Introduction to FSSP™ v. 4.0 from July 2014

The Food Spoilage and Safety Predictor software has been developed to facilitate the practical use of mathematical models to predict shelf-life as well as growth of spoilage and pathogenic microorganisms in food. A major objective has been to develop a user-friendly software tool to evaluate the effect of constant or fluctuating temperature storage conditions (Dalgaard et al. 1997; Dalgaard et al. 2002, Mejlholm and Dalgaard, 2014; Østergaard et al 2014).

FSSP™ is a significantly expanded version of the Seafood Spoilage Predictor (SSP) software which was first released in January 1999. FSSP v. 4.0 from July 2014 includes:

• Four product-specific relative rate of spoilage (RRS) models
• Three generic RRS models
• Four product-specific microbial spoilage models
• A generic model to predict microbial growth and shelf-life 
• Modules to compare predictions from FSSP with users own data of shelf-life or growth of bacteria
• Model to predict growth of psychrotilerant Lactobacillis spp. in seafood and meat products
• Models to predict growth and histamine formation by Morganella psychrotolerans and Morganella morganii.
• Growth and growth boundary model for Listeria monocytogenes
• Models to predict the simultaneous growth of Listeria monocytogenes and lactic acid bacteria in chilled seafood, meat products and cottage cheese.
• An extensive generic model to predict growth  in various foods for different microorganismon on the basis of their cardinal parameter values.

The relative rate of spoilage (RRS) models included in FSSP have been developed from shelf-life data determined by using sensory evaluation and  experiments with foods stored at different constant temperatures. These RRS-models use information about a products shelf-life as determined at a given constant storage temperature to predict shelf-life at various storage temperatures.

Microbial spoilage (MS) models predict shelf-life of foods from the initial concentration of specific spoilage organisms (SSO) and from their growth depending on product characteristics and storage conditions. 

Histamine formation models and models for growth and  growth boundary of Listeria monocytogenes are included in FSSP to facilitate evaluation of food safety depending on storage conditions and product characteristics

The extensive and generic growth model in FSSP allow predictions to be obtained for a very wide range of microorganism/food combinations and the effect of dynamic temperature, pH and lactic acid concentrations can be taken into account.

Predictions from models in FSSP have been evaluated by comparson of predictions with data from food. Results of these product validation studies are reported in the Help-function of FSSP for the individual models. Before using a model it is important to observe it's range of applicability i.e. the product characteristics and the storage conditions for which product validation studies have been successful.

As specified within the Help-function of FSSP other predictive microbiology application software are available and they can be used together with FSSP to evaluate growth and survival of a wide range of spoilage and pathogenic microorganisms in food.