Comparison Of The Performance Of A Trained And An Untrained Sensory Panel On Sweetcorn Varieties With The Panelcheck Software
In this paper the results of trained and untrained sensory panels are compared on five Hungarian commercial sweet corn samples. The two evaluations were carried out in a sensory laboratory (ISO 6658:2005), with the same experimental design, with two replicates, and the panels consisted of 10 panelists. In both cases the panels assembled the profiles of the samples according to the vocabulary chosen by the trained panelists. The results show that the untrained panel has higher standard deviation, weaker repeatability and less significant parameters (ISO/DIS 11132). However 10 of the 17 sensory attributes were significant in the case of the untrained panel, the trained panel has 15 significant parameters with lower standard deviation and good repeatability. During the statistical investigation we focused on the panel performance and used the PanelCheck open source software package to achieve this goal. We followed the workflow suggested by the researchers of the Nofima, the developers of the PanelCheck. According to the examined parameters the trained panel has better discrimination ability (F values) for attributes â€™yellow colorâ€™, â€™hueâ€™, roughnessâ€™, â€™freshnessâ€™, â€™juicinessâ€™, â€™tendernessâ€™. There was not an attribute evaluated by the untrained panel where all the panel members reached the line representing the 5% significance level. Furthermore the trained panel has better agreement between its assessors (Tucker-1 plots) and the repeatability is much better according to the MSE plots. This examination confirms that it is necessary to train the panels in order to get reliable and consistent results.
Volume (Year): 06 (2012)
Issue (Month): ()
|Contact details of provider:|| Web page: http://www.apstract.net/|
When requesting a correction, please mention this item's handle: RePEc:ags:apstra:138088. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (AgEcon Search)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.