Drone-based hyperspectral imagery was used to predict phosphorus (P) content in winter rye using Feedforward Neural Networks (FNNs). Model validation against laboratory data showed good agreement between predicted and measured values (R² = 0.36, RMSE = 0.84 g/kg, accuracy = 64%).The analysis identified key wavelength ranges contributing to the prediction model.