G., Dilts B. D. The aerobic growth of Aeromonas hydrophila and Listeria monocytogenes in broths and on pork. Int J Food Microbiol. 1997 Mar 18;35(1):67–74. doi: 10.1016/s0168-1605(96)01224-x. [DOI] [PubMed] [Google Scholar]
  8. Ko R., Smith L. T., Smith G. M. Glycine betaine confers enhanced osmotolerance and cryotolerance on Listeria monocytogenes. J Bacteriol. 1994 Jan;176(2):426–431. doi: 10.1128/jb.176.2.426-431.1994. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Lee I. S., Lin J., Hall H. K., Bearson B., Foster J. W. The stationary-phase sigma factor sigma S (RpoS) is required for a sustained acid tolerance response in virulent Salmonella typhimurium. Mol Microbiol. 1995 Jul;17(1):155–167. doi: 10.1111/j.1365-2958.1995.mmi_17010155.x. [DOI] [PubMed] [Google Scholar]
  10. McMeekin T. A., Ross T. Shelf life prediction: status and future possibilities. Int J Food Microbiol. 1996 Nov;33(1):65–83. doi: 10.1016/0168-1605(96)01138-5. [DOI] [PubMed] [Google Scholar]
  11. Mitchell G. A., Brocklehurst T. F., Parker R., Smith A. C. The effect of transient temperatures on the growth of Salmonella typhimurium LT2. I: Cycling within the growth region. J Appl Bacteriol. 1994 Jul;77(1):113–119. doi: 10.1111/j.1365-2672.1994.tb03052.x. [DOI] [PubMed] [Google Scholar]
  12. Mitchell G. A., Brocklehurst T. F., Parker R., Smith A. C. The effect of transient temperatures on the growth of Salmonella typhimurium LT2. II: Excursions outside the growth region. J Appl Bacteriol. 1995 Aug;79(2):128–134. doi: 10.1111/j.1365-2672.1995.tb00925.x. [DOI] [PubMed] [Google Scholar]
  13. Shaw M. K. Effect of abrupt temperature shift on the growth of mesophilic and psychrophilic yeasts. J Bacteriol. 1967 Apr;93(4):1332–1336. doi: 10.1128/jb.93.4.1332-1336.1967. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Smith L. T. Role of osmolytes in adaptation of osmotically stressed and chill-stressed Listeria monocytogenes grown in liquid media and on processed meat surfaces. Appl Environ Microbiol. 1996 Sep;62(9):3088–3093. doi: 10.1128/aem.62.9.3088-3093.1996. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Emerging Infectious Diseases are provided here courtesy of Centers for Disease Control and Prevention

RESOURCES