Evaluation of the toxicity of 17 essential oils against <i>Choristoneura rosaceana</i> (Lepidoptera: Tortricidae) and <i>Trichoplusia ni</i> (Lepidoptera: Noctuidae)
Bibliographic record
Abstract
BACKGROUND: The obliquebanded leafroller, Choristoneura rosaceana Harris, and the cabbage looper, Trichoplusia ni Hübner, are serious fruit and vegetable pests requiring multiple insecticide applications per year. To reduce non-target exposure to hazardous insecticides and to curb resistance development, alternative controls are required. Accordingly, a selection of 17 essential oils was screened against both lepidopteran pests, and the influence of azinphos-methyl resistance on essential oil toxicity to C. rosaceana was studied. RESULTS: Of the 17 essential oils screened, patchouli oil (Pogostemon cablin Benth.) and thyme oil (Thymus vulgaris L.) were selected for further testing against C. rosaceana, whereas patchouli oil, garlic oil (Allium sativum L.) and lemongrass oil (Cymopogon nardus L.) were selected for further testing against T. ni. LC(50) and LD(50) values confirmed that patchouli oil was the most toxic to C. rosaceana larvae, with LC(50) = 2.8 µL mL(-1) and LD(50) = 8.0 µg insect(-1). Garlic oil was the most toxic oil to T. ni larvae with LC(50) = 3.3 µL mL(-1) and LD(50) = 22.7 µg insect(-1), followed by patchouli oil and lemongrass oil. Azinphos-methyl-resistant leafrollers were 1.5-fold more tolerant to patchouli oil and 2.0-fold more tolerant to thyme oil. CONCLUSIONS: Based on these results, patchouli oil and other essential oils have sufficient efficacy to be considered as components of an essential oil-based insecticide that targets these lepidopteran pests.
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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) | 0.001 | 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 | 0.000 | 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".