Del 02 al 04 de Noviembre 2017

Nuevo Vallarta, Nayarit, México

Predictive microbiology modeling in foods and the use of USDA-pathogen modeling programs/COMBASE by the food industry

Predictive Microbiology for Food Safety

This workshop will provide attendees with an excellent opportunity to learn the most important microbiological safety issues facing the food industry on a global scale, enhance and update knowledge of predictive microbiology, and learn new approaches for modeling foodborne pathogens.  Furthermore, this workshop supports our mission to provide consumers with microbiologically safe foods in domestic markets and safe foods for export. The overall goal of the proposed workshop is to provide a clear understanding of how to use the microbial modeling software to obtain accurate estimates on growth, survival and lethal effects of processing environments on foodborne pathogens; and how to formulate foods to include acknowledged intrinsic barriers while designing intervention processes that ensure safety against pathogens in foods. 

The intended audience for this workshop will include: Undergraduate and graduate students in microbiology who have an interest in food safety predictive microbiology; regulatory agencies food inspectors; food industry professionals responsible for product development and ‘Hazard Analysis Critical Control Point’ (HACCP) validation, and quality assurance professionals.  Professionals will use the knowledge obtained in developing experimental designs, pertaining to the number of samples to be prepared and determining the interval between sampling, based on the predictions from the modeling program.

The objectives of the workshop are to give an overview of basic food microbiology and predictive modeling, and would cover topics, such as phases of bacterial growth, phases of bacterial inactivation, factors that affect bacterial growth and inactivation, classes of models, including discussion on underlying principles of modeling as well as the use and interpretation of the predictive models.  Participants will learn how to mathematically describe the experimental data, aiming at predicting the microbial behavior within the range of the experimental values tested (interpolation).  In other words, they will be able to predict the outcome of a process, e.g., number of log reduction, resulting from the processing conditions, e.g., residence time and temperature, and to predict for untested conditions. 

The lectures will be given in English but a simultaneous translation service will be provided, if needed.  The attendees will have the opportunity to ask questions in Spanish.  Also, the instructions on the use of software, a hands-on experience on laptop using online and desktop versions, will be given in English/Spanish.


The agenda for the workshop is as follows:

  1. Workshop introduction
  2. Food Safety Issues/Challenges in the 21st Century
  3. Quantitative microbiology in food manufacturing
    1. Pathogens and food products of concern
    2. Challenges in food safety
    3. Existing and emerging technologies for food preservation
    4. Food formulation and processing guidelines
    5. Comprehensive Intervention strategies for pathogen control in foods

Hurdle concept

Microbiology for Fermented and Baked Products

  1. Fundamentals of predictive microbiology
    1. Experimental design and data collection
    2. Primary models:  describe the microbial population with time (fitting curves to data) -- Growth, survival, inactivation; measuring parameter values

           Gompertz, Baranyi, Weibull, D value

  1. Secondary models: describing changes in parameter values of primary model with changes in environmental conditions  (T, pH, aw, preservatives)

 Square root growth, regression equations

  1. Tertiary models (model interface): software tools to input data, predict results, e.g., Pathogen Modeling Program (USDA)
  2. Overview and demonstration of software tools
  3. Regulatory perspective on the use of predictive microbiology
  4. Case studies demonstrating their application
  5. Hands-on demonstrations and training for proper use of the programs; all participants will be provided with a laptop.
  6. Close workshop: Evaluation sheet to obtain feedback from attendees.


This workshop will describe and demonstrate how the current computer programs of the U.S. Department of Agriculture, Agricultural Research Service can be used to predict behavior of the pathogens in foods.  The programs include: 1) Predictive Microbiology Information Portal (PMIP); 2) Pathogen Modeling Program (PMP); 3) ComBase.  By participating in this workshop, attendees will better understand how to use these programs to enhance the safety of food.  All participants will be provided with a laptop to obtain hands-on experience on the use of the software programs. A description of the programs to be covered in the workshop follows:


PMIP is geared to assist food companies (large and small) in the use of predictive models, the appropriate application of models, and proper model interpretation. The PMIP links users to numerous and diverse resources associated with models (PMP), databases (ComBase), regulatory requirements, and food safety principles. 

PMP, a desktop version, is a package of models that can be used to predict the growth and inactivation of foodborne bacteria, primarily pathogens, under various environmental conditions. These predictions are specific to certain bacterial strains and specific environments (e.g., culture media, food, etc.) that were used to generate the models.  

ComBase is a database that contains information about how microorganisms respond to different environments. Using an Internet interface, the user identifies criteria that are relevant to a specific food microbiology scenario. This may include identifying a specific microorganism, type of food, level of acidity, temperature, water activity, and the presence of specific food conditions, such as additives, preparation methods and packaging atmospheres.  After searching the database for the desired information, the results can be downloaded and used for model development or validation. 

Vijay K. Juneja
Miércoles, 1 Noviembre, 2017
Marival Resort & Suites