# A Predictive Model to Correlate Amino Acids and Aromatic Compounds in Calabrian Honeys
## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & \multicolumn{2}{c}{_Citrus (\(\mathbf{r=8}\))\({}^{*}\)_} & \multicolumn{2}{c}{**Chestnut (\(\mathbf{r=4}\))**} & \multicolumn{2}{c}{**Eucalyptus (\(\mathbf{r=4}\))**} & \multicolumn{2}{c}{**Acacia (\(\mathbf{r=4}\))**} & \multicolumn{2}{c}{**Sulla (\(\mathbf{r=5}\))**} \\ \cline{2-10}
**Amino Acids** & **MV** & **SD** & **MV** & **SD** & **MV** & **SD** & **MV** & **SD** & **MV** & **SD** \\ \hline Alanine (Ala) & 171.06 & 15.92 & 240.13 & 14.52 & 273.41 & 25.80 & 146.93 & 14.87 & 162.49 & 18.59 \\ Serine (Ser) & 84.83 & 5.09 & 99.92 & 5.10 & 112.03 & 5.24 & 74.66 & 2.53 & 81.70 & 7.02 \\ Proline (Pro) & 1101.80 & 159.11 & 206.37 & 160.65 & 1563.91 & 190.93 & 1050.58 & 82.48 & 922.90 & 135.79 \\ Valine (Val) & 684.54 & 59.76 & 304.88 & 21.75 & 510.53 & 12.53 & 373.41 & 24.24 & 441.27 & 22.26 \\ Threonine (Thr) & 46.06 & 5.65 & 32.89 & 4.71 & 59.77 & 8.74 & 43.17 & 4.12 & 42.31 & 7.72 \\ Leucine (Leu) & 988.19 & 277.33 & 59.46 & 10.57 & 142.74 & 33.32 & 137.22 & 16.39 & 223.54 & 60.38 \\ Isoleucine (Ile) & 1005.88 & 279.90 & 52.94 & 8.29 & 140.93 & 34.92 & 142.43 & 15.77 & 221.58 & 62.94 \\ Asparagine (Asn) & 826.29 & 72.74 & 197.73 & 12.44 & 463.69 & 21.31 & 1038.45 & 36.56 & 912.67 & 60.04 \\ Asparatic acid (Asp) & 212.73 & 33.52 & 208.32 & 29.51 & 373.77 & 13.59 & 226.69 & 37.83 & 219.02 & 15.68 \\ Lysine (Lys) & 315.08 & 35.21 & 24.11 & 4.92 & 87.95 & 6.52 & 387.67 & 23.46 & 233.08 & 35.17 \\ Glutamine (Gln) & 201.27 & 16.93 & 16.36 & 3.32 & 56.44 & 5.48 & 240.67 & 18.07 & 221.65 & 34.91 \\ Glutamic acid (Glu) & 174.64 & 270.06 & 73.17 & 1.89 & 143.30 & 6.98 & 76.85 & 1.70 & 79.16 & 5.40 \\ Histidine (His) & 169.71 & 5.53 & 34.69 & 1.69 & 76.50 & 3.97 & 209.21 & 3.82 & 192.92 & 12.20 \\ Phenylalanine (Phe) & 1866.58 & 359.49 & 120.68 & 23.66 & 223.13 & 48.51 & 229.06 & 8.37 & 666.61 & 152.22 \\ Argin (Arg) & 161.67 & 10.23 & 15.28 & 2.31 & 180.88 & 13.69 & 125.01 & 3.81 & 214.88 & 9.10 \\ Tyrosine (Tyr) & 380.47 & 47.37 & 263.61 & 17.57 & 317.55 & 33.08 & 240.29 & 21.83 & 472.73 & 71.48 \\ Tryptophan (Trp) & 36.03 & 6.22 & 1.51 & 0.01 & 2.88 & 0.79 & 44.25 & 6.28 & 8.22 & 2.60 \\ \hline \hline \end{tabular} \({}^{*}\) number of samples; MV: mean value; SD: standard deviation.  
\end{table} 
Table 3: Distribution of amino acids concentration for Calabria uniforal honey (mg/kg). The different shades of color allow us to evaluate the presence and relative abundance of amino acids and of different aroma families. Blue color means low quantity, and red color refers to high quantity. As shown (Figure 2), the higher level of proline was highlighted in the chestnut honeys, whereas the sulla honeys showed the lower levels. Phenylalanine was higher in the citrus honeys, followed by sulla, and lower in the other honeys. About the aromatic profile: Figure 2 shows that citrus honeys were characterized by higher levels of aldehydes and alcohols, even if the aldehyde family was the most abundant. To establish a correlation between various types of honeys, their amino acid profiles, and their aroma characteristics, a partial least squares (PLS) analysis was also conducted. If we consider n different honey types described by p amino acids and q aromatic classes of components, the aromatic attributes are stored in table X (with dimensions n and q), while the amino acid contents are presented in table Y (with dimensions n and p). The goal was to perform a PLS regression of amino acid contents (Y) against aromatic characteristics (X). For the graphical representation of this analysis, the \(X\) and \(Y\) variables were depicted on a \"correlation circle\", using their correlations with the first two components (t1 and  
Figure 2: Heat map of honey samples showing area of compounds by amino acids and volatile classes (blue color means low quantity and red color is high quantity, relatively). t2) of the PLS. This map closely resembles the traditional PLS regression loading plot but offers the advantage of accommodating additional variables.