The year 2022 has been a significant one for all things Salmonella related. With the recent USDA announcement classifying Salmonella as an adulterant in breaded and stuffed raw chicken products when exceeding 1 colony-forming unit (CFU) per gram, as well as the selection of a new Salmonella testing method of choice for USDA-Food Safety Inspection Service laboratories, there seems to be an increased interest from the poultry industry in how biomapping data can enhance statistics-based process control from flock to fork. The process of quantifying pathogens and microbial indicators, i.e., biomapping, has been described as an effective tool for process control, as it can highlight the effective interventions, provide a real-time status of the health of the process, and, ultimately, allow for risk-based decision making.
Despite many interventions over the past 20 years, the number of Salmonella incidences has not decreased significantly. This has been attributed to various factors but, when we look at available testing approaches, there are a few things to keep in mind, no matter what your method of choice is:
- Testing alone will never reduce the prevalence or quantity of Salmonella. The old saying that you cannot test your way to food safety remains true. A single test is unable to provide a full view of the information needed to identify points of concern within the production process. Furthermore, the testing data must be analyzed within the context of process metadata.
- Your method of choice must accompany a statistically valid sampling plan. This is the only way to ensure that your statistical process control programs are working properly.
- Don’t run microbiology tests if you don’t have a plan for the data. Otherwise, you’re wasting time and money. Data produced from tests help you understand gaps in your process and enable decision making about what tools are needed to address concerns.
Biomapping helps processors monitor the efficacy of antimicrobial interventions by sampling at critical control points (CCPs) where contamination levels can be assessed. When implemented accurately, biomapping can help to:
- Improve processors’ understanding of the antimicrobial interventions efficacy;
- Provide a holistic view of the process while providing deeper insights through monitoring CCPs; and
- Ultimately, improve the microbiological quality of processors’ products through better process controls.
Biomapping of CCPs allows for continuous improvements including improved risk assessments of the overall production process. If you don’t have a biomapping element in your testing process, you can incorporate one into existing protocols by identifying CCPs where contamination challenges are evident by existing microbial indicator data.
Biomapping via quantification of non-pathogenic microbes has long been a way to perform sanitation verification or biomapping. More recently, though, the tools for quantification have evolved from the use of indicator organisms to a more specific Salmonella quantification, and the quantification technology has evolved to more precise quantitative (q) PCR. As it stands today, this combination of indicator and Salmonella quantification remains the most potent way to understand the microbial makeup and load of the process. Also, with the availability of the qPCR technology, this trend of specific pathogen quantification is likely going to intensify via better use of data, and a potential expansion to include other pathogens of interest.
As is the case in our technology-driven world, however, all methods are not created equal, and technology advancements happen faster than we can keep up with them. Existing microbial quantification options have their drawbacks: Direct counting (optical microscopy) has a limited application, most probable number (MPN) is cumbersome and expensive, and direct plating does not offer a high certainty that a contaminant is Salmonella and therefore requires confirmation. The emergence of qPCR technologies, with or without enrichment, can correlate inversely with target DNA fragments, allowing for a validation on a per matrix basis (i.e., carcass versus parts versus ground) and decision making in a time bound manner. While biomapping remains a viable means of process improvement, the end will, and should, remain with how we leverage the data for improving our processes.