Remote Screening of Nitrogen Uptake and Biomass Formation in Irrigated and Rainfed Wheat

Sustainable nitrogen (N) management in arable crops requires the real-time assessment of crop growth and N uptake, particularly in water-limited environments. In the present study, we conducted two large-scale field experiments with rainfed and irrigated wheat in South-East Turkey to evaluate the effectiveness of drone- and satellite-based spectral indices, in combination with neural network models, for estimating biomass and nitrogen uptake. Four N fertilizer rates in the irrigated fields (N0: 0, N6: 60, N12: 120, and N16: 160 kg N ha−1) and five N rates in the rainfed fields (N0: 0, N2: 20, N4: 40, N5: 50, and N6: 60 kg N ha−1) were tested. Highest fresh biomass was 57.7 ± 1.1 and 15.9 ± 1.0 t/ha−1 for irrigated and rainfed treatments, respectively, with 2.5-fold higher grain yield in irrigated (8.2 ± 1.2 t/ha−1) compared to rainfed (2.9 ± 0.9 t/ha−1) wheat. Drone-based spectral indices, especially those based on the red-edge region (CLRed_edge), correlated strongly with biomass (R2 > 0.9 in irrigated wheat) but failed to explain crop N concentration throughout the vegetation period. This limitation was attributed to the nitrogen dilution effect, where increasing biomass during crop growth leads to a decline in the concentration of nitrogen, complicating its accurate estimation via remote sensing. To address this, we employed a two-layer feed-forward neural network model and used SPAD and plant height values as supplementary input parameters to enhance estimations based on vegetation indices. This approach substantially enhanced the predictions of N uptake (R2 up to 0.95), while even simplified model version using only NDVI and plant height parameters achieved significant performance (R2 = 0.84). Overall, our results showed that spectral indices are reliable predictors of biomass but insufficient for estimating nitrogen concentration or uptake. Integrating indices with complementary crop traits in nonlinear models provides acceptable estimates of N uptake, supporting more precise fertilizer management and sustainable wheat production under water-limited conditions.