Predict Safety

The United States Department of Agriculture’s (USDA) Agricultural Research Service’s Pathogen Modeling Program (PMP) is probably the most recognized predictive microbiology tool in the United States. The PMP is a tertiary model that can be used to predict the growth or inactivation of a number of foodborne pathogens exposed to combinations of specific environmental (temperature, pH, sodium nitrite concentration, and so on) or processing (heat/irradiation) conditions. Most PMP predictions are based on microbial responses observed experimentally in sterile laboratory growth media and not in a specific food, however, a shortcoming identified in reviews on predictive microbiology. Some other limitations of PMP: most of its models are isothermal based, and it may not be easy to use or interpret for those who have not been indoctrinated.

A similar tool, the Institute of Food Research’s (Norwich, U.K.) ComBase Predictor (www.combase.cc/), is also based on microbial behavior in liquid microbiological media and can be difficult to use and interpret. The ComBase database, however, offers an extensive resource for experimentally observed microbial responses in food environments. A recently developed tertiary model, THERM v.2 (Temperature History Evaluation of Raw Meat, www.meathaccp.wisc.edu/THERM/calc.aspx), has addressed some of these limitations for predicting Escherichia coli O157:H7, Salmonella serovars, and Staphylococcus aureus behavior in raw beef, pork, and poultry.

This tool is only applicable, however, to raw meat products that contain no ingredients that might inhibit pathogen growth, such as salt or sodium nitrite. Many other tools are available to predict microbial responses in food, including the Seafood Spoilage and Safety Predictor, made available by the Danish Institute for Fisheries Research and the Technical University of Denmark, which can predict the shelf life of seafood at constant or changing temperatures.

Validating HACCP Systems

When using predictive microbiology tools to support HACCP systems, predictions of microbial behavior made by tools must be validated with experimental observations of microbial behavior in the given food system. Although this validation has its own unique set of inherent difficulties, it is important to make these observations whether one is validating predictions from food-specific tools, like THERM v.2, or predictions from the often more conservative laboratory media-based tools.

HACCP arrived in the early 1960s during a collaboration between the Pillsbury Company, U.S. Army Natick Laboratories, and the U.S. Air Force Space Laboratory Project Group, in cooperation with the National Aeronautics and Space Administration, to develop rations for the U.S. space program. HACCP as a widely accepted food safety system gained momentum when the National Academy of Sciences published “An evaluation of the role of microbiological criteria for foods and food ingredients” in 1985. In 1988, the National Advisory Committee on Microbiological Criteria for Foods published their HACCP principles. These principles included conducting a hazard analysis, establishing critical control points, setting critical limits, monitoring those limits, establishing corrective actions for deviations, verifying that the system is working, and documenting all appropriate procedures and records.

The first regulatory mandates for HACCP came from the Food and Drug Administration (FDA) in their low-acid canned food regulations and seafood HACCP regulations. But HACCP truly arrived in the food industry in 1996, when the USDA adopted the “Pathogen Reduction; HACCP Systems; Final Rule,” which required that all meat and poultry processors use HACCP as their main food safety system.

Predictive microbiology tools are useful in several parts of HACCP systems, including in the areas of conducting a thorough hazard analysis, providing scientifically valid information in establishing critical limits at critical control points, and evaluating system deviations (corrective actions). Let’s consider some examples. The first two are brief and hypothetical, but they help illustrate predictive microbiology’s potential influence on HACCP systems. The third example is a more detailed description of an actual process deviation in which the use of predictive microbiology tools might have reduced the economic burden.