# Nutritional Analysis of Red-Purple and White-Fleshed Pitaya (_Hylocereus_) Species
## 3 Results
### Principal Component Analysis (PCA)  
PCA was used to determine the correlation between the various parameters. In a biplot, which is a product of PCA, the length of the lines approximates the variances of the variables. The longer line indicates higher variance. The cosine of the angle between the lines approximates the correlation between the variables they represent. The closer the angle is to 90 or 270 degrees, the smaller the correlation. An angle of 0 or 180 degrees reflects a correlation of 1 or \(-1\), respectively. Very distant breakpoints in the variable line direction indicate high values, while breakpoints on the variable line extended along the beginning represent low values. Finally, the distance between two points approximates the Euclidean distance between two observations in multivariable space. Observations that far apart have a high Euclidean distance and vice versa [50]. Principal component analysis (PCA) was performed to statistically reveal the effect of individual phenol compounds and sugar contents on red and white-fleshed pitaya (Figures 1-8). In other words, as the outputs of the PCA analyses, biplot graphs enabled us to visualize the interrelations between variables and observations. According to the biplot graph of the phenolics obtained as a result of Principal Component Analyses (PCA), PC1 (the first principal component) explained 51.32% of the total variance, while PC2 explained 26.59%. The variance that the two factors can explain is 77.92% in total; which phenolics were higher in observations and the relationships between phenolics were given visually in the Figure 1. In detail, the highest quercetin and ellagaic acid levels were observed in red-fleshed samples (especially in red 2 and red 3), while highest levels of kaempfer and myrsetin were detected in white samples. Besides, white-3 sample contained the highest gallic acid, caffe acid and \(p\)-coumaric acid levels. According to the PCA analysis related to sugars, PC1 explained 53.98% of the total variance, while PC2 (the second principal component) explained 33.40%. The total explained variance is 87.38% by the first two principal components. According to these findings, while xylose and fructose are closely related, total sugar and glucose are also closely related to each other. On the other hand, these two sugar groups were inversely correlated with the others, while \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & **Gallic** & **Caffeic** & **\(p\)-Coumaric** & **Ellagic** & **Myricetin** & **Quercetin** & **Kaempfer** & **DPPH** & **Total** \\  & **Acid** & **Acid** & **Acid** & **Acid** & **Myricetin** & **Quercetin** & **Kaempfer** & **DPPH** & **Phenol** \\ \hline Mann–Whitney U & 3.500 & 3.500 & 3.500 & 0.500 & 0.000 & 2.000 & 0.000 & 0.000 & 2.000 \\ Wilcoxon W & 9500 & 9.500 & 9.500 & 6.500 & 6.000 & 8.000 & 6.000 & 6.000 & 8.000 \\ Z & \(-0.443\) & \(-0.443\) & \(-0.443\) & \(-1.798\) & \(-1.964\) & \(-1.091\) & \(-1.964\) & \(-0.964\) & \(-1.091\) \\ Asymp. Sig. (2-tailed) & 0.658 & 0.658 & 0.658 & 0.072 & 0.050 & 0.275 & 0.050 & 0.050 & 0.275 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Mann–Whitney U test between groups. -fructose and xylose were higher in whites, total sugar and glucose were higher in reds (Figure 2). The highest levels of fructose and xylose were found in white-fleshed samples, while the highest levels of total sugar and glucose were observed in red-fleshed samples. In other words, red and white-fleshed samples created two groups in terms of sugar content. The relationships between variables and observations in volatile aroma substances in white and red-fleshed pitaya fruit are given in the figures with virtual and biplot graphs obtained as a result of PCA (Figures 3-8). For the alcohols, PC1 can explain 51.16% of the total variance while PC2 can explain 29.99%. 81.15% of the total variance can be explained by the first two factors (Figure 3).