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Chapter 3 : Microbial Ecology in Food Safety Risk Assessment

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Microbial Ecology in Food Safety Risk Assessment, Page 1 of 2

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Abstract:

The health risks associated with food-and water-borne microbiological hazards are influenced by a complex interplay of variable factors. In this chapter, risk is assumed to relate directly to risk to human health, considering the probability and severity of illness both to individuals and the overall population exposed. The effect of microorganisms is related more to their number than their size, and microbiologists typically think in terms of populations of microbes. It might be expected that development of reliable microbial food safety risk assessments will require a sound understanding of the microbial ecology of foods and the ability to express that understanding mathematically. Microbial hazards in foods can be extremely sensitive to their surroundings and, under some conditions, the microbial ecology of foods has characteristics of a chaotic system. The microbial ecology of foods is deterministic and much is known that can be applied to microbial food safety risk assessment to increase the scientific credibility and utility of risk assessment outcomes. The chapter summarizes knowledge of the deterministic aspects of microbial ecology of foods that is relevant to the conduct of microbial food safety risk assessment; highlights sources of variability and uncertainty in microbial behavior; reviews approaches that have been adopted to model microbial growth, stasis, and death along the farm-to-fork pathway, and identifies sources of information that can assist microbial food safety risk assessors to produce models that are more scientifically rigorous and thus defensible. It discusses five main groups of microorganisms which include algae, fungi, protozoans, bacteria, and viruses.

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3

Key Concept Ranking

Microbial Ecology
0.9669089
Food Microbiology
0.9252071
Food Safety
0.58374804
Quantitative Risk Assessment
0.57943714
Meat and Meat Products
0.498792
Viruses
0.4752727
Risk Assessment
0.47526023
Chemicals
0.448145
0.9669089
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Figures

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Figure 1

Patterns of microbial population inactivation kinetics. The underlying responses are believed to be log-linear (a proportion of the population is killed per unit of time) as shown by the solid heavy line, but variations in which (i) the rate of inactivation declines with time (“tailing,” shown by the light dashed line) or (ii) there is an initially slow rate followed by a more rapid, log-linear inactivation “shoulders” (heavy dashed line) are also commonly reported. Yet more complex kinetics may also been seen (faint, solid line; dotted line).

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3
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Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3
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Figure 2

Microbial population growth curve in a closed system, e.g., a unit of food, showing the generally recognized stages of “batch” population growth.

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3
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Figure 3

(a) Diagram illustrating the effects on microbial growth rate of two factors (temperature and water activity). The figure also illustrates the concept of the growth/no-growth boundary (dotted line) where the combination of factors at suboptimal levels eventually prevents growth. In the figure, the darker shaded areas represent regions of faster growth, while lighter shaded regions represent regions of slower growth. The rate of change of growth rate due to environmental conditions is not a constant, e.g., growth rate declines more quickly at temperatures above the optimum for growth than below. (b) An example of experimental data describing the water activity and temperature growth/no-growth interface for .

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3
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Figure 4

The coevolution of populations of total viable aerobic count (∎), lactic acid bacteria (▲), and ( ) in ham inoculated with and lactic acid bacteria. Error bars denote standard deviations of triplicate samples. In the upper figure, the level of is 100 times greater than that in the lower figure. Growth of the population of s in either trial appears to cease when the total viable count achieves stationary phase. This is an illustration of the Jameson effect (F. Birrell, L. A. Mellefont, and T. Ross, unpublished data).

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3
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References

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Tables

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Table 1

Food-borne parasites

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3
Generic image for table
Table 2

Food-borne bacterial pathogens

Citation: Ross T. 2008. Microbial Ecology in Food Safety Risk Assessment, p 51-97. In Schaffner D, Doyle M (ed), Microbial Risk Analysis of Foods. ASM Press, Washington, DC. doi: 10.1128/9781555815752.ch3

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