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Food manufacturers: Is something missing in your hygiene monitoring program?

A white conveyor belt moves pierogies along in a food processing plant.

Establishing and maintaining a robust hygiene monitoring program can be challenging. However, consider these three questions to help evaluate the current status of your program and identify opportunities for continuous improvement:

  • Which test methods are used to evaluate cleaning and sanitation?
  • How are test points selected?
  • How are pass and fail limits for each test point established?

Three test methods—used together.

Three test methods—visual inspection, adenosine triphosphate (ATP) testing and microbiological testing—play different, critical roles in the hygiene monitoring and management process.

Visual Inspection can provide initial feedback about effectiveness of cleaning. However, this method has limitations because microscopic levels of contamination cannot be seen by the human eye. Therefore, visual inspection is used prior to ATP testing and microbiological testing but cannot be considered a substitute for them.

ATP testing quickly and easily verifies whether biological material, such as food residue, micro-organisms, or soil, have been effectively cleaned from a surface or test point. Because results are obtained in real time, ATP testing can be used to help determine whether food manufacturing can begin or show that re-cleaning and re-testing should be repeated before food processing continues.

Microbiological testing can detect the presence of specific microorganisms that could negatively impact the quality and safety of manufactured food. While this approach requires at least one to two days of incubation to produce results, it can provide data to support that cleaning and sanitation methods are effective. It can also help identify areas and opportunities where your sanitation program can be improved.

Because visual inspection, ATP testing and microbiological testing provide complementary information, a robust hygiene monitoring program should utilize all three methods, in combination.

Test point selection using risk analysis.

A graphic shows a green gloved hand swabbing a grey striped surface.

Select test points using a risk analysis-based approach by evaluating the risk and probability of a hazard occurring at those points, based on these four factors:

  • proximity to food
  • potential for cross-contamination
  • accessibility for cleaning and testing
  • equipment age, substrate and condition

Proximity to food: Areas where food is exposed to the environment are considered higher risk and may require more frequent testing. The food industry generally uses four zones to identify the proximity of a test point to food:

  • Zone 1: food contact surfaces, posing a higher risk for contamination
  • Zone 2: non-food contact surfaces in close proximity to food
  • Zone 3: more remote non-food contact surfaces
  •  Zone 4: non-food contact surfaces outside the food processing areas, posing a lower risk

Potential for cross-contamination: Various causes of cross-contamination in food may include condensation in a humid environment, equipment positioned above product production and multiple operators using the same equipment.

Accessibility for cleaning and testing: A flat surface will be much easier to clean (low risk) than a piece of equipment that must be disassembled before it can be cleaned (high risk).

Equipment age, substrate and condition: Equipment age and the condition of the surface to be tested can affect risk. Examples that may pose higher risk include equipment that is older or has been relocated, damaged or recommissioned, possibly causing surfaces to become scratched, porous or damaged.

Once each test point has been selected, you should also consider how likely it is that risk might occur. A risk assessment matrix (see Figure 1) can be used to compare the severity associated with a surface being contaminated (high, medium or low) versus the probability of a risk occurring if it were to be contaminated.

Regardless of the food or beverage produced, a risk-based approach should become the foundation of a test point selection and evaluation process.

Figure 1:

Risk-based approach

Defining pass and fail limits.

Pass and fail limits should be established for visual inspection, ATP testing and microbiological testing. These define the minimal limits that cleaning, and sanitation should achieve for each test method used in your manufacturing plant.

These limits should be monitored regularly to ensure they continually reflect the expected cleaning and sanitation results, while allowing for ongoing improvement of cleaning and sanitation in your operation.

To achieve passing results, a visual check must confirm that all soil and biological material have been successfully removed from a surface. For clean-in-place (CIP), equipment, the final rinse water should be visibly free of residue.

Pass and fail limits for ATP testing will be the achievable level of cleanliness for a surface or a piece of equipment. Establishing these limits involves collection of a minimum of 30 results for each test point to first determine a statistically valid baseline. After cleanings, test results are compared to these established limits. When failures occur, those test locations should be re-cleaned and re-tested before production continues.

Pass and fail limits for microbiological tests can be established in several ways, including using established baseline levels, historical data or using specific industry guidance available. Limits will vary based on the types of food being manufactured, target organism of interest, sampling locations and the timing of sampling, following cleaning or sanitation.

There will also be situations in which these established limits might be modified, such as following a repair or change in processes impacting the equipment cleanability, changes to manufacturing processes, or as part of a continuous improvement program.

Using data to optimize your processes.

Woman working on a line.

Tracking and trending test results can help you prepare for scheduled and unplanned audits, as well as help optimize your processes and use of resources with the desired goal of continuous improvement. An automated hygiene monitoring and management system can help you efficiently collect, store and analyze new data plus use data you have already collected and turn it into actionable information.

For instance, an automated system can easily identify trends in failures (e.g., times of day or during particular work shifts), and highlight concerns that may require immediate attention. The results can also show whether your corrections and corrective actions have been effective.

A framework for testing.

To develop a framework in which both ATP testing and microbiological testing could be utilized by a variety of food manufacturing facilities, the Cornell University Department of Food Science and 3M Food Safety conducted a multi-phase study in a ready-to-eat (RTE) food manufacturing facility using the 3M™ Clean-Trace™ Hygiene Monitoring and Management System and 3M™ Petrifilm™ Plates. Findings of the study have been published in the peer-reviewed journal, Applied and Environmental Microbiology, Vol. 87 No. 5.2

Results showed a relationship between effective equipment surface cleaning and sanitation, and improvements in the facility’s environmental hygiene and the microbiological quality of the food produced. As the facility became cleaner, fewer failing test results occurred, which enabled testing to be decreased while still keeping the cleaning and sanitation process under control.

The 3M™ Clean-Trace™ Hygiene Monitoring Software helped facilitate data collection and analysis during the study. It also helped identify and justify opportunities for improvements in cleaning and sanitation.

Strengthen your program and drive continuous improvement.

Coming soon: 3M Food Safety assessment to understand key topics that can help mitigate risk and provide valuable insights for improving your hygiene monitoring program.



1: 3M. 2019. 3M Cornell Environmental Monitoring Handbook for the Food and Beverage Industries.

2: Sogin JH, Lopez-Velasco G, Yordem B, Lingle CK, David JM, Çobo M, Worobo RW. 2021. Implementation of ATP and microbial indicator testing for hygiene monitoring in a tofu production facility improves product quality and hygienic conditions of food contact surfaces: a case study. Appl Environ Microbiol 87:e02278-20.

About the Author

[enBio=Former Research Scientist, Daniel holds a Ph.D. in Microbiology from University Paris France and has over 10 years of experience working in Microbiology and Molecular Biology in a laboratory setting. Daniel joined 3M Food Safety in 2018.],[enJob=Professional Services, Food Safety, 3M Canada],[frBio=Ancien chercheur scientifique, Daniel est titulaire d’un doctorat en microbiologie de l’Université de Paris (France) et possède plus de 10 ans d’expérience en microbiologie et biologie moléculaire dans un laboratoire. Daniel a rejoint la Sécurité alimentaire 3M en 2018.],[frJob=Services professionnels, Sécurité alimentaire, 3M Canada]

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