UAVs Unlock New Insights into Wheat Senescence Dynamics

Our research team has introduced a novel approach (Song et al. 2025) to quantify wheat senescence dynamics by integrating UAV-based multispectral imaging with generalized additive models (GAMs).

Unlike traditional methods that capture only single time points, this study tracked the entire senescence process throughout the growing season and validated it, in collaboration with Prof. Minceva’s Lab at TUM, using laboratory measurements of leaf anthocyanins. The results revealed clear nitrogen-related differences among wheat varieties, demonstrating that the area under the curve (AUC) of UAV-derived vegetation indices strongly correlates with grain yield.

The newly proposed Senescence Dynamic Traits (SDTs) successfully distinguished both varietal and nitrogen treatment effects, offering a high-throughput, non-destructive tool for field phenotyping. This approach paves the way for characterizing crop senescence dynamics and accelerating wheat breeding through data-driven trait analysis.

Referance: Song X., Deng Q., Camenzind M., Luca S.V., Qin W., Hu Y., Minceva M. & Yu K. (2025). High-throughput phenotyping of canopy dynamics of wheat senescence using UAV multispectral imaging. Smart Agricultural Technology, 12, 101176. https://doi.org/10.1016/j.atech.2025.101176