Introduction to SSSP version 3.1 from August 2009
The Seafood 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 bacteria in seafood. 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. 2002, 2003, 2008).
SSSP
is a significantly expanded version of the Seafood Spoilage Predictor (SSP)
software from January 1999.
SSSP v. 3.1 from August 2009 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 SSSP with users own data of shelf-life
or growth of bacteria
- Models to predict growth and histamine formation by Morganella
psychrotolerans and Morganella morganii.
- Growth and growth boundary model for Listeria monocytogenes
- Model to predict the simultaneous growth of Listeria monocytogenes and
lactic acid bacteria in lightly preserved seafood
The relative rate of spoilage (RRS) models included in
SSSP have been developed from shelf-life data determined by using sensory evaluation
and experiments with seafoods 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
seafoods 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 SSSP to
facilitate evaluation of seafood safety depending on storage conditions and
product characteristics
Predictions from all types of models in SSSP have been evaluated by
comparson of predictions with data from seafood. Results of these product validation studies
are reported in the Help-function of SSSP 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.
- The SSSP software is developed specifically to predict shelf-life and
safety of seafood. However, SSSP includes an extensive Listeria monocytogenes growth and growth boundary
that has also been validated succesfully meat products As specified within the Help-function of SSSP
other predictive microbiology application
software are available and can be used to predict e.g. growth of
pathogenic microorganisms in various food.
|
