## 5 Conclusions  
This paper focuses on studying winter wheat at the nodulation and flowering stages in the experimental field of Leiling, Shandong Province. The canopy spectral curves of winter wheat at two fertility stages were obtained using ASD and UHD185. The NNI estimation model of winter wheat was constructed using the ASD spectral reflectance of the canopy as a reference. The optimal spectral indices were selected based on the combination of the acquired UHD185 spectral data. The main conclusions are as follows:  
1. A comparison of the spectral curves and spectral reflectance of the samples obtained by the airborne high-speed imaging spectrometer UHD185 and the portable non-imaging spectroradiometer ASD reveals that there is a strong correlation in the spectral reflectance collected by both sensors in the range of 454 nm to 830 nm. Furthermore, the spectral reflectance obtained by the ASD and the UHD185 are highly correlated, indicating that the spectral reflectance measured by the UHD185 is trustworthy within this wavelength range. The image data in this specific band range are highly dependable, and the spectral reflectance within this band range can be chosen for modeling research. 2. The most optimal combination of bands that shows a strong correlation in the original spectrum is the NDSI (R\({}_{682}\), R\({}_{578}\)), which combines wavelengths of 682 nm and 578 nm. The coefficient of determination (\(R^{2}\)) for this combination is 0.77. Similarly, in the first-order derivative spectrum, the best correlation band combination is the NDSI (FD\({}_{830}\), FD\({}_{678}\)), which combines wavelengths at 666 nm and 826 nm. The coefficient of determination (\(R^{2}\)) for this combination is 0.79. Hence, the utilization of the winter wheat's NDI content inversion can be employed for the purpose of modeling and analysis. The most optimal spectral indices for determining the nitrogen nutrition index in winter wheat are RSI (R\({}_{682}\), R\({}_{578}\)) and (FD\({}_{666}\), FD\({}_{826}\)). Additionally, the most effective spectral indices for differentiation are DSI (R\({}_{826}\), R\({}_{830}\)) and DSI (FD\({}_{810}\), FD\({}_{690}\)). 3. The model created using the first-order derivative spectra had higher accuracy compared to the model created using the original spectra, with an \(R^{2}\) value above 0.83. This suggests that using the first-order derivative spectra can enhance the estimation accuracy of the winter wheat NNI. 4. The linear model created using the ratio spectral index RSI (FD\({}_{666}\), FD\({}_{826}\)) was found to be the most accurate in estimating the nitrogen nutrient index of winter wheat. The model had a modeling \(R^{2}\) value of 0.85, an RMSE of 0.15, and an RE of 12%. The model was further validated, with a validation \(R^{2}\) value of 0.75, an RMSE of 0.18, and an RE of 10%, corresponding to the equation \(y=-2.0655x+0.156\). The methodology is straightforward and user-friendly, enabling more efficient inversion of winter wheat nitrogen feeding. Conceptualization, L.H. ; methodology, L.H. and W.L. ; software, L.G. ; validation, L.H. and W.L. ; formal analysis, L.H. ; investigation, W.L. ; resources, L.H. ; data curation, Z.C. ; writing--original draft preparation, L.H. ; writing--review and editing, J.J. and Z.Z. ; visualization, W.L. ; supervision, Z.C. ; project administration, J.J. and Z.C. ; funding acquisition, J.J. and Z.C. All authors have read and agreed to the published version of the manuscript. This research was funded by [the State Key Project of National Natural Science Foundation of China-Key projects of joint fund for regional innovation and development] grant number [U22A20620 U21A20108] and [Doctoral Science Foundation of Henan Polytechnic University] grant number [B2021-20] and [Department of Natural Resources of Henan Province Natural Resources Science and Technology Project] grant number [[PERSON] (2) 20190450-7]. Not applicable. Data Availability Statement: Data is unavailable due to privacy or ethical restrictions.