Foliar residue dynamics of azadirachtins following direct stem injection into white and green ash trees for control of emerald ash borer
Bibliographic record
Abstract
BACKGROUND: Azadirachtins are natural insecticides derived from the neem tree. The emerald ash borer (EAB) is an exotic invasive insect pest that infests various ash tree species and has the potential for significant economic, aesthetic and ecological impacts throughout North America. The initial translocation and foliar residue dynamics of azadirachtins were examined following direct injection into white and green ash trees growing in urban scenarios as a potential control for EAB. RESULTS: Substantial concentrations of azadirachtins A and B [mean maxima > 0.98 mg kg(-1) fresh weight (f.w.)] were observed within 2 days of injecting a specifically designed formulation of azadirachtins. Foliar residues declined exponentially through time, with half-life estimates ranging from 5.1 to 12.3 days. At the time of leaf senescence, foliar residue levels approximated 0.01 mg kg(-1) f.w., strongly mitigating the potential effects of non-target biota in soil or aquatic compartments. CONCLUSION: The magnitude and duration of exposures observed in this field study were considered to be above the thresholds required for biological effectiveness against both larval and adult life stages of EAB. Results support the use of azadirachtins as an environmentally acceptable systemic insecticide for control of EAB and protection of high-value ash trees in urban environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 source (direct Gemma or distilled Codex), 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".