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 ’yellow color’, ’hue’, roughness’, ’freshness’, ’juiciness’, ’tenderness’. 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.


Issue Date:
Sep 01 2012
Publication Type:
Journal Article
PURL Identifier:
http://purl.umn.edu/138088
Published in:
APSTRACT: Applied Studies in Agribusiness and Commerce, Volume 06, Number 1-2
Page range:
77-84
Total Pages:
8
Series Statement:
6
1-2




 Record created 2017-04-01, last modified 2017-08-26

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