Claim · model-written summary
On-ground calibration areas improved accuracy by an average of 28% and up to 48% for the line-based approach in narrow rows.
- Taxon
- soybean
Glycine maxt0 - Treatment
- on‐ground calibration arease1
- Outcome
- accuracye1
- Direction
- improvede1
- Value
- an average of 28% and up to 48%e1
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleComparatorSettingQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“stand counts in soybean”
e1“Incorporating on‐ground calibration areas improved accuracy by an average of 28% and up to 48% for the line‐based approach in narrow rows”
Title
Salem Ermish; Rachel Vann; Jason Ward; et al. Agronomy Journal 2026. doi:10.1002/agj2.70303
Other claims from this paper (7)
- Method / resource The point-based UAV counting method gave its highest accuracy, within ±12% of ground-truth with R 2 = 0.81, when imagery was collected 14 to 20 DAP at 15.2-m altitude.
- Association UAV count accuracy declined beyond 27 DAP as canopy overlap increased.
- Observation The line-based method remained more stable across altitudes and later growth stages.
- Observation The line-based method consistently overestimated plant counts, particularly in dense and narrow row canopies.
- Intervention effect Row spacing and plant removal patterns had minimal effects on UAV prediction error.
- Observation Short repeating gaps were poorly detected by the line-based method.
- Recommendation The authors conclude that UAV-based plant counts in soybean are feasible and dependable when flights are timed during early vegetative growth and supported by calibration.