This section shows step-by-step how you can use the SSSP software

Models and modules can be selected form the SSSP main window i.e. the thee-view structure shown below: 

1. Chose a model or module by a double click on the corresponding tree leaf

2. Enter product characteristics in the model dialog box and click on the APPLY button

3. Make predictions for (i) constant temperatures, (ii) a simple temperature profile created manually or (iii) a temperature profile entered from a logger file

4. To display graphs, click on the graph icon in the upper left corner of the screen or next to the entered temperature profile data
5. To save your predictions click on the   icon in the upper left corner of the screen
6. To exit a model or module click on
7. To obtain information click or  

Relative rate of spoilage (RRS) models and general information about SSSP

[SSSP home] Before any prediction can be performed product characteristics must be entered in the RRS model dialog box (as shown below). The only product characteristics required is the product shelf-life at a single known storage temperature (and then click on the APPLY button). From this information SSSP predicts shelf-life at different constant temperatures. To predict shelf-life in days, input a storage temperature in °C in the shelf-life prediction group-box and click on the CALCULATE button. Entering different constant temperatures is an easy way to get an idea about the temperature sensitivity of the product. 

In the dialog box shown below the shelf-life values are indicated with two decimals. However, from SSSP options (Options, General) the number of decimal places can be set by the user.  

Creating a temperature profile manually 

Within the RRS-model dialog box and under the tab 'Series of constant temperatures' (See picture just below) the storage temperature in °C and the storage time in hours can be entered for each step of a temperature profile. This is done by using the input fields as shown in the SSSP window below. Click on the button when temperature and time for each step of the profile has been entered. The button allows the last entered line to be deleted. Each step adds a new line and calculates remaining shelf-life as shown in the grid of the SSSP window below. SSSP calculates remaining shelf-life for storage at 0°C, 5°C and 10°C. These values indicate the remaining shelf-life of the product if, at a given point in time, it was stored at one of the three constant temperatures until spoiled.

To return from the SSSP output window with graphs (below) to the SSSP model dialog box (above) or to select a new SSSP model or module myou need to double click on relevane model/module in the SSSP tree-view structure.

A results-bar is shown at the bottom of the SSSP output window just above. When SSSP users click on a curve by using the right mouse bottom this results-bar shows (i)  remaining shelf-life (RSL) for the selected temperature profile, (ii) the actual storage temperature at that particular point in time and (iii) the remaining shelf-life (RSL) at 0°C, 5°C and 10°C. The remaining shelf life graph includes three curves showing the remaining shelf life at 0°C, 5°C and 10 °C.  In each point in time the remaining shelf-life curves indicate remaining shelf-life of the product if stored at a constant temperature of 0°C, 5°C or 10°C until spoiled. 

Once a temperature profile has been entered in SSSP (manually, from an ASCII file or by using the SSSP raw data importer) these data can be saved together with product characteristics in an XML-file (Click on the   icon). In this way the data are easy to use again in SSSP e.g. as part of a presentation or teaching session.

Entering temperature logger data into SSSP

The SSSP raw data importer () is a flexible tool that allow different types of data and various temperature profile data to entered into SSSP by copy and paste e.g. from a spreadsheet. In addition, SSSP can read temperature profiles in ASCII and XML formats. To import a temperature logger profile select 'Temperature profile from logger data' (See SSSP window below). To select and read data use the raw data importer () or press the LOAD FILE button () and select a TXT- or XML-file that contains the temperature data you want to evaluated and press OPEN. More information on this matter is found under temperature profile data - SSSP formats. Please observe that the product characteristics entered into SSSP cannot be changed after a temperature profile has been read. To evaluate different product characteristics with a given temperature profile the file containing the temperature data must be read/loaded again.  

RRS models with user-defined temperature characteristics

In addition to RRS models with fixed temperature characteristics corresponding to specific types of seafoods SSSP also includes RRS-models with user-defined temperature characteristics (See SSSP window below). These flexible RRS-models allow SSSP to predict shelf-life at different temperatures and for any food product where spoilage kinetics have been determined and the temperature characteristic is known to the user of SSSP.  Users of SSSP can select (i) the Arrhenius-spoilage model and enter an apparent activation energy (E_a-value), (ii) the Exponential-spoilage model and enter a slope parameter value or (iii) the Square-root-spoilage model and enter a T_min value. Two models can be selected at the same time to (a) compare two different temperature characteristics used with the same model or (b) to compare two different models with fixed temperature characteristics. Apart from their flexibility, the RRS-models with user-defined temperature characteristics function in the same way at the other RRS-models described above (See also Relative rate of spoilage (RRS) models).

Comparison of observed and predicted RRS data

This module of SSSP allows shelf-life data obtained at three different temperatures (or more) to be quantitatively compared with the Arrhenius, the Exponential or the Square-root spoilage models when used with a known temperature characteristic. Clearly, this includes any of the product specific RRS-models in SSSP. Thus, users can compare their own data with existing RRS-models in SSSP or evaluate if the Arrhenius, Exponential or Square-root spoilage models will be appropriate for their shelf-life data if these models are used with temperature characteristics optimal for the specific data.

Shelf-life data can be entered manually as shown in the SSSP dialog box below. Alternatively data can be entered using the SSSP raw data importer () or read from a file which is handy when SSSP is used for teaching.

SSSP uses relative rates of spoilage (RRS) to compare observed and predicted shelf-life data. The comparison rely on calculation of accuracy-factor values and presentation of observed and predicted data in graphs (See graphs in the SSSP output window below). When accuracy-factor values are calculated from RRS-data the reference temperature used to calulate RRS may influence the results. Therefore, SSSP determines average accuracy-factors. These average values are determined from the RRS data obtained by using all the tested storage temperatures as the reference temperature.       

Microbial spoilage models (MSM)

[SSSP home]. The MS-model dialog box is working in the same way as the RRS model dialog box described above. Predictions can only be performed after product characteristics have been entered. Product characteristics include (i) the initial concentration of bacteria in cfu/g (this value must be one or above), (ii) the storage temperature and (iii) possibly other factors like the level of carbon dioxide. When product characteristics have been entered, click on the APPLY button to calculate remaining shelf-life and microbial growth rate. By entering different sets of initial concentrations of bacteria (cfu/g) and storage conditions (temperatures or temperature and level of carbon dioxide) one can rapidly obtain an estimate of the products sensitivity with respect to 'the levels of contamination' and the storage conditions. The picture just below shows the MS-model dialog box in SSSP with calculated values.

MS-models predict microbial growth and remaining shelf -life at constant or at dynamic temperature storage conditions. Temperature profile data can be entered as described above for the RRS-models. More information on this matter is found under temperature profile data - SSSP formats. Click on the graph icon in the upper left corner of the screen () to show charts with a temperature profile and its effect on microbial growth over time and the remaining shelf-life at 0°C, 5°C and 10°C (See the SSSP output window below). 

Options and zoom functions available in SSSP to modify graphs  

[SSSP home] SSSP includes several options that allow the appearance of graphs to be modified by (i) changing the width of lines/curves, (ii) changing the number intervals for tichmarks on X- and Y-axis  and (iii) including or excluding data points and legends on graphs. OPTIONS are selected from individual gaphs () or in the SSSP main window (See the SSSP Options window below)

Depending on the type of model or module used, SSSP shows graphs of temperature profiles, remaining shelf-life, microbial growth (Log cfu/g) or microbial growth rate (1/h). Under OPTIONS, the GRAPH COMPARISON tab allows different overlay graphs to be produced.

To focus on particular areas of graphs SSSP includes a zooming function. When graphs are visible the zooming function is activated by holding down the left mouse button and then moving the mouse to mark the area to be magnified. To revert the magnification click on the right mouse button.