Luís SilvaCaroline BrunelliRaphael MoreiraSofia BarbosaManuela FernandesAndreia MiguelBenvindo Maçãset al.2025-12-122025-12-122025-09-17Silva, L.; Brunelli, C.; Moreira, R.; Barbosa, S.; Fernandes, M.; Miguel, A.; Maçãs, B.; Valero, C.; Patanita, M.; Lidon, F.C.; et al. Response of Nearby Sensors to Variable Doses of Nitrogen Fertilization in Winter Fodder Crops Under Mediterranean Climate. Sensors 2025, 25, 5811. https://doi.org/ 10.3390/s25185811http://hdl.handle.net/10400.26/60381The sustainable intensification of forage production in Mediterranean climates requires technological solutions that optimize the use of agricultural inputs. This study aimed to evaluate the performance of proximal optical sensors in recommending and monitoring variable rate nitrogen fertilization in winter forage crops cultivated under Mediterranean conditions. A handheld multispectral active sensor (HMA), a multispectral camera on an unmanned aircraft vehicle (UAV), and one passive on-the-go sensor (OTG) were used to generate real-time nitrogen (N) application prescriptions. The sensors were assessed for their correlation with agronomic parameters such as plant fresh matter (PFM), plant dry matter (PDM), plant N content (PNC), crude protein (CP) in%, crude protein yield (CPyield) per unit of area, and N uptake (NUp). The real-time N fertilization stood out by promoting a 15.23% reduction in the total N fertilizer applied compared to a usual farmerfixed dose of 150 kg ha−1 , saving 22.90 kg ha−1 without compromising crop productivity. Additionally, NDVI_OTG showed moderate simple linear correlation with PFM (R2 = 0.52), confirming its effectiveness in prescription based on vegetative vigor. UAV_II (NDVI after fertilization) showed even stronger correlations with CP (R2 = 0.58), CPyield (R2 = 0.53), and NUp (R2 = 0.53), highlighting its sensitivity to physiological responses induced by N fertilization. Although the HMA sensor operates via point readings, it also proved effective, with significant correlations to NUp (R2 = 0.55) and CPyield (R2 = 0.53). It is concluded that integrating sensors enables both precise input prescription and efficient monitoring of plant physiological responses, fostering cost-effectiveness, sustainability, and improved agronomic efficiency.engreal-time fertilizationautomationdata analysismonitoringremote sensinggeographic information systemssustainabilityresearch article2025-12-02cv-prod-456678210.3390/s25185811