## 3 Results and Discussion
### PCA Analysis-Association of Color Parameters with the Phenolic Content and the Antioxidant Activity  
PCA was performed to put more insight into the data matrix and to show the structure of the relationships between all parameters. The first four principle components (PCs) with eigenvalue greater than 1 were extracted, and together, they explained around 99% of the total variance, including PC1 explaining 55.96% of variance and PC2 explaining 25.66% of variance. A projection of the variables (parameters) and a projection of the scores on the principal component plane, with PC1 and PC2 on the X and Y axes, respectively, are presented in Figure 1. As can be seen from Figure 1a, PC1 was positively correlated with  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multicolumn{6}{c}{**Table Grape Varieties**} \\ \hline \multicolumn{2}{c}{**Phenolics (\(\mu\)g/g DW)**} & \multicolumn{1}{c}{**Autumn Royal**} & \multicolumn{1}{c}{**Black Magic**} & \multicolumn{1}{c}{**Red Globe**} & \multicolumn{1}{c}{**Red Globe (Pink)**} & \multicolumn{1}{c}{**Palieri**} \\ \hline \hline \
\begin{tabular}{c} Sinpic acid (SA) \\ Ferulic acid (FA) \\ hydroxycinnamic acid (hCynA) \\ Resveratrol (Res) \\ Quercetin (Q) \\ Taxifolia (M) \\ Myricetin (T) \\ Kemp2018 & 101.7 \(\pm\) 12.48 \({}^{\text{a}}\) \\ Kemp2018 & 1012.5 \(\pm\) 14.43 \({}^{\text{b}}\) \\ Kaempfer (K) \\ Resporter (H) \\ Eroidictyl (Er) \\ Rutin (R) \\ \end{tabular} &
\begin{tabular}{c} 48.17 \(\pm\) 2.91 \({}^{\text{c}}\) \\  
ACN (loaded value = 0.98), Q (0.98), H (0.97), Res (0.91), sinapic acid-SA (0.83), M (0.82), and hue angle-h (0.93), and it was negatively correlated with R (\(-\)0.94), L* (\(-\)0.95), and b* (\(-\)0.89). PC 2 was positively correlated with DPPH (0.93), a* (0.84), C* (0.78), ferulic acid-FA (0.74), TPC (0.73), and eriodiciyol-Er (0.69).  
As it could be observed, strong associations between color parameters, namely L*, h. and some phenolic compounds, such as ACN, Res, H, M, R, and Q, have been noted (Figure 1a). Moreover, a* color coordinates was highly related with the DPPH and TPC values. Thus, simple measurement of color parameters may be used as a fast and low-cost method of screening the quality parameters of grapes (antioxidant activity and phenolic content), which would be useful for consumers and producers. Especially, as it was shown in the Figure 1b, those variables distributed the grape samples along PC1 and PC2 and five distinct clusters could be observed. What is noteworthy, the dark-colored table grapes (Black Magic, Palieri, Autumn Royal) were on the right sight of the PC1 axis and showed high levels of ACN, Res, M, Q, H, high hue angle, and low lightness (L*), as well as R content. On the other side of PC1 axis (negative PC1 values) are Red Globe varieties, both with high lightness and R content. Moreover, when analyzing distribution of the samples along the PC2 axis, Red Globe and Black Magic were the two varieties placed on the positive side of the axis and showed high antioxidant activity, measured by the DPPH assay, in contrast to Red Globe pink variety located on the negative PC2 values with low antioxidant activity. Application of PCA for easy interpretation of data, according the similarities and differences in fruit and vegetables based on the antioxidant content, has been previously reported by others [9,11].