## 3 Results and Discussion  
Identification of the Chemical Compounds Correlated with the SCA Cupping Score Using Chemometric Profiling  
The identification of the chemical compounds in specialty beans was investigated in relation to the relationship between the sensorial data (cupping score) and information about the compounds obtained by non-targeted analyses. One of the important aspects of this approach is the quality of beans analyzed. Sixteen diverse samples of green coffee beans from Guatem with different qualities were prepared and roasted uniformly. The roasted beans were evaluated by an experienced Q grader using the standardized SCA protocol to ensure accurate evaluation. The SCA cupping scores among 16 samples were ranged from 76.5 to 89.0 (Tables 1 and S1).  
The remainder of the roasted beans were extracted with pentane/diethyl ether for comprehensive analysis and then subjected to non-targeted GC-MS measurements. Data processing and filtering of the GC-MS spectra provided 237 valid peaks. To isolate the key compounds and contributing to the SCA cupping scores, a supervised statistical multivariate technique was applied. Using the SIMCA-P\({}^{+}\) software, a cupping score prediction model based on OPLS regression analysis was created [36; 37]. The cupping score could be predicted with high accuracy using the information provided by GC-MS, as indicated by the value of the correlation coefficient (R\({}^{2}\)Y = 0.976), the cross-validated correlation coefficient (Q\({}^{2}\) = 0.936), and the square error of estimation (RMSEE = 0.46), with statistical significance (Figure 1A) [36]. The cupping score was highly correlated with the compound or multi-component compound information obtained from the beans. Using the results of the OPLS regression model, we determined the quality-related compounds based on the variable influence on the projection (VIP) parameter (Figure 1B). The top-ranked compound, 3-MBM (VIP-01), contributed most to the cupping score. In addition to the Maillard-derived aromatic compounds, which are important to determine the quality of coffee flavor [8; 38; 39; 40], among the top 30 variables, four MECs were listed: VIP-08, linoleic acid methyl ester, VIP-09 palmitic acid methyl ester, VIP-11, stearic acid methyl ester, and VIP-26, oleic acid methyl ester. The SCA scores and the GC-MS normalized areas of these five markers were strongly correlated (VIP-01, VIP-08, VIP-09, VIP-11, and VIP-26, with R\({}^{2}\) values of 0.73, 0.59, 0.54, 0.49, and 0.41, respectively (Figures 1C and S1)). Moreover, these correlations were all positive, indicating that high-cupping score coffee beans contain higher amounts of these MECs. Although MECs are known to be present in roasted beans [41], to the best of our knowledge, this is the first study to report that MECs are key compounds that contribute to higher-cupping score coffee flavor in arabica beans.  
\begin{table}
\begin{tabular}{c c} \hline \hline  & **SCA Cupping Score (Point)** \\ \hline
89 & 89.0 \\
88 & \\
87 & \\
86 & \\
85 & \\
84 & 84.0 \\
83 & 83.25 \\
82 & 82.0, 82.0, 82.25, 82.5 \\
81 & 81.0, 81.25, 81.25, 81.5 \\
80 & 80.75 \\
79 & 79.0 \\
78 & 78.5 \\
77 & 77.5 \\
76 & 76.5 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Sixteen green coffee beans from Guatem were evaluated using the SCA cupping score.