Monitoring Taste Panel Efficiency During Evaluation of the Sensory Quality of Roncal Cheese

Abstract

A statistical study was performed on the scores awarded by a taste panel over a full Roncal cheese manufacturing season. The panel evaluations were part of a quality control program carried out on that cheese under the auspices of the Appellation of Origin for Roncal cheese by panelists previously trained and qualified as proficient. Analysis of variance and factor analysis were performed to examine variability for the different attributes and the influence of such factors as cheesemaking plant and the manufacturing season and also to monitor panel reliability. The results indicated that the attributes associated with the descriptor “characteristic” had the highest variability; these attributes were characteristic odor, characteristic aroma, characteristic texture, characteristic flavor, and characteristic aftertaste. Cheesemaking plant was the factor that had the greatest effect on variability. Factor analysis and exploratory box plot data analysis were used to detect discrepancies between individual assessors and the rest of the panelists.

Performance Comparison among Trained Judges and Panels for the Evaluation of “Cuajada” Type Fresh Cheese in Two Regions from Oaxaca in México

“…In the present research, the samples were served by a simultaneous multiple way (attribute by attribute), which allows for better comparative discrimination among the products, getting high levels of discrimination and repeatability in the panel [31]. The results of judge factor determined some discrepancies in the use of the intensity' scale, which is explained by inter-individuals differences [12]. In the case of the session factor, the results showed that data from both panels were repetitive in the majority of attributes; this disagrees with the results presented by [4], who evaluated 16 sensory characteristics of products made from walnut with panels located in Italy, Spain and France, and they found a significant effect (P < 0.05) on 6, 4 and 3 attributes, respecttively.…”

“…The three-way ANOVA results with interaction (Product × Judge) for the performance evaluation of the UMAR panel are shown in Table 2; this group was highly discriminating (P < 0.01) in the most of the attributes except for the aroma to serum. The judge factor revealed differences in the use of the scale on white color, soft to the touch, salty, lumpy in the mouth and soft in the mouth attributes; this effect might been due to inter-individual variation because of differences in the use of the intensity' scale by the subjects [12] and by the difference in training time of the panelists [4,28]. The session factor revealed that the panel was repetitive on all attributes except on the salty attribute; while the interaction factor determined that there were differences in the classification of cheeses for smell of rennet and aroma to serum attributes.…”

“…In order to check the performance of each panel, the following mixed model of three-way ANOVA with interacttion (Product × Judge) was used: Attribute = Product + Judge + Session + Interaction (Product × Judge) + Error, where judge, session e interaction were considered as a random effect, and product as a fixed effect [12,15,17,33], using the Fisher (F) test, and the product factor (F product ) as an index of discriminatory power. Consensuality in the use of the scale among judges was assessed by judges factor (F judges ); session factor (F session ) was used to measure differences of the results among sessions, and the interaction factor (F interaction ) was used to determine similarities or differences in the classification of the chesses over the scale, with a level of significance of α = 0.05 [34].…”

“…The four-factors ANOVA results with interaction (Product x Panel) for the evaluation of the sensory characterization of cheese are shown in Table 3, where the product factor showed that both panels were highly discriminative (P < 0.01) on all sensory attributes except on soft to the touch [11], found highly significant differences (P < 0.01) on the hardness, smell cream, salty, creamy aroma attributes for the cheddar cheese evaluated by trained panels in Scotland and Norway; [13] reported that the smell, aroma and texture attributes had a highly significant effect (P < 0.01) in the evaluation of roncal type cheese. For the panel factor the results revealed that both panels used different parts of the scale for the evaluation of the cheeses, except for soft to the touch and lumpy in the mouth attributes, in which there were no significant differences (P > 0.05).…”

“…This has led to the standardization of sensory profiles and the measurement of the level of performance of judges and panels from different sensory laboratories [4,8,9]; also these kinds of studies have shown that data obtained by different panels are reliable and repeatable [10]. Nowadays, products like cheeses [11][12][13], beer [14], walnuts [4], chocolate [8], dry sausage [15] and jellies [9,16] have been successfully evaluated at a trained inter-panels level. In these types of studies the validation of performance of judges and the comparison of sensory profiles provided by different trained panels can be evaluated by univariate statistical methods such as Analysis of Variance (ANOVA) [17,18] and by multivariate statistical methods such as Principal Component Analysis (PCA) [19][20][21], Generalized Procrustes Analysis (GPA) [22], the Structuration des Tableaux a Trois Indices des Statistique (STATIS) [23,24] and Multiple Factorial Analysis (MFA) [8,25,26]; in this last method the position of the products and attributes used by each panel in the sensory map can be displayed [27].…”