UAV-Based Multispectral and RGB Imaging Techniques for Dry Bean Phenotyping
Bibliographic record
Abstract
This study investigates the unmanned aerial vehicle (UAV) (UAV)-based multispectral and RGB sensors to estimate dry bean breeding population canopy height, biomass yield, and physiological maturity. We collected the UAV data and conducted ground measurements over the AAFC Lethbridge research farm in Alberta, Canada. The canopy height model was computed by the difference between the digital surface model and the digital elevation model. The Normalized Difference Vegetation Index (NDVI) was used to relate the crop biomass yield. Additionally, the Modified Chlorophyll Absorption Reflectance Index (MCARI) was found to be robust in the estimation of dry bean crop maturity. Compared to the canopy height and biomass yield, the UAV-based imagery can better predict the physiological maturity dates for plant breeding applications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".