## 3 Results and Discussion
### Stepwise-LDA of Fluorescence Spectra
Specifically, the rate of samples that were classified correctly was 81.4%, while cross-validation was 79.7%. The statistical test of \(\Lambda\) was 0.081, 0.707m and 0.992 (\(p<0.05\)) for the first, second, and third discriminant functions, respectively. Furthermore, the eigenvalues of these functions were estimated at 7.685 with canonical a correlation at 94.1% for the first, 0.403 with 53.6% for the second, and 0.008 with 0.9% for the third. Finally, the correct classification of external validation (82.1%) further confirmed the reliability of the model. More detailed results are presented in Table 4. \begin{table}
\begin{tabular}{c c c c c c c} \hline  & & & \multicolumn{4}{c}{**Predicted Group Membership**} \\ \cline{3-8}  & **Labels** & \begin{tabular}{c} **Thyme** \\ **Honey** \\ \end{tabular} & **Pine Honey** & **Fir Honey** & \
\begin{tabular}{c} **Citrus** \\ **Honey** \\ \end{tabular} & **Total** \\ \hline \multirow{4}{*}{
\begin{tabular}{c} Original \\ \end{tabular} } & \multirow{4}{*}{Count} & Thyme honey & 17 & 1 & 0 & 0 & 18 \\ \cline{3-8}  & & Pine honey & 0 & 10 & 3 & 0 & 13 \\ \cline{2-8}  & & Fir honey & 0 & 6 & 10 & 0 & 16 \\ \cline{2-8}  & & Citrus honey & 1 & 0 & 0 & 11 & 12 \\ \cline{2-8}  & & Thyme honey & 94.4 & 5.6 & 0.0 & 0.0 & 100.0 \\ \cline{2-8}  & & Pine honey & 0.0 & 76.9 & 23.1 & 0.0 & 100.0 \\ \cline{2-8}  & & Fir honey & 0.0 & 37.5 & 62.5 & 0.0 & 100.0 \\ \cline{2-8}  & & Citrus honey & 8.3 & 0.0 & 0.0 & 91.7 & 100.0 \\ \hline \end{tabular}
\end{table} 
Table 4: Discrimination results based on fluorescence at \(\lambda\)ex = 360 nm. Figure 9: Discrimination results based on \(\lambda\)ex = 360 nm. Classification results and case-wise statistics from both chemometric models were similar, though the first chemometric model based at \(\lambda\)ex = 330 provided a slightly higher discriminant score (94.9%) compared to the second model (81.4%) based at \(\lambda\)ex = 360. Additionally, group centroids for both chemometric models can be explained. Specifically, as observed from the discriminant scatter plot, pine and fir honey are located near each other and are somewhat distinct from thyme and even more so from citrus honey. These findings are confirmed by the literature, as pine and fir honey is honeydew honey and, therefore, share several similarities [46]. Standardized canonical discriminant function coefficients responded to phenolic compounds and specifically to hydroxycinnamic and other phenyl carboxylic acids. Despite the presence of several fluorophore phenolics in this spectra region, the development of robust models remained unaffected by overlaps. No research on Greek honey using fluorescence spectroscopy has been previously conducted. Although the stepwise-LDA has not been applied for the classification of honey botanical origins, fluorescence spectroscopy studies from other researchers confirm the successful distinguishing of honey samples using the spectral region of phenolic compounds. [PERSON] et al. [14] differentiated honey with an average score from 70% to 100% using PCA-LDA, while noting that spectra region \(\lambda\)ex 290-440 nm was the most useful region. Furthermore, in another study, [PERSON] et al. (2007) suggested a PCA-FDA method to discriminate seven botanical origins. Recent studies also utilized the spectral region of phenolic compounds coupled with SIMCA [16] and HCA [17] for the botanical authentication of honey. The results of the present study confirmed that the fluorophore phenolic profile is related to the botanical origin of monofloral honeys, so it can be used as a robust tool for honey authentication. Consequently, the novel methodology developed in this study is robust and can be successfully applied for the authentication of honey botanical sources.