Turkish Tombul Hazelnut (<i>Corylus avellana</i> L.). 2. Lipid Characteristics and Oxidative Stability
Bibliographic record
Abstract
The quality of crude hazelnut oil extracted from Tombul (Round) hazelnut, grown in the Giresun province of Turkey, was determined by measuring lipid classes, fatty acids, and fat soluble bioactives (tocopherols and phytosterols). Oxygen uptake, peroxide value, thiobarbituric acid reactive substances, and alpha-tocopherol levels of stripped and crude hazelnut oils in bulk and oil-in-water (o/w) emulsion systems were also evaluated as indices of lipid oxidation over a 21 day storage period at 60 degrees C in the dark. The total lipid content of Tombul hazelnut was 61.2%, of which 98.8% were nonpolar and 1.2% polar constituents. Triacylglycerols were the major nonpolar lipid class and contributed nearly 100% to the total amount. Phosphatidylcholine, phosphatidylethanolamine, and phosphatidylinositol were the most abundant polar lipids, respectively. Sixteen fatty acids were identified, among which oleic acid contributed 82.7% to the total, followed by linoleic, palmitic, and stearic acids. Unsaturated fatty acids accounted for 92.2% of the total fatty acids present. Among oil soluble bioactives, alpha-tocopherol (38.2 mg/100 g) and beta-sitosterol (105.5 mg/100 g) were predominant in hazelnut oil and comprised 88 and 93% of the total tocopherols and phytosterols present, respectively. The results also showed that both stripped and crude hazelnut oils were more stable in terms of lipid oxidation in the bulk oil as compared to those in an o/w emulsion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 0.001 |
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".