Field Evaluation of Neem and Canola Oil for the Selective Control of the Honey Bee (Hymenoptera: Apidae) Mite Parasites <I>Varroa jacobsoni</I> (Acari: Varroidae) and <I>Acarapis woodi</I> (Acari: Tarsonemidae)
Bibliographic record
Abstract
Neem oil, neem extract (neem-aza), and canola oil were evaluated for the management of the honey bee mite parasites Varroa jacobsoni (Oudemans) and Acarapis woodi (Rennie) in field experiments. Spraying neem oil on bees was more effective at controlling V. jacobsoni than feeding oil in a sucrose-based matrix (patty), feeding neem-aza in syrup, or spraying canola oil. Neem oil sprays also protected susceptible bees from A. woodi infestation. Only neem oil provided V. jacobsoni control comparable to the known varroacide formic acid, but it was not as effective as the synthetic product Apistan (tau-fluvalinate). Neem oil was effective only when sprayed six times at 4-d intervals and not when applied three times at 8-d intervals. Neem oil spray treatments had no effect on adult honey bee populations, but treatments reduced the amount of sealed brood in colonies by 50% and caused queen loss at higher doses. Taken together, the results suggest that neem and canola oil show some promise for managing honey bee parasitic mites, but the negative effects of treatments to colonies and the lower efficacy against V. jacobsoni compared with synthetic acaricides may limit their usefulness to beekeepers.
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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 | 0.001 | 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".