2026/05/01 by Keely E. Brown, Haley Schuhl, Dhiraj Srivastava +4 · 2 voices
Agricultural and Biological Sciences · Engineering · #Crop Yield and Soil Fertility #Plant Surface Properties and Treatments #Soil Mechanics and Vehicle Dynamics
paper · pdf · doi:10.1002/pld3.70173
openalex publication_date 2026/05/01 · openalex created_date 2026/05/24 · openalex updated_date 2026/07/23
ABSTRACT Lodging is a major contributor to decreased yield in tef, a staple cereal crop in Ethiopia. Semidwarf varieties have been developed with a goal to increase yield through reduced lodging, but studying lodging susceptibility currently requires a labor‐intensive, imprecise, manual scoring method. Here we present workflows for analyzing tef stand height from UAS sensors across time to both predict lodging later in the season with early height and to measure the severity of lodging after a storm event. We compare 3D point clouds generated by photogrammetry from RGB images with those generated from LiDAR to estimate height, demonstrating that they produce similar results, despite differences in cost. Stand height and lodging can both be accurately measured with low‐cost UAS, reducing the need for manual measurements and increasing precision and temporal resolution in plant breeding programs.