Dynamic monitoring of rice plant height during the early growth stage using UAV-LiDAR and GWAS analysis of growth rate

Plant height during the early growth stage of rice is a key indicator reflecting canopy establishment rate, tillering potential, and overall growth vigor, all of which critically determine final yield formation. Conventional manual measurements fail to capture high-frequency, continuous, and non-destructive monitoring of plant height dynamics, limiting the understanding of early growth vigor and its genetic mechanisms. In this study, a UAV-based LiDAR system was employed to acquire canopy point clouds of 211 rice accessions across ten time points within 40 days after transplanting. High-resolution canopy height models (CHMs) were generated, and continuous plant height trajectories H(t) were reconstructed using piecewise cubic Hermite interpolation (PCHIP). The first derivative V(t) quantified growth rate dynamics and identified the timing of maximum growth (T max ), enabling precise differentiation of early growth patterns among geno-types. Genome-wide association analysis (GWAS) using a mixed linear model (MLM, Q+K) detected 604 significant SNPs, among which 33 were stably expressed across environments. Five candidate genes were identified within ±200 kb windows, mainly encoding proteins related to cell elongation, hormone signaling, and photosynthetic metabolism. The results highlight that LiDAR-based dynamic monitoring of plant height, coupled with genomic association analysis, provides a robust framework for quantifying rice early growth vigor and elucidating its molecular basis, offering valuable guidance for breeding high-vigor “early-establishing” rice cultivars.