Researchers in China have unveiled a low-cost drone imaging method that captures wheat height in fine detail, revealing subtle variations within plots and identifying genetic regions that traditional measurements often miss. The approach uncovered 11 stable height-related genetic loci—including two that appear to be new—and produced molecular markers that could speed the development of higher-yield, lodging-resistant wheat.
(A) An overhead view of a CCO imaging comprising two individual circles with a 50 % overlap between them. (B) Schematic diagram of wrap-around photography in CCO imaging. (C) Side view of the CCO imaging. Image Credit: Chinese Academy of Sciences
Wheat (Triticum aestivum L.) supplies roughly one-fifth of the world’s calories, making plant height (PH) a crucial trait for farmers and breeders. Taller plants are more likely to topple in wind or rain, while shorter ones may produce less biomass and have lower photosynthetic efficiency.
Dwarfing genes introduced during the “Green Revolution” boosted yields, but breeders still seek the ideal balance between productivity and resilience. Measuring height in the field is usually done by hand, a slow and error-prone process that overlooks variation within plots.
The study, published in Plant Phenomics by Yuntao Ma and Yonggui Xiao of China Agricultural University and the Chinese Academy of Agricultural Sciences, tested UAV cross-circling oblique (CCO) imaging against conventional nadir imaging. Both flew at the same altitude and overlap settings, with extra plots added to increase height variability.
CCO imaging produced denser, more accurate 3D point clouds and captured canopy detail—especially at plot edges—better than nadir imaging. Heights were calculated at 11 quantiles, with the 90 % quantile most closely matching field measurements. Lower quantiles sometimes reflected stem rather than canopy height. The detailed reconstructions even showed wheat spikes, though side-view capture was limited when plots were tightly packed.
In recombinant inbred line (RIL) populations, both field-measured and 3D heights followed normal distributions, with strong correlations across quantiles and high broad-sense heritability (0.775–0.959 within environments; 0.975–0.982 across environments). The 90 % and 92 % quantiles achieved RMSEs below 2 cm in most cases, with correlations up to 0.99.
QTL mapping across seven environments identified 106 loci for PH, with 40 shared between field and 3D methods and 11 stable loci unique to the multi-level 3D approach. Two—QPhzj.caas-3A.2 and QPhzj.caas-7A.1—appear to be new. Both were developed into KASP molecular markers, validated in natural populations, and linked to significant height differences under varied irrigation. Candidate gene analysis also identified Rht5, a gibberellin-sensitive dwarfing gene, and TaGL3-5A, associated with grain length and weight—both confirmed via KASP validation.
The combination of UAV CCO imaging and multi-level 3D plant height analysis gives breeders a precise, affordable, and scalable way to assess crop height in the field. By identifying genetic loci that standard measurements can overlook, the method makes marker-assisted selection more efficient, accelerating the breeding of wheat varieties that are both high-yielding and resistant to lodging. The researchers note that the same approach could be applied to other crops where canopy structure and height are key traits, opening the door to new gains in precision agriculture and crop improvement.
Journal Reference:
Fei, S., et al. (2025) Genetic resolution of multi-level plant height in common wheat using the 3D canopy model from ultra-low altitude unmanned aerial vehicle imagery. Plant Phenomics. doi.org/10.1016/j.plaphe.2025.100017.