## 3 Results and Discussion
(Panel **(B)**): Magnified view of the spectral fingerprint region (1200–800 cm\({}^{-1}\)), dominated by vibrational modes of sugars. (Panel **(C)**): Second derivative of spectra in the 1200–800 cm\({}^{-1}\). The relationships between ATR-FTIR data and the chemical parameters including TA, TP, AA and TSS, detected as reported in [20] (Table S2), were assessed by the heatmap of Figure 5. Two clusters were discovered for the chemical data. Specifically, TA, TP and AA behave similarly being positively correlated to the IR signals in the regions 3650-2700 cm\({}^{-1}\) and 1500-600 cm\({}^{-1}\), while TSS showed an opposite trend. Only TA resulted to be significantly correlated to the ATR-FTIR data and, in particular, to the two bands in the region 3650-2700 cm\({}^{-1}\) and with the peaks in the regions 1500-1280 cm\({}^{-1}\) and 1160-700 cm\({}^{-1}\). In other words, TA resulted to be the chemical attribute more related to IR data and the IR spectra mirrored the behaviour of TA. Generally, TA decreases during ripening due to the conversion of organic acids into sugars [29], and it is an objective indicator of maturity stage. Consequently, its prediction by ATR-FTIR might be a valid solution for a fast and non-destructive assessment of the ripening stage in strawberries. Figure 4: PCA model of the ATR-FTIR data: score scatter plot (panel (**A**)) and average profile of the SNV data coloured according to the first loading vector (panel (**B**)); in panel A, circles represent the technical replicates, triangles indicate the medians of the technical replicates of the same sample and green is used for observations belonging to the half-red group while red is used for those of the red group. Image Analysis Discrimination of the Ripening Stage of \"Candonga\" Strawberries and Correlation Analysis with Chemical Data  
Four samples of 12 \"Candonga\" strawberries were obtained pooling the collected fruit at each harvest time and at two different ripening stages, achieving a total of 12 samples for the half-red and 12 samples for the red fruit. Eight technical replicates were performed for each sample obtaining a data set composed of 192 observations and five variables (measuring colour attributes). All colour parameters obtained by strawberry image analysis allowed us to significantly discriminate the half-red and the red samples, as reported in Table 2.  
Indeed, for all the colour parameters considered the half-red samples showed median values significantly higher than red ones at each harvest time (fold changes greater than 1). This result is clearly visible also looking at the score scatter plot obtained by PCA analysis (autoscaled data, two principal components, R\({}^{2}\) = 0.999), using as variable the colour data (Figure 6). Red and half-red strawberries clustered in two different regions, at the right-hand side and at the left-hand side along the first component, respectively. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**ID** & **Half-Red** & **Red** & \(p\) & **FC** & **AUC** & **CI** \\ \hline \multirow{3}{*}{\(L^{\star}\)} & 15.71 & 10.58 & \multirow{3}{*}{\(<\)0.001} & \multirow{3}{*}{0.676} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00–1.00} \\  & [13.61–16.81] & [9.78–11.40] & & & & \\ \cline{1-1} \cline{5-6}  & 25.78 & 20.23 & \multirow{3}{*}{\(<\)0.001} & \multirow{3}{*}{0.787} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00–1.00} \\  & [23.28–27.46] & [19.02–21.58] & & & & \\ \cline{1-1} \cline{5-6} \(b^{\star}\) & 16.40 & 10.16 & \multirow{3}{*}{\(<\)0.001} & \multirow{3}{*}{0.621} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00–1.00} \\  & [14.03–17.72] & [9.14–11.31] & & & & \\ \cline{1-1} \cline{5-6} Chroma & 30.51 & 22.62 & \multirow{3}{*}{\(<\)0.001} & \multirow{3}{*}{0.741} & \multirow{3}{*}{1.00} & \multirow{3}{*}{1.00–1.00} \\  & [27.23–32.56] & [21.20–24.36] & & & & \\ \cline{1-1} \cline{5-6} Hue-angle & 0.56 [0.53–0.59] & 0.46 [0.44–0.48] & & & & \\ \hline \hline \end{tabular}
\end{table}