Abstract
Optimizing nitrogen (N) management in rainfed spring barley (Hordeum vulgare L.) production remains a formidable agronomic challenge in the semi-arid steppe environments of Southern Russia, where erratic precipitation and terminal drought frequently constrain nutrient uptake and grain quality. This two-year field investigation (2022–2023) evaluated the efficacy of variable-rate and split N fertilization regimens guided by multispectral remote sensing data (Sentinel-2 and unmanned aerial vehicle-derived NDVI and NDRE indices) on the grain yield, crude protein content, and nitrogen use efficiency (NUE) of spring barley grown on Calcic Chernozem soils in the Rostov region. Experimental treatments included five total N levels (0, 30, 60, 90, and 120 kg N ha-1) applied either entirely at sowing or partitioned between basal application and tillering/stem elongation topdressing adjusted using vegetation indices. Results demonstrated that sensor-directed split applications (60 kg N ha-1 basal + 30 kg N ha-1 topdressing) maximized grain yield (3.84 t ha-1) and agronomic nitrogen efficiency (18.2 kg grain kg-1 N applied), while maintaining malting-grade protein concentrations below 11.5%. Canopy NDRE assessed at the early stem elongation stage (Zadoks GS31) exhibited the strongest predictive correlation with final grain yield (r = 0.88, p < 0.001). Integrating multispectral remote sensing into split-nitrogen scheduling significantly mitigates the risk of luxury N consumption and economic loss under fluctuating rainfed conditions in Southern Russia.
