## 3 Results and Discussion
### Flash Profile  
The second session of the Flash Profile involved six panelists ranking the cheeses (SHGC-C, SHGC-PP, and SHGC-U) based on predefined sensory attributes. The results were analyzed using Generalized Procrustes Analysis (GPA) to assess consensus among panelists. Samples with the lowest residual variance across attributes exhibited the most consistent rankings. Given the sensory complexity introduced by the seaweed supplementation, the control cheese (SHGC-C) demonstrated the highest level of consensus across all attributes. In contrast, semi-hard goat's cheese supplemented with _P. palmata_ exhibited the highest residual variance for aroma (16.899), flavor (7.500), and aftertaste (9.464), while SHGC-U showed the highest residual variance for appearance (10.221) and texture (8.085), indicating a lack of agreement among panelists (see Table 6). Residuals' values determined via GPA for each panelist showed those with higher residual variance values--appearance for panelist 6 (8.705), aroma for panelist 4 (11.357), flavor for panelist 5 (7.013), texture for panelist 2 (5.331), and aftertaste for panelist 6 (8.610)--which indicates that the rankings of the referred attributes by these panelists were further from the consensus when compared to the other panelists (see Table S8 in Supplementary Materials). For panelists whose scaling factors were greater than 1, their rankings had to be stretched to align with the consensus, likely due to their use of the wider end of the ranking scale. Conversely, for panelists with scaling factors below 1, a scaled-down adjustment was applied, as they used the narrower range of the scale. In cases where scaling factors were close to 1, such as panelist 2 for aroma (0.969) and panelist 5 for flavor (0.938), no modifications were required during the GPA scaling. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Attributes** & **Object** & **Residual (\%)** \\ \hline \multirow{4}{*}{Appearance} & SHGC-C & 2.534 \\  & SHGC-PP & 8.724 \\  & SHGC-U & 10.221 \\ \hline \multirow{4}{*}{Aroma} & SHGC-C & 5.436 \\  & SHGC-PP & 16.899 \\  & SHGC-U & 8.911 \\ \hline \multirow{4}{*}{Flavor} & SHGC-C & 2.446 \\  & SHGC-PP & 7.500 \\  & SHGC-U & 6.353 \\ \hline \multirow{4}{*}{Texture} & SHGC-C & 2.524 \\  & SHGC-PP & 4.048 \\  & SHGC-U & 8.085 \\ \hline \multirow{4}{*}{Aftertaste} & SHGC-C & 5.931 \\  & SHGC-PP & 9.464 \\ \cline{1-1}  & SHGC-U & 7.051 \\ \hline \hline \end{tabular} \({}^{\pi}\)Legend: SHGC-C = semi-hard goat’s cheese control; SHGC-PP = semi-hard goat’s cheese supplemented with _Palmaria palmata_; SHGC-U = semi-hard goat’s cheese supplemented with _Ullow_ sp.  
\end{table} 
Table 6: Residual variance from Generalized Procrustes Analysis (GPA) of Flash Profile (FP) for the SHGCs \({}^{*}\) after 30 days of cheese ripening. According to [PERSON] [124], and [PERSON] [125], panelist bias can occur due to variability in individual interpretation of the scale. However, GPA transformations effectively mitigate such inconsistencies, ensuring that results remain robust and meaningful [125,126]. The consensus among panelists was evaluated using a consensus index (Rc) (Table 7). A permutation test was conducted with a significance level of \(p<0.0001\), and the consensus index was calculated as the percentage of consensus variance within the total variance. To further analyze the discriminative power of the sensory attributes, a correlation coefficient was applied to identify the sensory terms most strongly associated with the principal components (F\({}_{1}\) and F\({}_{2}\)), as these attributes play a key role in characterizing the samples within the sensory space [126]. The consensus index (Rc) indicated a low correlation, reflecting a low level of agreement among the panelists for all studied attributes. These values were lower than those reported by [PERSON] et al. [127] for the evaluation of \"Cuajada-type\" cheese from Oaxaca (Mexico), where Rc was 55.3% for non-trained panelists and 75.2% for trained panelists.