How can predictive microbiology help estimate food safety hazards?

1 What is predictive microbiology?

Predictive microbiology is the application of mathematical and statistical methods to describe and predict the behavior of microorganisms in food. It is based on the assumption that microbial growth, survival, and inactivation are influenced by intrinsic and extrinsic factors, such as temperature, pH, water activity, preservatives, oxygen, and processing methods. Predictive microbiology uses experimental data to develop equations or models that relate these factors to microbial responses, such as lag time, growth rate, maximum population, death rate, or probability of survival. These models can then be used to simulate or predict the behavior of microorganisms in different scenarios, such as storage, distribution, or processing of food.

2 Why is predictive microbiology useful?

Predictive microbiology can provide information on the potential growth or survival of pathogens or spoilage microorganisms in food products, which can be used to support decision making, risk assessment, shelf life determination, process optimization, or product development. For instance, predictive microbiology can help answer questions such as how long a food product can be stored at a certain temperature before becoming unsafe or unacceptable, what is the best combination of preservatives or additives to inhibit microbial growth in a food product, how effective is a thermal or non-thermal process in reducing the microbial load in a food product, and what is the probability of survival or growth of a specific pathogen in a food product under different conditions. Moreover, predictive microbiology can reduce the need for extensive and costly laboratory testing as it can provide estimates based on existing data and models; however, it is not a substitute for experimental validation due to its limitations and uncertainties.

3 What are some tools and resources for predictive microbiology?

Various tools and resources are available for predictive microbiology, such as ComBase, a public database of microbial growth and inactivation data and models; Pathogen Modeling Program (PMP), a software developed by the USDA Agricultural Research Service; Predictive Microbiology Information Portal (PMIP), a website that provides information and links to various predictive microbiology tools, resources, publications, and events; and International Commission on Microbiological Specifications for Foods (ICMSF), a non-governmental organization that provides scientific advice and guidance on microbiological aspects of food safety and quality. ComBase provides a web-based tool called ComBase Predictor, which allows users to access and apply the models to their own data or scenarios. PMP also offers Process Risk Model (PRM) to estimate the risk of illness associated with a food process. PMIP hosts a forum where users can ask questions and share experiences related to predictive microbiology. ICMSF has published several books and papers on predictive microbiology, such as the ICMSF Book 7 on Microorganisms in Foods 7: Microbiological Testing in Food Safety Management.

4 How to use predictive microbiology tools and resources?

Using predictive microbiology tools and resources requires following some basic steps. Firstly, you need to define your objective and scope - what is the question or problem you want to address? What is the food product, microorganism, and condition of interest? Additionally, you need to select the appropriate tool or resource based on the source and quality of the data and models available. Then, apply the tool or resource by inputting data and parameters, interpreting and validating results, and communicating and reporting findings. Finally, evaluate the outcome and feedback - is the information useful and reliable? Does it support your decision making or risk assessment? How can you improve or update your predictive microbiology approach?

5 What are some challenges and opportunities for predictive microbiology?

Predictive microbiology is a dynamic and evolving field that presents a variety of challenges and opportunities. These include data availability and quality, model development and validation, and model integration and application. To ensure the accuracy and applicability of models, data sharing, standardization, validation, and verification are essential. Additionally, user-friendly tools are needed to integrate different models and data sources. Responsible use of predictive microbiology is recommended to leverage its power for food safety and quality. By following the best practices and guidelines, you can enhance your food science skills and knowledge.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?