Repellency of Essential Oils to <I>Frankliniella occidentalis</I> (Thysanoptera: Thripidae) as Affected by Type of Oil and Polymer Release
Bibliographic record
Abstract
Eight essential oils [0.125-1.0% (vol:vol) in acetone] were separately deposited on leaf disks to evaluate their potential to repel western flower thrips, Frankliniella occidentalis (Pergande) (Thysanoptera: Thripidae), adult females. Two of the best-performing essential oils were incorporated into polymer matrices of methyl cellulose or alginate [0.5 or 1% (wt:vol)] to verify the potential of the polymer to extend repellency of oils over time (24-120 h). Results showed that at a concentration of 0.5%, Thymus vulgaris L. (common thyme) and Satureja montana L. (winter savory) were the most repellent essential oils. For these two treatments, no western flower thrips were counted on treated leaf disks 60 min after the start of the test. T. serpyllum and O. compactum also showed repellency values > or = 90% at this concentration. With both the alginate and methyl cellulose polymers, the incorporation of polymers into treatment solutions containing 0.5% concentrations of S. montana and T. serpyllum resulted in higher repellency compared with treatment solutions lacking these polymers for a minimum of 3 d. For the alginate polymer, differences associated with polymer concentrations were most dramatic. High repellency was maintained for 4 d when a 0.5% concentration of the alginate was used in combination with a 0.5% concentration of S. montana. The use of repellent oils with polymers that extend their repellency may prove useful for both pre- and postharvest applications in flower crops.
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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".