## 2 Materials and Methods
### Statistical Analysis and Response Surface Methodology  
Descriptive statistics, specifically box and whiskers plots, were used to estimate the data distribution and to explore potential differences between the terpenoid compounds and their impact on amino acid glycation. A D-Optimal design was combined with Response Surface Methodology (RSM) as a post hoc analysis [32]. A reduced quadratic randomized model was retrofitted to the experimental conditions. Time, temperature, glucose concentration and terpenoid compounds were used as numerical values and forced to predefined values as described above (fixed values), while the choice of terpenoid compounds was set as a categorical value. A total of 33 runs were determined by a selection criterion chosen during the experimental design (Table 1). Color Development, Absorbance at 280 nm, 360 nm and 420 nm and Fluorescence Intensity expressed as (%) difference from the control were used for response prediction. For this purpose, a randomly selected sample was used for response prediction. The model's fitness was confirmed by analysis of variance (ANOVA) and the determination coefficient (R\({}^{2}\)) using \(p\)-values. Dependent variables were analyzed either via a Linear or 2 FI model. Model choice was based on the following criteria: test of normality for residuals, residuals versus predicted and residuals versus runs plots, Predicted R\({}^{2}\) and Lack \begin{table}
\begin{tabular}{c c c c c c} \hline \hline \multirow{2}{*}{**Run**} & \multirow{2}{*}{**A: Time**} & \multicolumn{2}{c}{**B: Terpenoid Compound**} & \multicolumn{2}{c}{**C: Glucose**} & \multirow{2}{*}{**D: Temperature**} & \multirow{2}{*}{**E: Terpenoid Compound**} \\  & & **Concentration** & **Concentration** & & & \\ \hline Units & Hr & \(\mu\)M & M & \({}^{\circ}\)C & - \\ \hline
1 & 2 & 4 & 0.1 & 100 & \(\mathrm{Linalool}\) \\
2 & 3 & 4 & 1 & 100 & \(\mathrm{Linalool}\) \\
3 & 2 & 2 & 1 & 80 & \(\mathrm{Linalool}\) \\
4 & 2 & 8 & 0.1 & 100 & \(\mathrm{Linalool}\) \\
5 & 2 & 6 & 0.1 & 80 & \(\mathrm{Thymol}\) \\
6 & 1 & 8 & 0.1 & 100 & \(\mathrm{Thymol}\) \\
7 & 3 & 8 & 1 & 100 & \(\mathrm{Aniseed Oil}\) \\
8 & 1 & 2 & 1 & 80 & \(\mathrm{Linalool}\) \\
9 & 2 & 6 & 1 & 100 & \(\mathrm{Thymol}\) \\
10 & 2 & 6 & 1 & 100 & \(\mathrm{Thymol}\) \\
11 & 3 & 4 & 0.1 & 80 & \(\mathrm{Linalool}\) \\
12 & 3 & 8 & 0.1 & 80 & \(\mathrm{Aniseed Oil}\) \\
13 & 1 & 6 & 0.1 & 80 & \(\mathrm{Linalool}\) \\
14 & 2 & 6 & 0.1 & 80 & \(\mathrm{Thymol}\) \\
15 & 3 & 6 & 0.1 & 100 & \(\mathrm{Thymol}\) \\
16 & 1 & 8 & 0.1 & 80 & \(\mathrm{Thymol}\) \\
17 & 1 & 6 & 1 & 100 & \(\mathrm{Linalool}\) \\
18 & 1 & 4 & 1 & 80 & \(\mathrm{Thymol}\) \\
19 & 3 & 2 & 0.1 & 100 & \(\mathrm{Aniseed Oil}\) \\
20 & 1 & 6 & 1 & 80 & \(\mathrm{Linalool}\) \\
21 & 2 & 2 & 0.1 & 100 & \(\mathrm{Thymol}\) \\
22 & 2 & 6 & 0.1 & 100 & \(\mathrm{Aniseed Oil}\) \\
23 & 2 & 2 & 0.1 & 100 & \(\mathrm{Thymol}\) \\
24 & 1 & 2 & 0.1 & 80 & \(\mathrm{Aniseed Oil}\) \\
25 & 3 & 2 & 1 & 80 & \(\mathrm{Thymol}\) \\
26 & 3 & 4 & 1 & 100 & \(\mathrm{Linalool}\) \\
27 & 3 & 4 & 1 & 80 & \(\mathrm{Aniseed Oil}\) \\
28 & 1 & 2 & 0.1 & 100 & \(\mathrm{Linalool}\) \\
29 & 1 & 8 & 1 & 80 & \(\mathrm{Aniseed Oil}\) \\
30 & 2 & 6 & 0.1 & 100 & \(\mathrm{Aniseed Oil}\) \\
31 & 2 & 6 & 1 & 80 & \(\mathrm{Aniseed Oil}\) \\
32 & 1 & 2 & 1 & 100 & \(\mathrm{Aniseed Oil}\) \\
33 & 3 & 8 & 1 & 80 & \(\mathrm{Linalool}\) \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Independent experimental factors and design layout runs. of Fit test. Box-Cox analysis were used to identify the most suitable data transformations. Namely, Color development underwent an inverse square root transform, and Absorbance at 420 nm underwent a power transform with a \(\uplambda\) = 2.56 and k = 66.583. Color Development was analyzed with a linear model and Absorbances at 280 nm, 360 nm and 420 nm and Fluorescence Intensity were analyzed with a 2 FI model. Significance level was set at \(\alpha\) = 0.05.