Estimating probability distributions of bacterial concentrations in food based on data generated using the most probable number (MPN) method for use in risk assessment

Food Control

Volumn 29, Issue 2, 2013, Pages 350-357

  Pouillot, Régis ^a   Hoelzer, Karin ^a   Chen, Yuhuan ^a   Dennis, Sherri ^a  

^a CENTER FOR DRUG EVALUATION AND RESEARCH   (United States)

Author keywords

Bacterial concentration; Likelihood; MPN; Probability distribution; Risk assessment

Indexed keywords

BACTERIA (MICROORGANISMS); LISTERIA MONOCYTOGENES;

EID: 84866986552     PISSN: 09567135     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodcont.2012.05.041     Document Type: Article

References (43)

1. Blodgett R.J. Serial dilution with a confirmation step. Food Microbiology 2005, 22(6):547-552.
2. Blodgett R.J. Does a serial dilution experiment's model agree with its outcome?. Model Assisted Statistics and Applications 2010, 5:209-215.
3. Buchanan R., Dennis S. Conduct of quantitative microbial risk assessments by U.S. Food and Drug Administration's Center for food safety and Applied Nutrition: Lessons learned 2002, Food and Drug Administration, College Park, MD, Available at, Accessed 28.11.11. pp. 6. http://foodrisk.org/default/assets/File/cqmra.pdf.
4. Busschaert P., Geeraerd A.H., Uyttendaele M., Van Impe J.F. Estimating distributions out of qualitative and (semi)quantitative microbiological contamination data for use in risk assessment. International Journal of Food Microbiology 2010, 138(3):260-269.
5. Busschaert P., Geeraerd A.H., Uyttendaele M., Van Impe J.F. Hierarchical Bayesian analysis of censored microbiological contamination data for use in risk assessment and mitigation. Food Microbiology 2011, 28(4):712-719.
6. Chase G.R., Hoel D.G. Serial dilutions - error effects and optimal designs. Biometrika 1975, 62(2):329-334.
7. Cochran W.G. Estimation of bacterial densities by means of the most probable number. Biometrics 1950, 6(2):105-116.
8. Codex alimentarius Commission Principles and guidelines for the conduct of microbiological risk assessment 1999, FAO Edition, Rome, Available at, Accessed 28.11.11. pp. 6. http://www.codexalimentarius.net/download/standards/357/CXG_030e.pdf.
9. Codex alimentarius Commission Principles and guidelines for the conduct of microbiological risk management (MRM) 2007, Available at, Accessed 28.11.11. http://www.codexalimentarius.net/web/more_info.jsp%3fid_sta%3d10741.
10. Codex alimentarius Commission Working principles for risk analysis for food safety for application by governments 2007, Available at, Accessed 28.11.11. http://www.codexalimentarius.net/web/more_info.jsp%3fid_sta%3d10751.
11. Commeau N., Cornu M., Albert I., Denis J.B., Parent E. Hierarchical Bayesian models to assess between- and within-batch variability of pathogen contamination in food. Risk Analysis 2012, 32(3):395-415.
12. Crepet A., Albert I., Dervin C., Carlin F. Estimation of microbial contamination of food from prevalence and concentration data: application to Listeria monocytogenes in fresh vegetables. Applied and Environmental Microbiology 2007, 73(1):250-258.
13. Cummins E., Nally P., Butler F., Duffy G., O'Brien S. Development and validation of a probabilistic second-order exposure assessment model for Escherichia coli O157:H7 contamination of beef trimmings from Irish meat plants. Meat Science 2008, 79(1):139-154.
14. Danyluk M.D., Schaffner D.W. Quantitative assessment of the microbial risk of leafy greens from farm to consumption: preliminary framework, data, and risk estimates. Journal of Food Protection 2011, 74(5):700-708.
15. Delignette-Muller M.L., Pouillot R., Denis J.B., Dutang C. Fitdistrplus: Help to fit of a parametric distribution to non-censored or censored data 2010, Available at, Accessed 28.11.11. http://cran.r-project.org/web/packages/fitdistrplus/fitdistrplus.pdf.
16. Endrikat S., Gallagher D., Pouillot R., Hicks Quesenberry H., Labarre D., Schroeder C.M., et al. A comparative risk assessment for Listeria monocytogenes in prepackaged versus retail-sliced Deli meat. Journal of Food Protection 2010, 73(4):612-619.
17. FAO/WHO Exposure assessment of microbiological hazards in food. Microbiological risk assessment series, no 7 2008, 92. Food and Agriculture Organization of the United Nations and World Health Organization, Rome.
18. FDA Bacteriological analytical manual 2010, College Park, MD. Available at, Accessed 28.11.11. http://www.fda.gov/Food/ScienceResearch/LaboratoryMethods/BacteriologicalAnalyticalManualBAM/default.htm.
19. FDA Bacteriological analytical manual (BAM) 2010, Appendix 2: Most Probable Number from Serial Dilutions. College Park, MD. Available at, Accessed 28.11.11. http://www.fda.gov/Food/ScienceResearch/LaboratoryMethods/BacteriologicalAnalyticalManualBAM/ucm109656.htm.
20. FDA/FSIS Quantitative assessment of relative risk to public health from Foodborne Listeria monocytogenes among selected categories of ready-to-eat foods 2003, Food and Drug Administration, United States Department of Agriculture, Center for Disease Control, Available at, Accessed 28.11.11 pp. 541. http://www.fda.gov/Food/ScienceResearch/ResearchAreas/RiskAssessmentSafetyAssessment/ucm183966.htm.
21. FSIS Salmonella Enteritidis risk assessment. Shell eggs and egg products 1998, United States Department of Agriculture - Food Safety Inspection Service, Available at, Accessed 28.11.11. http://www.fsis.usda.gov/ophs/risk/.
22. FSIS Comparative risk assessment for intact (non-tenderized) and non-intact (tenderized) beef: Technical report 2002, United States Department of Agriculture - Food Safety Inspection Service, Available at, Accessed 28.11.11. pp. 39. http://www.fsis.usda.gov/PDF/Beef_Risk_Assess_Report_Mar2002.pdf.
23. Garthright W.E. Bias in the logarithm of microbial density estimates from serial dilutions. Biometrical Journal 1993, 35(3):299-314.
24. Garthright W.E., Blodgett R.J. FDA's preferred MPN methods for standard, large or unusual tests, with a spreadsheet. Food Microbiology 2003, 20(4):439-445.
25. Gombas D.E., Chen Y., Clavero R.S., Scott V.N. Survey of Listeria monocytogenes in ready-to-eat foods. Journal of Food Protection 2003, 66(4):559-569.
26. Gonzales-Barron U., Butler F. Characterisation of within-batch and between-batch variability in microbial counts in foods using Poisson-gamma and Poisson-lognormal regression models. Food Control 2011, 22(8):1268-1278.
27. Gonzales-Barron U., Butler F. A comparison between the discrete Poisson-gamma and Poisson-lognormal distributions to characterise microbial counts in foods. Food Control 2011, 22(8):1279-1286.
28. Gonzales-Barron U., Kerr M., Sheridan J.J., Butler F. Count data distributions and their zero-modified equivalents as a framework for modelling microbial data with a relatively high occurrence of zero counts. International Journal of Food Microbiology 2010, 136(3):268-277.
29. Haas C.N. Estimation of microbial densities from dilution count experiments. Applied and Environmental Microbiology 1989, 55(8):1934-1942.
30. Haas C.N., Heller B. Test of the validity of the poisson assumption for analysis of most-probable-number results. Applied and Environmental Microbiology 1988, 54(12):2996-3002.
31. ILSI Impact of microbial distributions on food safety. Report series 2010, Brussels, Belgium. Available at, Accessed 28.11.11. http://www.ilsi.org/Europe/Publications/Microbial%20Distribution%202010.pdf, ILSI Europe risk analysis in food Microbiology Task Force Force (Ed.).
32. Kilsby D.C., Pugh M.E. The relevance of the distribution of micro-organisms within batches of food to the control of microbiological hazards from foods. Journal of Applied Microbiology 1981, 51(2):345-354.
33. Lorimer M.F., Kiermeier A. Analysing microbiological data: Tobit or not Tobit?. International Journal of Food Microbiology 2007, 116(3):313-318.
34. Nauta M. The Modular Process Risk Model (MPRM): a structured approach to food chain exposure assessment. Microbial risk analysis of foods 2008, ASM Press, Washington, D.C. D.W. Schaffner (Ed.).
35. Oscar T.P. A quantitative risk assessment model for Salmonella and whole chickens. International Journal of Food Microbiology 2004, 93(2):231-247.
36. Pouillot R., Delignette-Muller M.L. Evaluating variability and uncertainty separately in microbial quantitative risk assessment using two R packages. International Journal of Food Microbiology 2010, 142(3):330-340.
37. Pouillot R., Hoelzer K., Chen Y. Estimating distributions out of microbiological MPN data for use in risk assessment. Seventh International Conference on Predictive Modelling of food Quality and Safety - Conference Proceedings 2011, 226-229. UCD, DIT, Teagasc, Dublin, Ireland. E. Cummins, J.M. Frias, V.P. Valdramidis (Eds.).
38. Pouillot R., Miconnet N., Afchain A.L., Delignette-Muller M.L., Beaufort A., Rosso L., et al. Quantitative risk assessment of Listeria monocytogenes in French cold-smoked salmon: I. quantitative exposure assessment. Risk Analysis 2007, 27(3):683-700.
39. Salama I.A., Koch G.G., Tolley H.D. On the estimation of the most probable number in a serial dilution experiment. Communication in Statistics - Theory and Methods 1978, A7(13):1267-1281.
40. Waller L.A., Smith D., Childs J.E., Real L.A. Monte Carlo assessments of goodness-of-fit for ecological simulation models. Ecological Modelling 2003, 164(1):49-63.
41. WHO Food safety: About microbiological risk assessment (MRA) in food 2011, Available at, Accessed 28.11.11. http://www.who.int/foodsafety/micro/about_mra/en/index.html.
42. Worcester J. How many organisms?. Biometrics 1954, 10(2):227-234.
43. WTO Agreement on the application of sanitary and phytosanitary measures (SPS agreement) 1995, Available at, Accessed 28.11.11. http://www.wto.org/english/docs_e/legal_e/15-sps.pdf.