“The plant owner had done a good job collecting cooler and carcass time and temperature data,” she says. “Professor Ingham plugged the data into THERM, which predicted that neither Salmonella nor E. coli O157:H7 had gone into growth phase. The plant owner printed the graph and presented it to his inspector as validation that the carcasses were still safe, even though a deviation from a critical limit had occurred.
Using THERM was quick, based on scientifically validated parameters, and straightforward in its reported information. Any tool that works this well makes the regulatory/industry partnership less stressful, with both sides working toward a common goal of food safety, and should be used whenever possible.”
Predictive microbiology and HACCP have been intertwined from the start. With further development, refinement, and validation, we should soon see wider acceptance of validated predictive microbiology tools to enhance HACCP systems, thus ensuring the safety of the consumer and the nation’s food supply using 21st-century tools.
The authors would like to acknowledge the efforts of Christopher Doona, PhD; Cheryl Baxa, PhD; and Lt. Col. Timothy Stevenson, DVM, PhD for their review of, and contributions to, this article.
Dr. Burnham is veterinary liaison, combat feeding directorate, at the U.S. Army’s Natick Soldier Research, Development, and Engineering Center. Reach him at greg.burnham@us.army.mil. Dr. Schaffner is a professor and food science extension specialist at Rutgers, The State University of New Jersey. Reach him at schaffner@aesop. rutgers.edu. Dr. Ingham is a professor and food safety extension specialist at the University of Wisconsin-Madison. Reach him at scingham@wisc.edu.
RESOURCES
- Burnham GM, Ingham SC, Fanslau MA, et al. Using predictive microbiology to evaluate risk and reduce economic losses associated with raw meats and poultry exposed to temperature abuse. United States Army Medical Department. AMEDD Journal. 2007;PB8-07-7/8/9:57-65.
- Doona CJ, Feeherry FE, Ross EW. A quasi-chemical model for the growth and death of microorganisms in foods by non-thermal and high-pressure processing. Int J Food Microbiol. 2005;100(1):21-32.
- Ingham SC, Fanslau MA, Burnham GM, et al. Predicting pathogen growth during short-term temperature abuse of raw pork, beef, and poultry products: use of an isothermal-based predictive tool. J Food Prot. 2007;70:1446-1456.
- McDonald K, Sun DW. Predictive food microbiology for the meat industry: a review. Int J Food Microbiol. 1999;52:1-27.
- McKellar RC, Lu X. Modeling Microbial Responses in Food. Boca Raton, Fla.: CRC Press; 2004.
- McMeekin TA, Olley JN, Ross T, et al. Predictive Microbiology: Theory and Application. Taunton, U.K.: Research Studies Press Ltd; 1993.
- National Academy of Sciences. An evaluation of the role of microbiological criteria for foods and food ingredients. Washington, D.C.: National Academies Press; 1985. Available at: www.nap.edu/openbook.php?isbn=030 9034973. Accessed March 11, 2008.
- Peleg M. Advanced Quantitative Microbiology for Foods and Biosystems. Boca Raton, Fla.: CRC Press; 2006.
- United States Department of Agriculture, Food Safety & Inspection Service. Pathogen Reduction; Hazard Analysis and Critical Control Point (HACCP) Systems; Final Rule.10. United States Department of Agriculture, Food Safety and Inspection Service.
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