Analysis of changes in rice yield components and vegetation indices in response to lodging timing during the grain-filling stage, lodging severity, and nitrogen fertilization

Lodging in rice (Oryzasativa L.) is a major agronomic constraint that significantly reduces grain yield and quality. This study investigated the effects of lodging timing during the grain-filling stage, lodging severity, and nitrogen fertilization levels on ripened grain ratio and thousand-grain weight in two widely cultivated cultivars, Sindongjin and Chamdongjin. Field experiments were conducted in a split–split plot design with four nitrogen levels (90, 130, 150, and 200 kg ha⁻¹), three lodging timings (19, 27, and 39 days after heading, DAH), and five lodging severities (0°, 30°, 45°, 60°, and 90°). Lodging was induced by bending stems to predetermined angles, and yield components were measured after harvest. Multispectral imagery was acquired at approximately weekly intervals using a UAV equipped with a multispectral camera, and nine vegetation indices (VIs) were calculated to monitor canopy responses. Ripened grain ratio declined markedly under early lodging (19 DAH), reaching 74.81% in Chamdongjin, whereas late lodging (39 DAH) caused minor reductions, up to 87.64%. Complete lodging (90°) resulted in the most severe yield losses, decreasing ripened grain ratio from 86.19 to 67.02% in Sindongjin and from 74.81 to 58.02% in Chamdongjin. Thousand-grain weight showed a similar trend, decreasing from 25.04 to 23.62 g and from 24.79 to 23.76 g, respectively. A significant three-way interaction was observed among lodging timing, severity, and nitrogen level. The lowest ripened grain ratio (30.36%) occurred under early and complete lodging with 150 kg ha⁻¹ nitrogen, whereas the highest (91.81%) was recorded under late lodging, no lodging, and 130 kg ha⁻¹ nitrogen. UAV-based vegetation indices (BNDVI, GNDVI, LCI, NDRE, and SIPI2) significantly decreased under complete lodging, and PLS-DA enabled clear classification of lodging severity. These findings demonstrate that the interaction of lodging factors strongly affects yield components and that UAV-derived vegetation indices are effective tools for assessing lodging severity and timing.