LAUSR

Previous studies on estimating leaf nitrogen concentration (LNC) and grain protein concentration (GPC) from canopy reflectance did not pay particular attention to the nitrogen (N) and protein absorption features, which are mostly located in the shortwave infrared (SWIR) region and challenging to use due to the adverse effect of water absorption. This study aimed to develop a new approach to mitigate the effect of water signals from canopy reflectance spectra of winter wheat and enhance the absorption features of N and protein in the SWIR region. The water effect at the canopy level was removed by using the simulated dry-canopy reflectance (SDR) spectra based on the radiative transfer models, and a three-band spectral triangle index (STI) was constructed to capture the chemical-specific absorption variations of N and protein. The results demonstrated that these absorption features became sufficiently apparent by canopy water removal. With the SDR spectra, the STIs with three bands related to N and protein absorption features in SWIR subregions exhibited remarkably stronger correlations with LNC and GPC than those with the measured reflectance (MR) spectra. Specifically, STI $_{2060-2180-2240}$ from the SDR spectra achieved the top sensitivity to LNC and GPC. The combination of plant pigment ratio (PPR) and STI $_{2060-2180-2240}$ yielded significantly lower root-mean-square error (RMSE) values (LNC: RMSE = 0.19% and GPC: RMSE = 0.67%) than either one alone. The integration of water removal and STI could help us better understand the underlying mechanism on the relationships of LNC and GPC with N and protein absorption features.