Physico-Chemical Profile of Four Types of Honey from the South of the Republic of Moldova
Bibliographic record
Abstract
There are many studies that compare the quality and biological characteristics of honey with distinct geographical and botanical origins. However, the physico-chemical and biological properties of different types of honey in the same production regions are rarely mentioned. The honey used in this study: sunflower honey, rapeseed honey, manna honey and polyflora honey, came from GT “Malai C” in Taraclia village, Causeni district in the southern part of the Republic of Moldova and belonged to the flowering season of year 2020. Following the polynecological analysis, it was found that two types of honey are monofloral with a dominant pollen content of Helianthus spp. (49.15% - 93.12%) in sunflower honey and Brassica spp. (52.17% - 70.11%) in rapeseed honey. Mana honey and polyflora contain several types of pollen. Thus, four types were identified in manna honey, including: Acer platanoides (29.11% - 30.11%), Quercus robur (28.67% - 29.99%), Rubus idaeus (21.55% - 28.78%), Taraxacum officinale (22.21% - 28.76%). Polyflora honey contains: Helianthus annuus (24.91% - 31.11%), Brassica napus (23.45% - 29.18%), Tilia (28.95% - 31.92%). Based on a Pfund scale, it was found that the color of the honey varied from a lighter shade for rapeseed honey (water amber 7.66 ± 3.002 mm) to a darker color for sunflower honey and polyflora (extra light amber 34.366 ± 21.01 mm and 36.04 ± 1.115 mm respectively). Spectrophotometric determination of phenolic compounds in honey samples showed that their content ranged from 38.18 mg GAE/kg honey for rapeseed honey to 831.09 mg GAE/kg honey for manna honey. At the same time, the flavonoid content ranged from 28.41 mg QUE/kg honey for rapeseed honey to 151.72 mg QUE/kg honey for manna honey. Mana honey showed a better antioxidant activity than the other honey samples in the study (72.03%). The reported results suggest that manna honey has the best potential and its consumption in the human diet as food with valuable biological properties can be encouraged, despite the fact that in the Republic of Moldova it is in a small amount.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 teacher head, 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".