The recognition of high molecular weight melanoidins as the main components responsible for radical-scavenging capacity of unheated and heat-treated Canadian honeys
Bibliographic record
Abstract
As the Maillard reaction is known to occur in heat-treated foods, unheated and heated honey samples were subjected to the activity-guided fractionation and size-exclusion chromatography to compare the degree of browning, radical scavenging activity (ORAC) and molecular size of the fractions obtained. Heat-treatment increased browning in the fractions of light- and medium-coloured honeys (p < 0.002), accelerated the formation of high molecular weight melanoidins (85–232 kDa) and significantly increased ORAC values (p < 0.0001). In contrast, melanoidin content and ORAC decreased in the fractions of heat-treated dark buckwheat honey (p < 0.001). Unheated dark honey contained a significantly higher amount of melanoidins than other honeys (p < 0.007). Together, results showed that at low initial concentration of melanoidins, heat-treatment accelerated formation of new melanoidins and increased ORAC, while at high concentration it caused decrease and a reduction of radical scavenging activity. This study emphasises the importance of non-enzymatic browning in the prediction of the antioxidant pool in thermally processed honeys.
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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) | 0.001 | 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".