Composition of Buckwheat Honey
Bibliographic record
Abstract
Buckwheat has been grown in Virginia since late 1700s; however, today the crop is almost non-existent in Virginia. Since buckwheat flowers profusely in a few weeks after planting, it has potential to support honeybees but there is a lack of information about quality of buckwheat honey produced in Virginia. Our objective was to characterize composition of honey produced by honeybees foraging on buckwheat (Buckwheat honey), compared to that produced by honeybees foraging on wild plants (Wild plant honey). Buckwheat honey differed in composition, antioxidant concentrations, and microbial activities from wild plant honey. Concentrations of fructose, glucose, and melezitos in buckwheat honey were quantitatively lower than that in wild plant honey whereas concentrations of sucrose and maltose exhibited an opposite trend—concentration of maltose being statistical significant. Fructose was the dominant sugar (42 and 52 percent in buckwheat honey and wild plant honey, respectively). Buckwheat honey had significant higher concentrations of K and Cu in comparison to wild plant honey (0.17 and 0.04 percent, and 5.0 and 3.33 ppm, respectively). Concentrations of Trolox and TPC were significantly higher in buckwheat honey than wild plant honey (1.01 and 0.32, and 0.39 and 0.17, respectively). Both types of honeys exhibited anti-microbial activity against gram-positive and gram-negative bacteria. The buckwheat honey was darker in color than the honey from wild plants. We concluded that production of buckwheat as a grain or cover crop can also support honeybees and buckwheat honey might be superior to wild plant honey.
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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".