SELECTION AND SCREENING OF A DESCRIPTIVE PANEL FOR EWES MILK CHEESE SENSORY PROFILING

The aim of this work was to select a competent sensory panel considering its ability to describe ewes milk cheese sensory properties. The panelists evaluated the sensory characteristics of several ewes milk cheeses in terms of odor, flavor and texture. The performance of judges was assessed taking into account the following aspects: (1) individual discriminatory ability and reproducibility for each sensory attribute; (2) group discriminatory ability and reproducibility and agreement between judges for each attribute; (3) panel homogeneity; (4) panel consonance; and (5) overall panel discriminatory ability. The panel performance was checked with a set of statistical procedures. The results obtained by the selected group were better than the initial panel from the point of view of discriminant power, reproducibility and agreement. The suggested method can be easily applied in routine control of assessors performance and to discover deviant behavior or differences in individual perception of the samples.     

PANEL PERFORMANCE AND NUMBER OF EVALUATIONS IN A DESCRIPTIVE SENSORY STUDY

The assessor performance is a key point in a sensory evaluation. In particular, at the end of a session, a decrease of the performance can be feared. We propose to analyze this performance with various criteria: usual ones as the main product effect or the error variance; a new one measuring the perceived products variability. The performance can then be studied all along the session from two points of view: in taking into account the only products tested at a given instant (named instantaneous); in taking into account all the products tested up to a given instant (named cumulative). In the presented example, in spite of the large number of products successively tested by each assessor, the instantaneous performance of the panel shows no significant deterioration. Furthermore, when the number of products tested by each assessor increases, more significant product effects can be obtained thanks to the accumulation of the amount of data. This shows that the number of products that can be reasonably studied by one assessor during one session is generally underestimated.     

INFLUENCE OF PANEL INCONSISTENCY ON THE OUTCOME OF SENSORY EVALUATIONS FROM DESCRIPTIVE PANELS

Different types of panelist by treatment interaction are explored to determine how they influence the outcomes of discrimination tests. The study compares the situations where panelists are considered as fixed or random effects over the range of most testing conditions for small panels (5–15 panelists) that replicate their judgements. Magnitude interaction and nonperceivers or nondiscriminators have minor effects on test outcomes. Cross-over interaction increases the chances for a type II error, especially when panelists are considered as random effects. False discrimination increases the chances for a type I error when panelists are considered as fixed effects. Applications of methods to reduce the chances for these errors in the testing for differences among treatments are discussed.     

A COMPARISON OF METHODS FOR EVALUATING THE PERFORMANCE OF A TRAINED SENSORY PANEL1

Cluster analysis, consonance analysis, principal component analysis (PCA) and the GRAPES program (Schlich 1994) were compared for the evaluation of panel performance. Ten judges evaluated 25 Merlot wines for 24 color, aroma and flavor attributes. Cluster analysis grouped similar judges. PCA identified judges according to their attribute use. Consonance analysis determined a numerical index for attribute agreement and the GRAPES program compared judges in their use of the scale, reliability, discrimination and disagreement. Three of the four techniques provided a graphical representation of similarities and differences between judges. Methodologies were best used in conjunction with one another. Ultimately the application of these tools will serve to improve the quality of sensory evaluations.     

MODELING THE EVOLUTION OF THE PERFORMANCE OF A SENSORY PANEL: A MIXED-MODEL AND CONTROL CHART APPROACH

A sensory panel is often used to profile the same type of product with the same set of attributes for many years. We are interested in characterizing the evolution of the performance of such a panel (and its panelists) over time. This article presents a methodology based on a mixed‐model approach that takes into account the evolution of both panel and panelist in the same model. At the panel level, linear and quadratic evolutions of the performance are tested. At the panelist level, the method allows detection of whether some panelists perform better than others, and whether this difference remains the same or evolves over time. This mixed‐model approach is followed by a graphical representation using a control chart method to identify occasional outliers. Data used to illustrate this methodology are eight sensory profiling data sets collected on ready‐made frozen meals between 1997 and 2001 (every 6 months). The performance index chosen as an example in this study is the individual repeatability measured by standard deviation over replicates.