Remote evaluation of rice nitrogen utilization efficiency using chlorophyll-related spectral indices derived from unmanned aerial vehicle imagery

Introduction Nitrogen utilization efficiency (NUtE) directly reflects the efficiency of nitrogen remobilization to grains, serving as a key indicator of yield formation and environmental performance. However, conventional methods for assessing NUtE rely on destructive sampling and laboratory analysis, which are labor-intensive and time-consuming, whereas most existing remote sensing studies estimate NUtE by directly regressing spectral features against the final efficiency value without decomposing it into its underlying physiological components. Methods This study developed a remote-sensing-based indicator of rice NUtE based on chlorophyll-related vegetation indices at key rice growth stages, termed the Nitrogen Utilization Efficiency-Vegetation Index (NUtE-VI). NUtE showed a close and near-linear relationship with the ratio of panicle nitrogen accumulation from heading to dough stage (ΔPNA dough-heading , sink indicator) to leaf nitrogen accumulation at booting stage (LNA booting , source indicator). Therefore, with multi-site field experiments across different rice cultivars and nitrogen treatments, this study employed unmanned aerial vehicle imaging to accurately estimate rice leaf and panicle nitrogen accumulations, enabling rapid, large-scale evaluation of rice NUtE. Results This proposed index showed a strong correlation with measured NUtE (R 2 = 0.72, rRMSE = 10.84%) and effectively captured the distinct patterns of NUtE across different nitrogen treatments and cultivars. Discussion Our developed indicator is generalizable across diverse conditions for high-throughput selection of nitrogen-efficient cultivars and precision nitrogen management in sustainable agriculture.