Jeanne-Marie Membre

Microbiological Risk Assessment Associated with the Food Processing and Distribution Chain


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(2009).

      Clostridium botulinum is one of the most serious hazards considered in food safety. There are well-established control procedures that have been identified to destroy or inhibit the growth of non-proteolytic spores of C. botulinum. One of these, used in the manufacture of refrigerated foods, is the application of “non-proteolytic C. botulinum cooking”, based on the fact that spores from non-proteolytic strains are considerably more heat-sensitive than spores from proteolytic strains. It is thus accepted that a temperature of 90°C for 10 minutes results in an inactivation of 6 log 10 of non-proteolytic C. botulinum (Gould 1999) and this rule is commonly used for the thermal processing of refrigerated foods. However, in order to maintain the texture and flavor of refrigerated products such as vegetable puree, it is possible to try to drop below this bar (“safe harbor”) of 90°C for 10 mins. In this case, some spores of C. botulinum could survive. However, under stress conditions provided by intrinsic factors (e.g. pH) or extrinsic factors (e.g. storage at refrigerated temperatures), the surviving heat-treated spores require some time (referred to here as the “latency period”) before they recover from their injury, germinate and start to develop.

      The objective of this study was therefore to explore the possibility of identifying heat treatments milder than 10 minutes at 90°C, integrating this latency time with the classic thermal inactivation effect. An exposure assessment model, based on the concept of the DoP, was developed.

      with ΔR being the decimal reduction due to thermal inactivation and ThI the DoP due to thermal stress. Both are expressed as the decimal logarithm of the reciprocal of a probability:

      [1.2]image

      [1.3]image

      Pr indicates the probability that a spore will survive thermal treatment and Pi the probability that the latency period will be shorter than the SL:

      Once the model has been built, the results can be set out in two ways. The first is to present the DoP, including thermal inactivation and stress, for different processes, formulations (pH and aw) and refrigerated storage conditions at different shelf lives.

      The second is to choose a targeted level of protection and present the model results as a set of combinations of processes, formulations, storage conditions and SLs that achieve that target protection. This second presentation of the results can be compared to an isoprobability method, because the DoPs are derived from probability calculations. The second approach was the one chosen in this study. An overall DoP of 6 was chosen because it is a reference value currently applied in the management of food safety, in the form of inactivation (Gould 1999). Work by Membré et al. (2009), which led to this approach, along with bibliographical references and a number of illustrations are presented in the Appendices.

      A Web of Science search (January 2021) using the query “TITLE: (hazard AND identification) AND TOPIC: (microbial OR microbiological OR microorganism*)” first of all revealed the very small number of scientific articles in the field of hazard identification. Indeed, since 1950, there have been only 61 articles which directly address (in the sense that the keywords are in the title) the topic of microbiological hazard identification.

      Hazard identification was most often done as part of HACCP systems or risk (or exposure) assessment, which is consistent with what has already been said in section 1.2. Finally, the articles reporting on molecular approaches were published from 2015. The two cited (Franz et al. 2015; Pielaat et al. 2015) were identified in the literature search because the term “hazard identification” was in the title of the article, but there are other articles that deal with the use of molecular methods and in particular with WGS in hazard identification; see, for example, the review by Rantsiou et al. (2018).

      As noted in the Introduction, hazard identification is the first step in microbiological risk assessment. This chapter does not develop examples; they are merely provided to illustrate the process. The reader is invited to consult the first book in this series (Haddad 2022) to see numerous examples of hazard identification.

Title of publication Reference Publication Year Scope
Hazard identification in swine slaughter with respect to foodborne bacteria Borch et al. (1996) 1996 Application of hazard identification
Live bacterial vaccines – A review and identification of potential hazards Detmer and Glenting (2006) 2006 Application of hazard identification
An approach to reduction of salmonella infection in broiler chicken flocks through intensive sampling and identification of cross-contamination hazards in commercial hatcheries Davies and Wray (1994) 1994 Food safety management
A comparison between broiler chicken carcasses with and without visible fecal contamination during the slaughtering process on hazard identification of Salmonella spp. Jimenez et al. (2002) 2002