Control of conifer defoliators with neem-based systemic bioinsecticides using a novel injection device
Bibliographic record
Abstract
Abstract A systemic tree injection tube was designed to introduce the required volumes of neem-based bioinsecticides into conifer trees. The device consists of plastic tubing attached with hose clamps to a maple sap spile at one end and a tubeless automobile tire valve at the other end. A hole is drilled in the tree, the spile is hammered into the hole, the device is filled with the systemic insecticide, and the system is pressurized by attaching a bicycle pump to the tire valve. The parts are readily available, the device is simple to construct and easy and quick to install on a tree, application volumes are adjustable, and the device is reusable. This device has been used successfully to inject 188 trees representing four conifer species in either spring or fall, primarily with neem formulations but also with dimethoate, imidacloprid, and acephate. In most cases, all of the material was injected into the trees without leakage, although neem formulations were characteristically slow to enter the trees and certain neem formulations were not injected completely at volumes above 15 mL per injection tube. Dosages of 0.2 g azadirachtin/cm of diameter at breast height (dbh) or less provided control of pine false webworm, spruce budworm, cedar leafminers, gypsy moth, and introduced pine sawfly on red pine, white spruce, eastern white cedar, white pine, and white pine, respectively. Dosages as low as 0.005 g active ingredient/cm of dbh applied with injection tubes in either one or two holes per tree resulted in a 95% reduction in defoliation of mature (mean dbh ± SD = 23.4 ± 3.3 cm) red pine caused by pine false webworm.
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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".