dpsp modified by Matthias Filter

Matthias Filter — Sat, 03 May 2014 11:22:30 -0000
--- v1
+++ v2
@@ -1,34 +1,70 @@
 ####Name:####

-
+Dairy Product Safety Predictor
 ####Company / Institution:####

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+ACTALIA/CNIEL, France
 ####Development Partners:####

-
+ACTALIA
+CNIEL
 ####Contact person:####

-
+H. Souaifi,
+F. Tenenhaus-Aziza
 ####Link:####

+https://aqr.maisondulait.fr/
+####Created:####

+2012
 ####Designed for:####

-
+Food business operators
 ####Applicable for:####

-
+Risk assessment module
 ####Media covered:####

-
+Food matrix (Especially cheeses: soft-cheese, semi-soft cheese, hard cheese)
 ####Microorganisms covered:####

-
+Pathogens: 4 species
 ####Growth Factors covered:####

-
+Temperature
+pH
+Water activity
+Lactic acid
+Interactions between factors
 ####Modeling approach:####

+Probabilistic
+####Description:####

-####Description:####
+For several years now, the French dairy sector has been developing microbiological risk assessment
+and exposure assessment models for the safety of dairy products, especially cheeses. To date, when a
+food business operator has developed an exposure assessment model specific to its product and one
+microorganism, he has the possibility to perform simulations with parameters of its choice, online, via a
+user-friendly interface, provided he has subscribed.
+The model development is a prior step to the online simulations. It is done together with the French
+technical center for milk and dairy product Actilait and a food business operator. It can last from some
+months to one year, depending on available data. The model development includes the collection of data
+regarding physical and chemical parameters all along the process (temperature, pH, water activity and
+lactic acid), accounting for variability; the statistical analysis of results from challenge tests, if available,
+to assess optimal growth rate of the microorganism in the considered matrix; the implementation of
+predictive microbiological models for growth in dynamic conditions (primary model and secondary
+cardinal models) and destruction, but also models describing cross-contamination; if the cheese is
+made from raw milk, a statistical analysis of milk routine microbiological results is performed, to assess
+the initial contamination of the milk (frequency, concentration); if the cheese is made from pasteurized
+milk, definition of recontamination scenarios is needed, using for instance routine microbiological
+control of the product and in the environment during process.
+Generally, the final results of a model are the distribution of the prevalence and the concentration at
+different steps of the process, until consumption. These results allow then defining sampling plans,
+verifying if a microbiological criterion is respected, etc. A risk of illness can also be calculated. When
+finalized, the tailor-made model is loaded in the interface and made available to the food business
+operator only, via a personal access. When logged in to his account, the user has to download an
+Excel sheet in which parameters accounted for in the model can be modified. After having changed
+parameters (for example a different temperature for the ripening phase), the user uploads the new
+version of the Excel sheet in the interface and starts simulation. When results are available online, he is
+informed by email.
Recent changes to dpsp

dpsp modified by Matthias Filter

dpsp modified by Matthias Filter

Name:

Company / Institution:

Development Partners:

Contact person:

Link:

Designed for:

Applicable for:

Media covered:

Microorganisms covered:

Growth Factors covered:

Modeling approach:

Description:
