Carvone and citral, two promising compounds for controlling the honey bee ectoparasitic mite, <i>Varroa destructor</i>
Bibliographic record
Abstract
Abstract Varroa destructor (Acari: Varroidae) is an external parasitic mite that has compromised honey bee (Hymenoptera: Apidae) health worldwide. Varroa mite resistance to commercial formulations of synthetic acaricides has led to an increasing need for new compounds to control mite infestations in honey bee colonies. Thus, essential oils and plant extracts have been used by organic producers concerned about the environment because they are low‐risk pesticides. This study tested the toxicity of four natural compounds: carvone, citral, cineole and limonene to mites and bees under laboratory conditions. Tau‐fluvalinate was used as positive control. Seven concentrations with logarithmic interval were used to test each compound. The safety margin of the compounds for the bees was calculated from selectivity ratios. Carvone was significantly more toxic to varroa mites (LC50 = 272.74 μg/ml) than the other three compounds but did not differ with tau‐fluvalinate (LC50 = 272.30 μg/ml). Citral was the second most toxic compound to mites (LC50 = 318.54 μg/ml), followed by cineole (LC50 = 3897.65 μg/ml) and limonene (LC50 = 3003.94 μg/ml). Citral and carvone showed low toxicity to worker bees at both 24 and 48 hpt. The LD50 values for citral, carvone and tau‐fluvalinate were 78,459, 106,620 and 143.02 μg/ml at 24 hpt, respectively, which were significantly different from each other. The relative selectivity ratios calculated for carvone, citral and tau‐fluvalinate were 390.9, 246.3 and 0.53, respectively. This study provides preliminary laboratory evidence for the effectiveness and safety of two plant compounds, carvone and citral, that could potentially be used for the control of V. destructor infestations in honey bee colonies.
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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".