Abstract
Purpose Alignment of crop nitrogen (N) demand with N supply is crucial to improve N use efficiency of organic fertilizers whose N is largely bound organically. This study aimed to evaluate the potential of unmanned aerial vehicle (UAV)-based multispectral imagery to monitor in-season N uptake and to assess how different organic fertilizers affect N dynamics. Methods A field trial in Wallbach, Switzerland, compared untreated cattle slurry, anaerobically digested slurry, solid digestate, a mineral N control, and a zero-N control over two winter cereal seasons. UAV-acquired multispectral data were combined with environmental data (weather, soil and fertilizer) to model dry matter, N concentration, N uptake and the nitrogen nutrition index using random forest regression. Results The random forest models combining UAV-based multispectral imagery with environmental data showed good performance in predicting in-season N uptake of winter wheat (R 2 = 0.85, RMSE = 13.9 kg N ha − 1 ) and of winter barley (R² = 0.78, RMSE = 9.3 kg N ha − 1 ). Predicted N dynamics revealed transient N uptake maxima in organic treatments before fertilization, likely due to legacy fertilizer effects. Post-fertilization, N uptake increased most under mineral fertilization. N uptake dynamics were affected by fertilizer properties, with low C/N ratio and high NH 4 -N proportion showing stronger effects. Conclusion Highly temporal UAV-based multispectral imagery captures in-season N uptake dynamic and reveals differences in fertilizer N release caused by quality differences of organic fertilizers. These insights support optimized fertilizer application for better synchronization of N mineralization with crop demand.