Laboratory Evaluation of the Toxicity of Systemic Insecticides to Emerald Ash Borer Larvae
Bibliographic record
Abstract
Emerald ash borer (Agrilus planipennis Fairmaire) (Coleoptera: Buprestidae), an invasive phloem-feeding insect native to Asia, threatens at least 16 North American ash (Fraxinus) species and has killed hundreds of millions of ash trees in landscapes and forests. We conducted laboratory bioassays to assess the relative efficacy of systemic insecticides to control emerald ash borer larvae in winter 2009 and 2010. Second- and third-instar larvae were reared on artificial diet treated with varying doses of emamectin benzoate (TREE-äge, Arborjet, Inc., Woburn, MA), imidacloprid (Imicide, J. J Mauget Co., Arcadia, CA), dinotefuran (Safari, Valent Professional Products, Walnut Creek, CA), and azadirachtin (TreeAzin, BioForest Technologies, Inc., Sault Ste. Marie, Ontario, and Azasol, Arborjet, Inc., Woburn, MA). All of the insecticides were toxic to emerald ash borer larvae, but lethal concentrations needed to kill 50% of the larvae (LC50), standardized by larval weight, varied with insecticide and time. On the earliest date with a significant fit of the probit model, LC50 values were 0.024 ppm/g at day 29 for TREE-äge, 0.015 ppm/g at day 63 for Imicide, 0.030 ppm/g at day 46 for Safari, 0.025 ppm/g at day 24 for TreeAzin, and 0.027 ppm/g at day 27 for Azasol. The median lethal time to kill 50% (LT50) of the tested larvae also varied with insecticide product and dose, and was longer for Imicide and Safari than for TREE-äge or the azadirachtin products. Insecticide efficacy in the field will depend on adult and larval mortality as well as leaf and phloem insecticide residues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".