Applied Sciences (Dec 2021)

Sensory Panel Performance Evaluation—Comprehensive Review of Practical Approaches

  • László Sipos,
  • Ákos Nyitrai,
  • Géza Hitka,
  • László Ferenc Friedrich,
  • Zoltán Kókai

DOI
https://doi.org/10.3390/app112411977
Journal volume & issue
Vol. 11, no. 24
p. 11977

Abstract

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Sensory assessors determine the result of sensory analysis; therefore, investigation of panel performance is inevitable to obtain well-established results. In the last few decades, numerous publications examine the performance of both panelists and panels. The initial point of any panelist measures are the applied selection methods, which are chosen according to the purpose (general suitability or product-specific skills). A practical overview is given on the available solutions, methods, protocols and software relating to all major panelist and panel measure indices (agreement, discrimination, repeatability, reproducibility and scale usage), with special focus on the utilized statistical methods. The novel approach of the presented methods is multi-faceted, concerning time factor (measuring performance at a given moment or over a period), the level of integration in the sensory testing procedure and the target of the measurements (panelist versus panel). The present paper supports the choice of the performance parameter and its related statistical procedure. Available software platforms, their accessibility (open-source status) and their functions are thoroughly analyzed concerning panelist or whole panel evaluation. The applied sensory test method strongly defines the applicable performance evaluation tools; therefore, these aspects are also discussed. A special field is related to proficiency testing. With the focus on special activities (product competitions, expert panels, food and horticultural goods), practical examples are given. In our research, special attention was given to sensory activity in companies and product experts or product-specific panels. Emerging future trends in this field will involve meta-analyses, application of AI and integration of psychophysics.

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