## 3 Results  
Sensory data were validated from CVr% values, resulting in all being under 20%.  
Olive pate sensory profiles resulted from all the descriptors of the profile sheet expressed as median values and are displayed as spider plots, with distinct colors for each cv. and overlapped with each other's (Figure 6).  
None of the samples resulted in defects. Nocellara del Belice samples were perceived as the saltiset, while those of Nocellara etnea were perceived as the bit interest. Hojiblanca samples resulted in being more balanced on the olfactory/gustatory level since the descriptors are closer to each other than the other cultivars; they also appeared to be less acidic. In terms of texture, Hojiblanca olive pate seemed to be more consistent and grainier than the others but less fluid and less adhesive, so it hardly merged with saliva and barely adhered to the palate and teeth when chewed.  
Itrana samples have the highest adhesiveness, solubility, oiliness, and chewiness of all the other CVs. Bella di Cerignola olive pate is mostly characterized by olfactory/gustative attributes rather than textural ones since these descriptors have extremely low values, mainly for oiliness, being a cultivar with very low oil content.  
By analyzing the tasters likings (Figure 7), it can be noted that Itrana samples were the most appreciated (about 20% of tasters liked it), followed by Hojiblanca samples that scored a liking of 4 for about 75% of tasters. Nocellara etnea samples also recorded a high liking (score 4) for about 45% of the tasters, reaching 77% with the lower score (3). Nocellara del Belice, Bella di Cerignola, and Itrana samples were less appreciated by adding scores of 3 and 4 for 60% of the tasters.  
Figure 6: Spider plots resulting from sensory analysis of olive pate samples.  
Due to the qualitative nature of the data shown in Figure 7, it is possible to obtain only the median and related standard deviation of each single CV analyzed, as shown in Table 1.  
The textural parameters of olive pate samples resulting from the back extrusion test were analyzed by a one-way ANOVA statistic test, which highlighted many differences among various olive pate types (Table 2).  
general textural parameters. For the work of cohesion, statistical differences do not emerge between samples.  
After conducting a correlation test between firmness evaluated by sensory analysis and firmness and consistency measured by Texture Analyzer, the following R values were obtained:  
R = 0.8515 (S_Firmness vs. BE_Firmness)  
R = 0.8200 (S_Firmness vs. BE_Consistency)  
where S_Firmness is the firmness evaluated by sensory analysis; BE_Firmness is the firmness measured by Texture Analyzer; BE_Consistency is the consistency measured by Texture Analyzer.  
The data show a good correlation between sensory and texture analysis.  
Analyzing dissimilarities between samples and considering all kinaesthetic parameters obtained by sensory and textural analyses through agglomerative hierarchical analysis (AHC), the various samples showed a clear clusterization into two groups (clusters): C1 and C2. The same clusterization results, but with different dissimilarity values, were obtained using both single linkage (Figure 8) and complete linkage (Figure 9) agglomeration methods.  
As shown, dissimilarity values logically differ between the two different agglomeration methods, except for subcluster C1-Nocellara etnea-Bella di Cerignola. The clusterization used is a dissimilarity Euclidean distance using the Hartigan Index for truncation (default values: from 2 to 5).  
Inside the C1 cluster, three cultivars are grouped: Hojblanca, Nocellara etnea, and Bella di Cerignola. These last two cultivars are sub-clusterized together with an even lower dissimilarity value that is exactly the same using both the single and complete linkage methods (3532.059).  
Inside the C2 cluster, with a dissimilarity value of 11,693.865, the two remaining cultivars are found: Nocellara del Belice and Itrana. The dissimilarity value between the two clusters is 55,927.403.