Determination of Bioactive Compounds and Mineral Contents of Seedless Parts and Seeds of Grapes
Bibliographic record
Abstract
In this study, phenolic compounds, minerals, total flavonoids, total phenolic contents and antioxidant activities of the seedless parts (pulp+skin) and seeds of table and wine grapes were determined.Also, the total oil, tocopherol contents and fatty acid composition of seed oils of table and wine grapes were investigated.The highest total phenolic content of the grape pulp was found in Trakya ilkeren (199.063mg/100 g), while total flavonoid and antioxidant activity of the pulp was determined at a high level in Red Globe (6.810 mg/g, 90.948%).Antioxidant activity, and the total phenolic and flavonoid contents of grape seeds varied between 86.688 and 90.974%, 421.563 and 490.625 mg GAE/100 g, and 90.595 and 145.595 mg/g respectively (p < 0.05).Generally, the main phenolic compounds of all grape pulps and seeds were gallic acid, 3,4-dihydroxybenzoic acid, (+)-catechin and 1,2-dihydroxybenzene.In addition, the oil contents of grape seeds ranged from 5.275 (Çavuş) to 13.881% (Çınarlı karası) (p < 0.05).The major fatty acids of grape seed oils were linoleic, oleic and palmitic acid.The seed oil of the Trakya ilkeren variety was rich in tocopherols in comparison with the other varieties.The major minerals of both the seedless parts and the seeds were determined as K, Ca, P, S, Mg.
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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".