# From Vine to Wine: Non-Colored Flavonoids as Fingerprints
## 3 Results
### Multivariate Analysis
#### 3.3.2 Linear Discriminant Analysis
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Original \(\rightarrow\)** & **DOT** & **DO O** & **DO Y** & **DO G** & **DO A** & **LP** & **HI** & **LZ** & **GO** & **GC** \\ \hline DO T & **84.4** & 3.7 & 5.6 & 10.0 & 15.2 & 0.0 & 0.0 & 0.0 & 0.0 & 23.1 \\ \hline DO O & 6.7 & **92.6** & 16.7 & 0.0 & 6.5 & 6.7 & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline DO Y & 0.0 & 0.0 & **55.6** & 0.0 & 6.5 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline DO G & 0.0 & 0.0 & 5.6 & **80.0** & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline DO A & 4.4 & 0.0 & 5.6 & 10.0 & **71.7** & 0.0 & 0.0 & 0.0 & 0.0 & 7.7 \\ \hline LP & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & **93.3** & 0.0 & 0.0 & 0.0 & 0.0 \\ \hline HI & 0.0 & 0.0 & 5.6 & 0.0 & 0.0 & 0.0 & **100.0** & 0.0 & 0.0 & 0.0 \\ \hline LZ & 0.0 & 3.7 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & **100.0** & 0.0 & 0.0 \\ \hline GO & 4.4 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & **100.0** & 0.0 \\ \hline GC & 0.0 & 0.0 & 5.6 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & 0.0 & **69.2** \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Correct classification rates (diagonal values) and misclassifications obtained from the LDA employed to differentiate red wines according to DO on Tenerife Island. lower accuracy of 69.2%, with 23.1% of cases misclassified with DO T. One of the regions with lower classification accuracy was DO Y, where only 55.6% of cases were correctly classified. DO Y has a south and north side on Tenerife Island, which could explain the misclassifications from this region. In fact, the misclassifications mainly occurred with DO O (north border of the vineyards included in DO Y), DO A (south border of the vineyards included in DO Y), and DO T (north side of the island), suggesting that these DO areas inside Tenerife Island share similar characteristics, and their common flavonoid profile might have confused the model. In terms of flavanols, a positive correlation was observed between the two flavanol compounds Cate and Epic (r = 0.430, \(p\) < 0.001). Interestingly Epic presents quite less significant correlations with flavonoids (just with Iggl, Isor, and Quer) whereas Cate was significantly related with almost all the flavonoids quantified, except M3 gu and Q3 gl, and usually with a higher Pearson coefficient. Similar behavior was observed in the flavonoid group, as the concentration of both miricetyn glycosylated derivatives, M3 gu and M3 gl, was relatively less related to the other flavonoids, but for instance, Myri was significantly related to most of them, such as with M3 Gl, L3 gl, K3 gl, Myri, Q3 gu, Ruti, Iggl, Isor, S3 gl, and Quer. The presence of strong correlations between glycosylated flavonoids (GFlo) and their aglycone counterparts (AFlo) suggests a dynamic equilibrium between glycosylation and deglycosylation processes in flavonoids, as illustrated in Figure 2A (r = 0.697; \(p\) < 0.01). Interestingly, when this analysis was conducted for specific flavonoid structures, the association between aglycone and glycosylated flavonoids was most pronounced in the case of Isor and I3 gl (r = 0.877; \(p\) < 0.01) (Figure 2B). In contrast, this correlation was less significant in other flavonoid structures, such as Quer and Q3 gl (r = 0.297; \(p\) < 0.01) and Quer-Q3 gu (r = 0.271; \(p\) < 0.01). Moreover, no significant correlations (_p_ > 0.05) were observed for other aglycone glycosylated forms, such as Myri and M3 gu, Quer and Ruti, or Myri and M3 gl. Additionally, a highly significant correlation (r = 0.832; \(p\) < 0.01) was observed between Myri and Q3 gu (Figure 2C). There was also a highly significant relationship (r = 0.900; \(p\) < 0.01) between the different glycosylation forms of quercetin, such as Q3 gl and Q3 gu (Figure 2D). In terms of flavonoid calculations, GFlo significantly (_p_ < 0.001) correlated with most of the flavonoids employed for its calculation (M3 gl, r = 0.494; L3 gl, r = 0.263; Q3 gu, r = 0.941; Q3 gl, r = 0.909; Ruti, r = 0.470; I3 gl, r = 0.633).