Comparative Anti-oxidant Activity of Korean and Canadian High Bush Blueberry Fructus
Bibliographic record
Abstract
Blueberries (Ericaceae) are cultivated worldwide, and are used not only as foodstuff but also for relievement of eyestrain. Bluberry species representatively includes highbush blueberry (V. corymbosum L.), lowbush blueberry (V. angustifolium AIT.), rabbiteye blueberry (V. ashei READE), and bilberry blueberry (V. myrtillus L.). All of these species contain large amounts of phenolics and anthocyanins. In this regard, we isolated six compounds from Korea cultivated blueberry and identified as 3-O-caffeoylquinic acid (1), 5-O-caffeoylquinic acid (2), myricetin-3-O-β-D-galactoside (3), quercetin-3-O-ruti- noside (4), ethyl-3-O-caffeoylquinic acid ester (5), ethyl-5-O-caffeoyl quinic acid ester (6) by 1 H-NMR, 13 C-NMR and MS. Anti-oxidative activities of six compounds were verified by anti-oxidant assay such as DPPH, ABTS and Hypoxanthine/xan- thine oxidase system. And then, anti-oxidant activities of Korea blueberry and Canadian were compared with each other. These results support that Korean blueberry has also the possibility to be potential supplementary material as healthy food like Canadian blueberry. Therefore, Korean blueberry can be used as a substitute of Canadian blueberry. Keywords □ high bush blueberry (V. corymbosum L.), 3-O-caffeoylquinic acid, 5-O-caffeoyl quinic acid, myricetin-3-O-β-D- galactoside, quercetin-3-O-rutinoside, ethyl-3-O-caffeoyl quinic acid ester, ethyl-5-O-caffeoylquinic acid ester, anti-oxidant activity
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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".