Impact of microbial distributions on food safety I. Factors influencing microbial distributions and modelling aspects

Kinetics of migration of colloidal particles in meat muscles in the absence and presence of a proteolytic enzyme to simulate non-motile bacteria penetration

“…Possibly, cell count methods overestimated the presence of bacteria due to contamination occurring during sampling or growth leading to an overamplification upon plating. Alternatively, bacteria grow in clusters and cell separation could occur which lead to a more widespread distribution compared to colloidal particles (Jongenburger et al, 2012). In this context, one needs to also consider the complexity of processes involved in bacterial growth that may contribute to bacterial migration.…”

“…Furthermore, bacterial migration was found to be dependent on a great number of intrinsic and extrinsic factors, such as fiber orientation, hydration of meat proteins and the availability of pores and canals in the muscle tissue (Elmossalami & Wassef, 1971;Sikes & Maxcy, 1980;Thomas et al, 1987). Thus, if one reviews food science literature, it becomes apparent that there are many open questions regarding the distribution, location and pathways of bacteria in structured solid food, and in particular in muscle systems (Jongenburger, Bassett, Jackson, Zwietering, & Jewell, 2012;Wilson et al, 2002).…”

Use of quantitative microbial risk assessment when investigating foodborne illness outbreaks: The example of a monophasic Salmonella Typhimurium 4,5,12:i:− outbreak implicating beef burgers

“…The clustered spatial distribution could also be confirmed with the analysis of the variance and mean of the logarithm of observed numbers of Salmonella per portion. Indeed, Jongenburger et al (2012b) proposed that clustering can be quantified by the ratio variance/mean of the log numbers of observed microorganisms. Contamination is not "homogenous" when this ratio is above 6.…”

“…Contamination is not "homogenous" when this ratio is above 6. Jongenburger et al (2012b) recommended the use of a member of the family of generalised Poisson distributions (negative binomial or Poisson lognormal) to model microbial distributions in foods, especially to investigate spatial clustering. Negative binomial distribution was chosen to model contamination in beef burgers as this distribution "may be easier to apply in practice and is comparatively as appropriate as the Poisson-lognormal" (Jongenburger et al, 2012b).…”

“…Another explanation lies in the variability of the dose consumed, either by the amount of food consumed varying between individuals or through a heterogeneous distribution of the contaminant in the food matrix (Jongenburger et al, 2012a). Significant variability of exposure could also be explained by variations in the cooking process (ILSI Europe, 2010;Jongenburger et al, 2012b). The results of exposure assessment of burgers can exclude the heterogeneity of contamination between portions as a key element within the context of the community outbreak under consideration because each beef burgers consumed contained at least 1 MPN.…”