191
Views
1
CrossRef citations to date
0
Altmetric
Review Articles

The probability of bacterial spores surviving a thermal process: The 12D myth and other issues with its quantitative assessment

References

  • Awuah, G. B., H. S. Ramaswamy, and A. Economides. 2007. Thermal processing and quality: Principles and overview. Chemical Engineering and Processing: Process Intensification 46 (6):584–602. doi: 10.1016/j.cep.2006.08.004.
  • Buzrul, S. 2022. The Weibull model of microbial inactivation. Food Engineering Reviews 14 (1):45–61. doi: 10.1007/s12393-021-09291-y.
  • Casolari, A. 1988. Microbial death. In Physiological models in microbiology, ed. M. J. Bazin, J. Prosser, and M. J. Bazin, vol. 2, 1–44. Boca Raton: CRC Press.
  • Cerf, O. 1977. Tailing of survival curves of bacterial spores. The Journal of Applied Bacteriology 42 (1):1–19. doi: 10.1111/j.1365-2672.1977.tb00665.x.
  • Chen, G., and O. H. Campanella. 2012. An optimization algorithm for estimation of microbial survival parameters during thermal processing. International Journal of Food Microbiology 154 (1-2):52–8. doi: 10.1016/j.ijfoodmicro.2011.12.019.
  • Chick, H. 1908. An investigation of the laws of disinfection. Epidemiol. Infect 8:92–153.
  • Corradini, M. G., M. D. Normand, and M. Peleg. 2008. Prediction of an organism’s inactivation patterns from three single survival ratios determined at the end of three non-isothermal heat treatments. International Journal of Food Microbiology 126 (1-2):98–111. doi: 10.1016/j.ijfoodmicro.2008.05.007.
  • Corradini, M. G., M. D. Normand, and M. Peleg. 2010. Stochastic and deterministic model of microbial heat inactivation. Journal of Food Science 75 (2):R59–R70. doi: 10.1111/j.1750-3841.2009.01494.x.
  • Corradini, M. G., M. D. Normand, C. Newcomer, D. W. Schaffner, and M. Peleg. 2009. Extracting survival parameters from isothermal, isobaric and ‘iso-concentration’ inactivation experiments by the ‘three end points method. Journal of Food Science 74 (1):R1–R11. doi: 10.1111/j.1750-3841.2008.00980.x.
  • Corradini, M. G., M. D. Normand, M. Eisenberg, and M. Peleg. 2010. Evaluation of a stochastic inactivation model for heat-activated spores of Bacillus spp. Applied and Environmental Microbiology 76 (13):4402–12. doi: 10.1128/AEM.02976-09.
  • Doona, C. J., F. E. Feeherry, K. Kustin, H. Chen, R. Huang, X. P. Ye, and P. Setlow. 2017. A quasi-chemical model for bacterial spore germination kinetics by high pressure. Food Engineering Reviews 9 (3):122–42. doi: 10.1007/s12393-016-9155-1.
  • Eisner, M. D. 2021. Direct and indirect heating of milk: A technological perspective beyond time-temperature profiles. International Dairy Journal 122:105145. doi: 10.1016/j.idairyj.2021.105145.
  • Geeraerd, A. H., V. P. Valdramidis, J., and F. Van Impe. 2005. GinaFiT, a freeware tool to assess non-loglinear microbial survival curves. International Journal of Food Microbiology 102 (1):95–105. doi: 10.1016/j.ijfoodmicro.2004.11.038.
  • Halder, A., D. G. Black, P. M. Davidson, and A. Datta. 2010. Development of association and kinetic models for microbiological data to be used in comprehensive food safety prediction software. Journal of Food Science 75 (6):R107–R120. doi: 10.1111/j.1750-3841.2010.01687.x.
  • Horowitz, J., M. D. Normand, M. G. Corradini, and M. Peleg. 2010. A probabilistic model of growth, division and mortality of microbial cells. Applied and Environmental Microbiology 76 (1):230–42. doi: 10.1128/AEM.01527-09.
  • Koyama, K., H. Hiroki, S. Kawamura, and S. Koseki. 2019. Calculating stochastic inactivation of individual cells in a bacterial population using variability in individual cell inactivation time and initial cell number. Journal of Theoretical Biology 469:172–9. doi: 10.1016/j.jtbi.2019.01.042.
  • Koyama, K., H. Hokunan, M. Hasegawa, S. Kawamura, and S. Koseki. 2017. Modeling stochastic variability in the number of surviving Salmonella enterica, Enterohemorrhgic Escherichia coli and Listeria monocytogenes cells at single-cell level in a desiccated environment. Applied and Environmental Microbiology 83 (4):4–16. doi: 10.1128/AEM.02974-16.
  • Mafart, P., O. Couvert, S. Gaillard, and I. Leguerinel. 2002. On calculating sterility in thermal preservation methods: Application of the Weibull frequency distribution model. International Journal of Food Microbiology 72 (1-2):107–13. doi: 10.1016/S0168-1605(01)00624-9.
  • Peleg, M. 2006. Advanced quantitative microbiology for food and biosystems: Models for predicting growth and inactivation. Boca Raton, FL: CRC Press.
  • Peleg, M. 2017. Modeling microbial inactivation by pulsed electric fields. In Handbook of electroporation, ed. D. Miklavcic, 1269–86. Switzerland: Springer.
  • Peleg, M. 2020. Endpoints method for predicting microbial inactivation, nutrients degradation and quality loss at high and ultra-high temperatures. In Food safety engineering, ed. A. Demirci, H. Feng, and K. Krishnamurthy, 421–46. USA: Springer.
  • Peleg, M. 2021. The thermal death time concept and its implications revisited. Food Engineering Reviews 13 (2):291–303. doi: 10.1007/s12393-021-09279-8.
  • Peleg, M. 2023. Fully probabilistic microbial inactivation models: The Markov chain reconstruction from experimental survival ratios. Food Engineering Reviews. 15: doi: 10.1007/s12393-022-09325-z.
  • Peleg, M., and M. B. Cole. 1998. Reinterpretation of microbial survival curves. Critical Reviews in Food Science and Nutrition 38 (5):353–80. doi: 10.1080/10408699891274246.
  • Peleg, M., M. D. Normand, and M. G. Corradini. 2005. Generating microbial survival curves during thermal processing in real time. Journal of Applied Microbiology 98 (2):406–17. doi: 10.1111/j.1365-2672.2004.02487.x.
  • Peleg, M., M. D. Normand, M. G. Corradini, A. J. van Asselt, P. de Jong, and P. F. ter Steeg. 2008. Estimating the heat resistance parameters of bacterial spores from their survival ratios at the end of UHT and other heat treatments. Critical Reviews in Food Science and Nutrition 48 (7):634–48. doi: 10.1080/10408390701724371.
  • Rana, Y. S., L. Chen, V. M. Balasubramaniam, and A. B. Snyder. 2022. Superheated steam effectively inactivates diverse microbial targets despite mediating effects from food matrices in bench-scale assessments. International Journal of Food Microbiology 378:109838. doi: 10.1016/j.ijfoodmicro.2022.109838.
  • Ruiz, V., R. Alonso, M. Salvador, S. Condon, and S. Condon-Banto. 2021. Impact of shoulders on the calculus of heat sterilization treatments with different bacterial spores. Food Microbiology 94:103663. doi: 10.1016/j.fm.2020.103663.
  • Scanlon, K. A., U. Tiwari, C. Cagney, D. Walsh, D. A. McDowel, and G. Duffy. 2015. Modelling the thermal inactivation of five Campylobacteraceae species. Food Control 47:135–40. doi: 10.1016/j.foodcont.2014.06.042.
  • Smelt, J. P. M, and S. Brul. 2014. Thermal inactivation of microorganisms. Critical Reviews in Food Science and Nutrition 54 (10):1371–85. doi: 10.1080/10408398.2011.637645.
  • Toledo, R. T., R. K. Singh, and F. Kong. 2018. Fundamental of food processing Engineering. 4th ed. Switzerland: Springer International Publishing.
  • Tucker, G., and S. Featherstone. 2021. Essential of thermal processing. 2nd ed. UK: Wiley & Sons.
  • Van Boekel, M. S. 2002. On the use of the Weibull model to describe thermal inactivation of microbial vegetative cells. International Journal of Food Microbiology 74 (1-2):139–59. doi: 10.1016/s0168-1605(01)00742-5.
  • Van Boekel, M. S., P. F. ter Steeg, and A. E. Dahoe. 2020. Co-optimization of safety, quality and legislation: Opening Pandora’s box? Current Opinion in Food Science 36:65–71.
  • Van Zuijlen, A., P. M. Periago, A. Amezquita, A. Palop, S. Brul, and P. S. Fernandez. 2010. Characterization of Bacilus sporothermoduranns IC4 spores; putative indicator microorganism for optimization of thermal processes in food sterilization. Food Research International 43 (7):1895–901. doi: 10.1016/j.foodres.2009.11.011.
  • Warda, A. K., H. M. den Besten, N. Sha, T. Abee, and M. N. Nierop Groot. 2015. Influence of food matrix on outgrowth heterogeneity of heat damaged Bacillus cereus spores. International Journal of Food Microbiology 201:27–34. doi: 10.1016/j.ijfoodmicro.2015.02.010.
  • Zwietering, M. H., A. Garre, M. Wiedmann, and R. L. Buchanan. 2021. All food processes have a residual risk, some are small, some very small and some are extremely small: Zero risk does not exist. Current Opinion in Food Science 39:83–92. doi: 10.1016/j.cofs.2020.12.017.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.