Characterisation of within-batch and between-batch variability in microbial counts in foods using Poisson-gamma and Poisson-lognormal regression models

Food Control

Volumn 22, Issue 8, 2011, Pages 1268-1278

  Gonzales Barron, Ursula ^a   Butler, Francis ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

Between batch; Distributions; Gamma; Lognormal; Microbial counts; Poisson gamma; Poisson lognormal; Sampling plan; Within batch

Indexed keywords

ESCHERICHIA COLI;

EID: 79953800520     PISSN: 09567135     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.foodcont.2011.01.028     Document Type: Article

References (17)

1. Anscombe F.J. The statistical analysis of insect counts based on the negative binomial distribution. Biometrika 1949, 5:165-173.
2. Augustin J.C., Minvielle B. Design of control charts to monitor the microbiological contamination of pork meat cuts. Food Control 2008, 19:82-97.
3. 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, 138:260-269.
4. Corradini M.G., Engel R., Normand M.D., Peleg M. Estimating the frequency of future high microbial counts in records with an actual or potential trend or periodicity. Journal of Food Science 2002, 67(4):1278-1285.
5. 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.
6. Gonzales-Barron U., Kerr M., Sheridan 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, 136:268-277.
7. Jarvis B. Statistical aspects of the microbiological examination of foods 2008, Elsevier, London. 2nd ed.
8. Kilsby D.C., Pugh M.E. The relevance of the distribution of microorganisms within batches of food to the control of microbiological hazards from foods. Journal of Applied Bacteriology 1981, 51:345-354.
9. Legan J.D., Vandeven M.H., Dahms S., Cole M.B. Determining the concentration of microorganisms controlled by attributes sampling plans. Food Control 2001, 12:137-147.
10. Marks H., Coleman M. Estimating distributions of numbers of organisms in food products. Journal of Food Protection 1998, 61(11):1535-1540.
11. Montgomery D.C. Statistical quality control: A modern introduction 2009, John Wiley & Sons, New Jersey. 6th ed.
12. Nauta M. Microbiological risk assessment models for partitioning and mixing during food handling. International Journal of Food Microbiology 2005, 100:311-322.
13. Paoli G., Hartnett M. Overview of a risk assessment model for Enterobacter sakazakii in powdered infant formula 2006, Available from, The Food and Agriculture Organization of the United Nations and the World Health Organization, FAO/WHO. http://www.who.int/foodsafety/micro/jemra/r_a_overview.pdf.
14. Smelt J.P., Quadt J.F. A proposal for using previous experience in designing microbiological sampling plans based on variables. Journal of Applied Bacteriology 1990, 69:504-511.
15. So P.M. Distribution patterns and sampling plans for Tetranychus urticae Koch (Acarina: Tetranychidae) on roses. Research Population Ecology 1991, 33:229-245.
16. Van Schothorst M., Zwietering M.H., Ross T., Buchanan R.L., Cole M.B. Relating microbiological criteria to food safety objectives and performance objectives. Food Control 2009, 20:967-979.
17. Whiting R.C., Rainosek A., Buchanan R.L., Miliotis M., LaBarre D., Long W., et al. Determining the microbiological criteria for lot rejection from the performance objective or food safety objective. International Journal of Food Microbiology 2006, 110:263-267.