Near-infrared imagery from unmanned aerial systems and satellites can be used to specify fertilizer application rates in tree crops
Bibliographic record
Abstract
Aerial images obtained using an unmanned aerial system (UAS) were used to create a classified image showing tree canopy health in a macadamia orchard. The resulting map was used to modify management of a macadamia plantation. Vegetation indices, principally the Canopy Chlorophyll Content Index (CCCI), derived from both UAS and WorldView2 satellite imagery, were compared and correlated with spectral radiometry and leaf nitrogen levels determined by field sampling. Classified CCCI images from both sensor types were integrated into farm management software (PAM Ultracrop) and processed into a suitable format for driving a GPS-controlled fertilizer spreader for more effective control of nitrogen application rates. Applying fertilizer at a variable rate according to tree health will result in cost savings to the industry and potentially increase production.
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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) | 0.000 | 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".