Panel Performance

Panel and Panelist Performance

 
Testing the performance of a panel is essential for the products evaluation. Indeed, to assess them it is needed to detect differences if they exist. A panel is efficient if it can discriminate products and if it is reproducible and repeatable from one session to another. To evaluate its performance, several analyzes can be carried out.

Panel Performance

 
To assess the panel efficiency, the following ANOVA model can be used. “Descriptor Grade” represents the mean for each parameter which has been used to grade products (sweetness, consistency,…)
 
Descriptor Grade ~ Product+Judge + Session + Product:Judge + Product: Session +Judge: Session
 
This model enables to consider the judge effect (the fact that the products mean is different from one judge to another), the session effect (the fact that from one session to another the products mean is different) and their interactions : product:judge (judges don’t assess products in the same way), and product session(products are not described in the same way from one session to another). In the statistical software R, the « panelperf » function of the package SensoMineR can be used to perform this analysis.
 
If the product effect is significant (p<0.05), there is a panel consensus to the assessment parameters, and thus the panel is reproducible.To study the panel repeatability, the interaction judge:session can be considered. If it is significant, from one session to another, the panel (i.e. all the judges) does not have the same grade mean for all the products. If the interaction product:session is significant, judges don’t assess the products in the same way from one session to another, thus they are not repeatable.

Panelists performance

 
A panelist can be considered efficient if he can discriminate and agrees with the rest of the panel. To evaluate their individual efficiency, the following ANOVA model for each panelist can be used:
 
Descriptor Grade~Product+Session
 
If the product effect is significant, the corresponding judge managed to differentiate products for the descriptor concerned. Moreover, if the correlation of a judge with the whole panel for each descriptor is positive and above 0.85, one can conclude that the judge agrees with the whole panel.

Conclusion

 
Obtaining an efficient panel is quite difficult even with trainings. Nevertheless, assessments done by panelists are more in-depth because of their human aspect whereas automatized analyses do not have this component, so they are incontrovertible.