## 3 Results and Discussion
(**a**–**h**) respectively represents the position of red edge (REP), the slope of red edge (RES), the reflectance of red valley (RRV), the reflectance of green peak (RGP), the position of green peak (GPP), the reflection of water stress band (RWSB), the position of yellow edge (YEP), and the slope yellow edge (YES) under different parasitic intensities. chlorophyll content of _Osmanthus fragrans_ under different parasitic degrees. According to the results in Figure 7, the spectral parameter model with the highest accuracy was selected. Then, a prediction model is established with the most sensitive spectral parameters as independent variables and chlorophyll content as dependent variable. Finally, the accuracy of the model was further verified by analyzing the predicted and measured values calculated by the linear regression model (Figure 8). As shown in Figure 8, the chlorophyll inversion model of red valley reflectance was tested, and it was found that the prediction accuracy of this model was high and stable (\(R^{2}\) = 0.8811, RMSE = 0.0004). \begin{table}
\begin{tabular}{c c c c c} \hline  & **RRV** & **RGP** & **RES** & **RWSB** \\ \hline LT & 0.25218 & \(-\)0.1787 & \(-\)0.28318 * & 0.09577 \\ LA & \(-\)0.01651 & 0.18462 & \(-\)0.14292 & 0.0353 \\ LDMC & 0.01136 & \(-\)0.00523 & 0.03048 & 0.09512 \\ SLA & 0.20281 & \(-\)0.24112 & \(-\)0.06407 & 0.0641 \\ LTD & \(-\)0.19553 & 0.17124 & 0.13662 & \(-\)0.01367 \\ CCI & \(-\)0.82993 ** & 0.72953 ** & 0.65295 ** & \(-\)0.56967 ** \\ \hline \end{tabular}
\end{table} 
Table 2: Pearson correlation analysis between plant traits and spectral parameters. * indicates that the correlation reaches a significant level at the level of \(p\) < 0.05. and ** indicates a significant correlation reaches a significant level at the level of \(p\) < 0.01. Figure 7: Linear correlation between functional traits and spectral parameters. (**a**) the reflection of red valley (RRV) and CCI, (**b**) the reflectance of green peak (RGP) and CCI, (**c**) the slope of red edge (RES) and CCI, (**d**) the reflection of water stress band (RWSB) and CCI, (**e**) the reflectance of green peak (RGP) and LT. Effects of Parasitic Plants on the Correlation of Functional Traits of Osmanthus fragrans and Analysis of Leaf Economics Spectrum  
There was an interdependent relationship between the functional traits of the leaves (Table 3). There was a significant positive correlation between LA and SLA. There was a significant negative correlation between SLA and LDMC and LTD. LA was significantly negatively correlated with LDMC and LTD. There was a significant negative correlation between LT and LTD. There was a very significant positive correlation between LDMC and LTD. There was a significant positive correlation between CCI and SLA. At the same time, LT has a negative correlation with SLA and LA, but the correlation has not reached a significant level. Studies have shown that leaf functional traits can reflect the adaptability of plants to the environment, but compared with a single leaf functional trait, continuous leaf economics spectrum can better reflect the growth strategy and adaptation mechanism of plants [54; 55]. In this study, there was an obvious trade-off relationship between the functional traits of plant leaves, which indicate that when plants are harmed by parasitic plants, host plants show certain ecological trade-off strategies in terms of functional traits for survival. SLA is closely related to the growth and survival strategy of plants, which can represent the adaptability of plants to the environment and the ability to obtain resources [58]. In this study, after being invaded by parasitic plants, the reduction of SLA of the host plants makes the plants adapt to resource-poor environment. LDMC represents the plants to maintain water and nutrients (cellulose, protein and Nitrogen content, etc), while LTD reflects the bearing capacity and defense ability of plant leaves, which is closely related to the turnover growth rate of leaves [59; 60; 61].