## 3 Results and Discussion
### Relationships between Evaluated Parameters  
Data obtained for determined parameters were subjected to multivariate statistical analysis. The correlation matrix among the physical, chemical and rheological parameters of the nine samples (Table 4) showed that many interactions among these parameters were significant at \(p<0.01\) level. Among those associations with correlation coefficients above 0.80, some were more expected than others. The high correlation between the soluble solid content and consistency index \(K^{\prime}\) (r = 0.883) and \(K^{\prime\prime}\) (r = 0.910), pH and acidity (r = \(-\)0.802) were presumed. The color parameter \(a^{*}\) was also highly correlated with flow behavior index \(n^{\prime}\) (r = 0.657) and \(n^{\prime\prime}\) (r = 0.701). The consistency index \(K^{\prime}\) was significantly correlated with  
Figure 4: Yield stress value of suspensions containing 15% (T1), 20% (T2) and 25% (T3) tomato pomace powder. \(b^{*}\) (r = \(-\)0.719) and \(C^{*}\) (r = \(-\)0.669) color parameters of the suspension. Acidity showed a moderate negative correlation with lightness (r = \(-\)0.580), and pH with consistency index \(K^{\prime\prime}\) (r = \(-\)0.567), whereas between consistency index \(K^{\prime}\) (r = \(-\)0.495) and pH, a weak negative correlation was found. The application of principal component analysis (PCA) allowed a general overview of the data and suspensions evaluated. The PCA projection for the physical, chemical and rheological parameters of the nine suspensions on the first two principal components (Figure 5) showed that the first and second principal components accounted for 51.86% and 29.14% of the variability of the data, respectively. Consistency index \(K^{\prime}\) and \(K^{\prime\prime}\), soluble solid content and acidity were heavily weighted on the PC1. The small angles between \(K^{\prime\prime}\) and soluble solid content reflected the highly significant correlation coefficient (Table 4). Flow behavior index \(n^{\prime}\) and \(n^{\prime\prime}\) were heavily weighted on the PC2. \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**Parameter** & **pH** & **Acidity** &
\begin{tabular}{c} **SS** \\ **Content** \\ \end{tabular} & \(L^{*}\) & \(a^{*}\) & \(b^{*}\) & \(C^{*}\) & \(K^{\prime}\) & \(n^{\prime}\) & \(K^{\prime\prime}\) & \(n^{\prime\prime}\) \\ \hline pH & 1 & & & & & & & & & \\ \multicolumn{1}{c}{Acidity} & \(-\)0.802 ** & 1 & & & & & & & & \\ \multicolumn{1}{c}{SS content} & \(-\)0.419 * & 0.275 & 1 & & & & & & & \\ \multicolumn{1}{c}{\(L^{*}\)} & 0.478 * & \(-\)0.580 ** & \(-\)0.552 ** & 1 & & & & & & \\ \multicolumn{1}{c}{\(a^{*}\)} & 0.179 & \(-\)0.205 & \(-\)0.300 & 0.201 & 1 & & & & & \\ \multicolumn{1}{c}{\(b^{*}\)} & 0.338 & \(-\)0.359 & \(-\)0.478 * & 0.340 & 0.933 ** & 1 & & & & \\ \multicolumn{1}{c}{C*} & 0.262 & \(-\)0.287 & \(-\)0.394 * & 0.274 & 0.984 ** & 0.983 ** & 1 & & & \\ \multicolumn{1}{c}{\(K^{\prime}\)} & \(-\)0.495 ** & 0.368 & 0.883 ** & \(-\)0.569 & \(-\)0.599 & \(-\)0.719 & \(-\)0.669 & 1 & & \\ \multicolumn{1}{c}{\(n^{\prime}\)} & \(-\)0.158 & 0.183 & \(-\)0.047 & 0.118 & 0.657 ** & \(-\)0.500 ** & 0.588 ** & \(-\)0.350 & 1 & & \\ \multicolumn{1}{c}{\(K^{\prime\prime}\)} & \(-\)0.567 ** & 0.452 * & 0.910 ** & \(-\)0.529 & \(-\)0.431 * & \(-\)0.623 & \(-\)0.535 & 0.922 ** & 0.023 & 1 & \\ \multicolumn{1}{c}{\(n^{\prime\prime}\)} & \(-\)0.142 & 0.111 & 0.110 & 0.049 & 0.701 ** & 0.531 ** & 0.627 ** & \(-\)0.259 & 0.963 ** & 0.090 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Correlation matrix with Pearson’s correlations among the evaluated parameters. Figure 5: Principal Component Analysis bi-plot: blue bullets represent variables; green triangles represent tomato pomace powder suspension samples with 15, 20 and 25% tomato pomace at 20 \({}^{\circ}\)C (MT1, MT2 and MT3); thermal-treated at 60 \({}^{\circ}\)C (CT1, CT2 and CT3) and thermal-treated at 95 \({}^{\circ}\)C (HT1, HT2 and HT3).