## 3 Results and Discussion
### Sensitive Waveband Analysis  
The RF algorithm was used to analyze the relative importance of each wavelength to investigate the intrinsic mechanism of the machine learning model to predict the tea polyphenol content of fresh tea leaves. The number of iterations was set to 1000, the probability threshold was chosen to be 15%, the processing method was chosen to be \"center\", and the first 62 wavebands with higher probability were finally taken as sensitive wavebands (Figure 8a). From (Figure 8b), the sensitive wavebands of tea polyphenol content of fresh tea leaves are mainly distributed in 402-448 nm, 555-600 nm, 810-1042 nm, 1056-1103 nm, 1219-1323 nm, 1406-1416 nm, and 1499-1511 nm.  
Figure 8: Sensitive wavebands related to tea polyphenol content extracted by RF algorithm. (**a**) Selection probability of different wavelengths, and (**b**) distribution of the first 62 selected sensitive wavebands.  
Figure 7: LS-SVR modeling performances of predicting tea polyphenol content based on dual-band spectral data. (**a**) Correlation analysis of a scatter plot. The hollow square and circle markers denote the calibration set and prediction set, respectively. The black line is the regression for the whole set. (**b**) Comparison of predicted and measured values of tea polyphenol content. The solid square and circle markers represent the measured value and predicted value, respectively.  
A total of 12 sensitive wavelengths (402, 406, 416, 417, 420, 424, 448, 555, 562, 563, 600, and 705 nm) are located in the visible spectral region (400-780 nm), which correspond to the absorption properties of the auxochromes (e.g., -OH, -NH, and -SH) and chromophores (e.g., carboxyl, ester group, aromatic systems) within the fresh tea leaves [44, 45, 46]. There are 20 sensitive wavelengths (810, 821 856, 865, 884, 885, 894, 895, 910, 914, 934, 983, 990, 993, 995, 1020, 1027, 1034, 1040, and 1042 nm) in the short-wave NIR spectral region (781-1050 nm), which mainly attribute to the second and third overtones of the O-H group or C-H group vibrations of phenols [47, 48]. There are 30 sensitive wavebands (1056, 1074, 1103, 1219, 1220, 1221, 1222, 1225, 1228, 1229, 1254, 1285, 1286, 1294, 1317, 1318, 1320, 1321, 1323, 1406, 1411, 1412, 1414, 1416, 1499, 1501, 1502, 1505, 1508, and 1511 nm) in the long-wave NIR spectral region (1051-1650 nm), depending on the O-H or methyl C-H group in the phenolic. Among them, 1020, 1027, 1034, 1040, 1042, 1056, 1074, and 1103 nm correspond to the second overtones of the O-H group [49]; 1219, 1220, 1221, and 1222 nm relate to the second overtones and combination of the C-H group stretching vibration of -CH\({}_{2}\)[50]; 1225, 1228, 1229, 1254, 1285, 1286, 1294, 1317, 1318, 1320, 1321, and 1323 nm are the second overtones and combination of C-H group stretching vibrations [51, 52]; 1406, 1411, 1412, 1414, and 1416 nm are associated with the first overtones of free O-H group vibrations; 1499, 1501, 1502, 1505, 1508, and 1511 nm reflect the first overtones of the N-H group stretching vibrations [8]. This demonstrated that the prediction of tea polyphenol content of fresh tea leaves using dual-band spectral data combined with LS-SVR model depends on close correlation between phenolic compounds and auxochromes, chromogenic groups, and hydrogen-containing groups (e.g., -OH, -NH, and -CH) [34].