Efficacy and Safety of an Oxalic Acid and Glycerin Formulation for Varroa destructor Control in Honey Bee Colonies During Summer in a Northern Climate
Bibliographic record
Abstract
Effective control of the parasitic mite Varroa destructor in honey bee (Apis mellifera) colonies relies on integrated pest management (IPM) strategies to prevent mite populations from reaching economic injury levels. Formulations of oxalic acid combined with glycerin may provide a viable summer treatment option in continental Northern climates. This study evaluated the efficacy of oxalic acid and glycerin strips compared to oxalic acid dribble and 65% formic acid when applied in mid-August. Mite levels and colony health parameters were assessed, and honey samples from oxalic acid-treated colonies were analyzed for residue levels. Results showed that the oxalic acid and glycerin strips had a moderate acaricidal efficacy (55.8 ± 3.2%), which was significantly higher than those of 65% formic acid (42.6 ± 3.2%) and oxalic acid dribble (39.5 ± 4.3%), which did not differ between them, suggesting potential for summer mite control. No significant adverse effects on cluster size, worker mortality, queen status, or colony survival were observed. Oxalic acid and glycerin increased the proportion of spotty brood patterns at early timepoints after treatment, but recovery was noted after 45 days of starting the treatment. Similar effects on brood were observed with 65% formic acid 14 days after starting the treatment, with recovery by 28 and 45 days after starting the treatment. No significant differences in oxalic acid residues in honey from the control and treatment colonies were found. Oxalic acid and glycerin strips might help control varroa mite populations, delaying their exponential growth and helping reduce economic losses for beekeepers, but this treatment should be considered as part of an IPM strategy and not a stand-alone method for V. destructor control.
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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) | 0.000 | 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".