Prevalence of Adult Honey Bee (Apis mellifera L.) Pests and Pathogens in the Five Beekeeping Regions of Mexico
Bibliographic record
Abstract
Mexico is a major honey producer, but not much information exists about the health status of honey bees (Apis mellifera L.) in the country. This study was conducted to determine the sanitary status of adult honey bees in Mexico’s five beekeeping regions. Samples from 369 apiaries were diagnosed to identify pathogens such as Varroa destructor, which was quantified, Acarapis woodi, Nosema spp., and five viruses. Colonies were also inspected for the presence of the small hive beetle (SHB), Aethina tumida. Varroa destructor was found in 83.5% of the apiaries, with the Pacific Coast region having the highest prevalence (>95%) and rates (4.5% ± 0.6). Acarapis woodi was detected in only one apiary from the Pacific Coast, whereas Nosema spp. were prevalent in 48.5% of the apiaries, with the highest and lowest frequencies in the Yucatan Peninsula and North regions (64.6% and 10.2%, respectively). For viruses, deformed wing virus (DWV) was detected in 26.1% of the apiaries, with the highest frequency in the Pacific Coast region (44.7%). Israeli acute paralysis virus (IAPV) was diagnosed in 3.2% of the samples and sacbrood bee virus (SBV) in 23.3% of them, with the highest frequency in the High Plateau region (36.4%). Chronic bee paralysis and Kashmir bee viruses were not detected. SHB prevalence was 25.2% nationwide, with the highest frequency in the Yucatan Peninsula (39.2%). This study shows that the most common parasites of adult honey bees in Mexico are V. destructor and Nosema spp., and that the most prevalent virus is DWV, whereas SHB is highly prevalent in the Yucatan Peninsula. This information could be useful to design disease control strategies for honey bee colonies in different regions of Mexico.
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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 | 0.001 | 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".