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Seafood Spoilage and Safety Predictor (SSSP) software v. 3.1 (Revised August 2009)

The SSSP software is avialable free of charge:

The SSSP software predicts shelf-life and growth of bacteria in different fresh and lightly preserved seafood e.g. the effect of product temperature profiles recorded during storage and distribution by data loggers. Some of the predictive models in SSSP are equally useful for other types of food. New features of SSSP v. 3.1:

  • Listeria monocytogenes growth and growth boundary model for the effect of temperature, salt (NaCl/aw), pH, CO2, smoke intensity, nitrite and organic acids (acetic/diacetate, benzoic, citric, lactic and sorbic acid). This model has been successfully validated for both seafood and meat products.
  • Text in SSSP can be selected in many different language including Chinese, Croatian, Danish, Dutch, English, French, Finnish, German, Greek, Italian, Persian, Polish, Portuguese, Spanish and Vietnamese.

SSSP contains:

  • Models for relative rates of spoilage
  • Models for growth of spoilage bacteria in specific seafood products.
  • Models to predict histamine formation by Morganella psychrotolerans and Morganella morganii
  • Model to predict the simultaneous growth of Listeria monocytogenes and lactic acid bacteria.
  • Model to predict the growth boundary of Listeria monocytogenes depending on storage conditions and product characteristics.
  • Models where parameter values can be changed by the user to make them appropriate for various types of food or bacteria.
  • Modules that allow observed shelf-life or growth of bacteria to be compared with predictions from SSSP.

For SSSP to operate appropriately your PC must use:

  • A screen resolution of 1024 x 768 or higher
  • The Microsoft .Net Framework version 2.0 or above
  • MS Windows 98 or above
  • Microsoft Explorer version 5.00.3 or higher

The Help-menu within SSSP explains how the software can be used and provides information about the different mathematical models used to predict shelf-life and growth of bacteria.


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SSSP v. 3.1 Installation guide
Download information related to SSSP:
Prædiktiv mikrobiologi - et centralt redskab til produktudvikling og dokumentation af fødevaresikkerhed - Teamdag ved DTU d.27. februar 2014
Artikel om prædiktiv mikrobiologi og SSSP i "Fisk & Hav"
Questions and comments about SSSP are welcome and should be forwarded to:
Paw Dalgaard, Seafood & Predictive Microbiology (Research group), National Food Institute (DTU Food), Technical University of Denmark, building 221, Soltofts Plads, DK-2800 Kgs. Lyngby, Denmark, E-mail: pad@aqua.dtu.dk, Tel. 45 25 25 66