Sensory shelf-life testing can be performed to determine the length of
time that a product’s sensory characteristics stay within your
organization's acceptable range.
Typical examples of shelf-life testing uses:
To determine the ideal storage conditions
(temperature, humidity, light levels, etc.) that will not degrade a
product's acceptable shelf-life.
To determine consumer acceptability/rejection when instrumental measurements alone are not able to.
However, if you do not have products in the Products library and your organization is not planning on using it, please ignore the parts of the workflow referring to sample/product linking. Everything else in the workflows is still applicable to your scenario and there is still analysis available, only in different area of the software.
*** Important Guidelines ***
For best analysis outputs for your shelf-life testing data in Compusense, we
recommend the following:
Question type selection. In Compusense you can set shelf-life tests using Category or Line Scale
questions to obtain Dunnett's analysis. In our examples we will use Category scales, but the
same guidelines apply to Line scales as well. Depending on your control sample availability, you could use Difference from control (DFC) method, or acceptability testing, etc.
You are welcome to use other question types in your shelf-life tests, too, which will not be compatible with the Dunnett's analysis, but will be compatible with other analysis types.
Testing on different days vs. testing in one sitting or in one day. Typically shelf-life testing take place over time, on different days, or weeks, or months, etc. We will refer to this as real-time shelf-life time point testing.
In some scenarios all time points can be tested in a single sitting, or in multiple sittings within one day. This testing method is possible in accelerated shelf-life testing where the samples are not fatiguing and there aren't that many so that they can be completed in a single day. If the samples that have undergone accelerated shelf-life treatment are fatiguing or there are too many to evaluate in a single day or session, evaluation over different days is recommended.
The test setup workflow in Compusense will depend on whether you need to evaluate samples across multiple days/weeks/months, or in a single session (or a single day).
Separate tests for different time points. For all real-time shelf-life time point testing we recommend creating separate tests for every time point. The time point 0 test should contain the sample at its initial state (e.g. shortly after production, or harvest, etc.). The sample in the time point 0 test will be your control sample to compare other time point samples to when you reach the analysis point of your shelf-life testing.
The example product we will use is a granola bar. The time point 0 test should have one granola bar sample in it that is fresh from the production line.
If you are evaluating in parallel granola bars and soft drink samples, for example, for their shelf-life, the recommended approach is to create separate tests for different product evaluations and separate tests for their corresponding time points. This is especially efficient and "cleaner" approach when questions are different for different products.
One of the main reasons we recommend separate tests for different time points is
because realistically it is very likely that some panelists that
participated in one time point may not be able to participate in
another in the future. If all time points were in one test and a
panelist couldn't come to even just one of the time point evaluations, you would
end up with missing data. When time points are set up as separate tests,
you will not have to deal with missing data due to someone's schedule
conflict for a specific time point evaluation.
However, if the N is different across tests when running the analysis, the software will use the lowest N. For example, let's suppose that you had 5 time points in your shelf-life testing and the N in each test was 12, 11, 13, 12, and 12. When running analysis the software will include 11 sample sets from each test in your reports. All tests that had more than 11 sample sets will get those 'excess' sample sets excluded. You can control which sample sets to exclude by using Filters, or let the software automatically exclude the sample sets.
If you are using DFC method, the marked control sample should not be included in any time point test. Panelists are not expected to collect data for the sample that is clearly marked as control, but rather compare other samples against it.
The sample in the time point 0 test must be set as a Control Sample type for the Dunnett's analysis to work properly. Other time point tests should not have a blind control included in them. This rule applies regardless of the question types used in tests.
Sample name should include in it a reference to the time point for easier identification in the reports (graph legends).
Subsequent time point test setup. When fully happy
with the setup of the time point 0 test, clone the test to create the next time point. Update each time point test as needed to reflect the correct
information for corresponding time point. Be sure to set the Sample type for all samples in all time point tests that are not time point 0 to something other thanControl. If you forget to do that, it might affect the analysis.
Single test setup for accelerated shelf-life testing in one session or day. If this is your scenario, and if you are planning on using the DFC method, get a head start with our preset DFC template. From the Dashboard, click Create new test. Scroll down to the Difference from control test and click Use. If you require different test setup from that found in our template DFC test, please contact Compusense Support for assistance.
We recommend using Dunnett's analysis for shelf-life data. The
Dunnett's multiple comparison test compares every test sample included
in the analysis to the control sample from the time point 0.
With Dunnett's analysis you can analyze up to 17 samples at a time. If your shelf-life testing includes more than 17 samples, that is not a problem. All you have to do is include up to 17 of them in one go, and then repeat the analysis for the remaining samples making sure to also include the time point 0 (the control sample) in the next round.
Train panelists. Consider using Compusense FCM® to train your panelists for reliable results.
If you are using the Products library to store your overarching products in it, and you link samples to products, then there are multiple different graphs and reports available directly in the Products library that you can generate on your shelf-life data:
Products over time. Graphical representation of data using action standards.
PowerPoint Report. Graphical representation of data based on the analysis options selected before generating the report. As mentioned earlier, we recommend Dunnett's analysis.
Summary Report. A quick and easy way to see if there is significant difference among samples. As mentioned earlier, we recommend Dunnett's analysis for shelf-life data.
Top Box Report. Crosstabulations and analysis for specified top/bottom boxes, such as TURF analysis.
You can always export the raw data if analysis outside of Compusense is needed.
The Products library is not the only place where you can generate graphs on data linked to products. Our Advanced search & analysis across tests feature offers the Graphing tool that can provide you with clear visual representation of how the samples are performing over time.
Overview The focus of this workflow is accelerated shelf-life testing using the difference style (Difference From Control) with Category intensity scale. The objective is to see whether the panel can identify a difference in a test sample from a ...
Overview The focus of this workflow is real-time shelf-life time point testing using the difference style (Difference From Control) with Category intensity scale. The objective is to see whether the panel can identify a difference in a test sample ...
Overview The recommended analysis for shelf-life testing data is the Dunnett's test. Dunnett's test compares a (blind) control against each test sample. This workflow will help you select specific analysis options when generating the PowerPoint ...
Overview The recommended analysis for shelf-life testing data is the Dunnett's test. Dunnett's test compares a (blind) control from the first test (time point 0) against each test sample from to subsequent tests (time points). This workflow will help ...
Overview Collect quantitative data on your products using the Standard test type. Use this test type to access a variety of question types to be used in profiling, difference from control or consumer tests. Question Compatibility The Standard test ...