## 3 Results and Discussion
### Construction of Quality Score Prediction Model  
#### 3.3.1 Selection of Characteristic Spectral Intervals via the siPLS Method  
The siPLS method was applied to construct prediction models for combinations of 2-4 spectral subintervals. The spectral intervals that achieved the lowest RMSECV were identified as the characteristic spectral intervals indicative of YCXY tea quality. The results are summarized in Table 2.  
As shown in Table 2, as the number of spectral subintervals increases from 10 to 24, all PLS models utilize four spectral subintervals. This indicates that four subintervals provide more useful modeling information compared to two or three subintervals. Consequently, dividing the full spectrum into an appropriate number of subintervals and selecting four for modeling yields the best prediction performance. As the number of subintervals increases, the RMSECV of the PLS models initially decreases and then increases. When the full spectrum is divided into 16 subintervals, subintervals [2; 3; 7; and 10] are selected, and the RMSECV reaches its lowest value (0.837). These subintervals represent the optimal spectral regions for predicting YCXY tea quality, corresponding to spectral ranges of 4377.6 cm\({}^{-1}\)-4751.7 cm\({}^{-1}\), 4755.6 cm\({}^{-1}\)-5129.7 cm\({}^{-1}\), 6262.7 cm\({}^{-1}\)-6633.9 cm\({}^{-1}\) \begin{table}
\begin{tabular}{c c c c} \hline
**Intervals** & **Factors** & **Subintervals** & **Proportion (\%)** & **RMSECV** \\ \hline
10 & 11 & [5 8 9 10] & 40.00 & 1.436 \\
11 & 11 & [5 8 9 10] & 36.36 & 1.355 \\
12 & 12 & [6 9 11 12] & 33.33 & 1.331 \\
13 & 11 & [7 10 11 13] & 30.77 & 1.239 \\
14 & 12 & [7 9 12 14] & 28.57 & 1.103 \\
15 & 12 & [7 10 14 15] & 26.67 & 1.005 \\
16 & 13 & [2 3 7 10] & 25.00 & 0.837 \\
17 & 13 & [6 7 10 16] & 23.53 & 0.876 \\
18 & 12 & [5 8 11 17] & 22.22 & 0.915 \\
19 & 11 & [11 12 15 19] & 21.05 & 0.919 \\
20 & 13 & [11 12 17 20] & 20.00 & 0.964 \\
21 & 12 & [7 12 17 20] & 19.05 & 0.992 \\
22 & 12 & [7 8 9 20] & 18.18 & 1.015 \\
23 & 14 & [4 13 15 18] & 17.39 & 1.129 \\
24 & 11 & [6 13 22 24] & 16.67 & 1.224 \\ \hline \end{tabular}
\end{table} 
Table 2: Results of siPLS calibration models for YCXY tea quality scores. Figure 4: MSC+SD preprocessed spectra. and 7386 cm\({}^{-1}\)-7756.3 cm\({}^{-1}\). Interestingly, the spectral intervals selected by the siPLS method account for only 25.00% of the full spectrum, but significantly enhance the model's predictive accuracy. Compared to the best results in Section 2.2, the RMSECV is reduced by 27.3%. The spectral range of 4377.6 cm\({}^{-1}\)-5129.7 cm\({}^{-1}\) corresponds to the first overtone absorption of the C-H bond and the second overtone absorption of the C=O bond. The range of 6262.7 cm\({}^{-1}\)-6633.9 cm\({}^{-1}\) reflects the second overtone absorption of the N-H bond, while 7386 cm\({}^{-1}\)-7756.3 cm\({}^{-1}\) represents the second overtone absorption of the C-H bond [35]. During the processing of YCXY tea, a series of biochemical reactions dominated by polyphenols occur, leading to the formation of new compounds rich in tea polyphenols, catechins, EGCG, ECG, and EGC, which are characterized by abundant C-H and C=O bonds. Moreover, Y CXY tea liquor contains significant amounts of free amino acids, which are closely associated with its freshness and positively correlated with tea quality, and these amino acids feature N-H bonds. Key quality-related compounds in Yongchuan Xiuyu tea, such as tea polyphenols and amino acids, contain chemical bond information (C-H, C=O, and N-H) that is detectable within the near-infrared spectral range. These spectral regions were identified using the siPLS method, enabling a more precise characterization of tea quality. The results show that the selected characteristic spectral intervals effectively represent the quality attributes of Yongchuan Xiuyu tea, confirming that the siPLS method is a robust and reliable approach for selecting key spectral intervals.