## 3 Results and Discussion
\begin{table}
\begin{tabular}{c c c c c c c} \hline
**ID** & **Half-Red** & **Red** & \(p\) & **FC** & **AUC** & **CI 95\%** \\ \hline S1 & 0.439 & 0.408 & & & & \\  & [0.415–0.456] & [0.364–0.429] & \(<\)0.001 & 0.929 & 0.946 & 0.922–0.969 \\ S2 & 3.812 & 4.710 & & & & \\  & [3.416–4.185] & [3.924–5.541] & \(<\)0.001 & 0.809 & 1.236 & 0.950–0.989 \\ S3 & 0.430 & 0.389 & & & & \\  & [0.409–0.443] & [0.359–0.414] & \(<\)0.001 & 1.105 & 0.905 & 0.942–0.98 \\ S4 & 1.075 & 1.077 & & & & \\  & [1.061–1.084] & [1.067–1.085] & & & & \\  & 0.421 & 0.380 & & & & \\  & [0.398–0.443] & [0.356–0.406] & & & & \\  & 3.907 & 4.198 & & & & \\  & [3.691–4.225] & [3.845–4.669] & & & & \\  & 1.322 & 1.930 & & & & \\  & [1.234–1.445] & [1.506–2.198] & \(<\)0.001 & 0.685 & 1.460 & 1.000–1.000 \\ S8 & 5.713 & 6.370 & & & & \\  & [5.349–6.303] & [5.671–6.974] & \(<\)0.001 & 0.897 & 1.115 & 0.847–0.924 \\ S9 & 1.800 & 2.283 & & & & \\  & [1.642–1.95] & [2.042–5.555] & & & & \\  & 1.196 & 1.204 & & & & \\  & [1.160–1.224] & [1.172–1.226] & 0.40 & 0.994 & 1.006 & 0.526–0.669 \\ \hline \end{tabular}
\end{table} 
Table 1: Univariate data analysis: ID indicates the sensor name, in columns half-red and red the median (5 th–95 th) percentile is reported for the two maturity stages, \(p\) is the \(p\)-value of the factor maturity stage obtained by LME, FC is the fold change calculated as the ratio between the median of red and the median of half-red, AUC is the area under the ROC curve and CI 95% is the confidence interval of AUC at the level of 95%. Cluster analysis allowed us to gather the VOCs in two groups and the e-nose sensors in three clusters. Specifically, the first group consisted of all the VOCs with the exception of 2-methylbutanoic acid (Ac4) and mesifurane (F1), which formed the second cluster (Figure 2). On the other hand, the first group of the e-nose sensors included S2, S6, S7, S8 and S9, the second involved S1, S3 and S5 and the third cluster contained S4 and S10. Specifically, the first group of VOCs exhibited a highly positive association with the sensors  
Figure 1: PCA model of the e-nose data: circles represent the observations (technical replicates), while triangles indicate the medians of the technical replicates of the same sample; the green colour is used for observations belonging to the half-red group and the red colour for those of the red group. Figure 2: Heatmap: a different colour code was used to represent the clusters discovered by cluster analysis; \(\rho\) is the Pearson correlation coefficient. S2 (broad range), S6 (broad-methane), S7 (sensitive to many terpenes), S8 (broad-alcohol) and S9 (responsive to sulphur and aromatic metabolites) and a highly inverse correlation with the sensors S1 (sensitive to aromatic compounds), S3 (sensitive to ammonia and aromatic compounds) and S5 (sensitive to hydrocarbons and aromatic compounds). The correlations with the sensors S4 (sensitive to hydrogen) and S10 (sensitive to methane) were negligible, in agreement with the univariate data analysis (Table 1). Moreover, the sensors of the first cluster (S2, S6, S7, S8 and S9) presented a higher response to the red fruit, which may be caused by the increase in methane and alcohol, in line with previous studies [16]. On the other hand, the sensors of the second cluster (S1, S3 and S5) showed a higher signal to the half-red samples, allowing us to discriminate between the two ripening stages (Table 1, Figure 2). The compounds Ac4 and F1 were positively correlated to the sensors S7 and S9 (Figure 2), and their correlation coefficient showed smaller absolute values with respect to the other VOCs, maintaining the same sign. Interestingly, in our previous study these two compounds showed a significant correlation only with red-H3 strawberries [20]. Specifically, mesifurane (F1), which is known to increase during fruit ripening and to confer caramel or cotton candy-like notes to ripe strawberries, has been reported to have a negative impact on the consumers' acceptance [27].