Authentication of the botanical and geographic origin of Egyptian honey using pollen analysis methods
Bibliographic record
Abstract
In the honey market, botanical and geographical mis-labeling has become common. Therefore, the aim of this study was to use pollen analyses to authenticate the botanical origin and labeling of seven kinds of Egyptian honey and to identify sources of pollen used by honey bees in Egypt. Honeys are labeled, based on sources of pollen, which are usually provided by Egyptian beekeepers are classified as; clover, sidr, citrus, banana, cotton, Brazilian peppertree, and sunflower honey. During 2016–2017, absolute and relative numbers of pollen types were collected synchronously from apiaries and recta of worker bees from which samples of honey were also collected. Pollen from 20 plant taxa, belonging to 14 families was observed. Results of pollen analysis confirmed identities of sources of honey and nectar, as indicated and labeled during collection for all honeys except cotton, sunflower, and Brazilian pepper honeys, where, the predominant types of pollen identified in honey and recta of bees were: Zea mays (69%) in cotton honey, Cucurbitaceae (79%) in sunflower honey, and Eucalyptus sp. (52%) in Brazilian pepper honey. These data suggest that these honey should be re-classification (labeling) as Zea mays, cucurbits, and Eucalyptus honey instead of cotton, sunflower, and Brazilian pepper honey, respectively. Most of the honeys screened contained pollen grains (PGs) of Echium sp. and Trifolium alexandrinum, which indicated their wide geographical distributions in Egypt. Quantitative data of PGs per 10 g of honey indicated unequal geographical distributions of appropriate plants for use by bees in Egypt.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".