Quantitative Microbiology: A Basis for Food Safety

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...

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Main Authors: T. A. McMeekin, J. Brown, K. Krist, D. Miles, K. Neumeyer, D.S. Nichols, J. Olley, K. Presser, D. A. Ratkowsky, T. Ross, M. Salter, S. Soontranon
Format: Article
Language:English
Published: Centers for Disease Control and Prevention 1997-12-01
Series:Emerging Infectious Diseases
Subjects:
Online Access:https://wwwnc.cdc.gov/eid/article/3/4/97-0419_article
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spelling doaj-6b23695c048f496e98d1540d57d072432020-11-24T21:50:38ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60591997-12-013454154910.3201/eid0304.970419Quantitative Microbiology: A Basis for Food SafetyT. A. McMeekinJ. BrownK. KristD. MilesK. NeumeyerD.S. NicholsJ. OlleyK. PresserD. A. RatkowskyT. RossM. SalterS. SoontranonBecause 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.https://wwwnc.cdc.gov/eid/article/3/4/97-0419_articleAustralia
collection DOAJ
language English
format Article
sources DOAJ
author T. A. McMeekin
J. Brown
K. Krist
D. Miles
K. Neumeyer
D.S. Nichols
J. Olley
K. Presser
D. A. Ratkowsky
T. Ross
M. Salter
S. Soontranon
spellingShingle T. A. McMeekin
J. Brown
K. Krist
D. Miles
K. Neumeyer
D.S. Nichols
J. Olley
K. Presser
D. A. Ratkowsky
T. Ross
M. Salter
S. Soontranon
Quantitative Microbiology: A Basis for Food Safety
Emerging Infectious Diseases
Australia
author_facet T. A. McMeekin
J. Brown
K. Krist
D. Miles
K. Neumeyer
D.S. Nichols
J. Olley
K. Presser
D. A. Ratkowsky
T. Ross
M. Salter
S. Soontranon
author_sort T. A. McMeekin
title Quantitative Microbiology: A Basis for Food Safety
title_short Quantitative Microbiology: A Basis for Food Safety
title_full Quantitative Microbiology: A Basis for Food Safety
title_fullStr Quantitative Microbiology: A Basis for Food Safety
title_full_unstemmed Quantitative Microbiology: A Basis for Food Safety
title_sort quantitative microbiology: a basis for food safety
publisher Centers for Disease Control and Prevention
series Emerging Infectious Diseases
issn 1080-6040
1080-6059
publishDate 1997-12-01
description 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.
topic Australia
url https://wwwnc.cdc.gov/eid/article/3/4/97-0419_article
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