Antioxidant and Antiradical Activities in Extracts of Hazelnut Kernel (<i>Corylus avellana</i>L.) and Hazelnut Green Leafy Cover
Bibliographic record
Abstract
Phenolic compounds in the aqueous systems were extracted, from hazelnut kernel (HK) and hazelnut green leafy cover (HGLC), with 80% (v/v) ethanol (HKe and HGLCe) or 80% (v/v) acetone (HKa and HGLCa). The extracts were examined for their phenolic and condensed tannin contents and phenolic acid profiles (free and esterified fractions) as well as antioxidant and antiradical activities by total antioxidant activity (TAA), antioxidant activity in a beta-carotene-linoleate model system, scavenging of DPPH (2,2-diphenyl-1-picrylhydrazyl) radical, and reducing power. Significant differences (p < 0.05) in the contents of total phenolics, condensed tannins, and TAA existed among the extracts that were examined. HGLCa extract had the highest content of total phenolics (201 mg of catechin equivalents/g of extract), condensed tannins (542 mg of catechin equivalents/g of extract), and TAA (1.29 mmol of Trolox equivalents/g of extract) followed by HGLCe, HKa, and HKe extracts, respectively. Five phenolic acids (gallic acid, caffeic acid, p-coumaric acid, ferulic acid, and sinapic acid) were tentatively identified and quantified, among which gallic acid was the most abundant in both free and esterified forms. The order of antioxidant activity in a beta-carotene-linoleate model system, the scavenging effect on DPPH radical, and the reducing power in all extracts were in the following order: HGLCa > HGLCe > HKa > HKe. These results suggest that both 80% ethanol and acetone are capable of extracting phenolics, but 80% acetone was a more effective solvent for the extraction process. HGLC exhibited stronger antioxidant and antiradical activities than HK itself in both extracts and could potentially be considered as an inexpensive source of natural antioxidants.
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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) | 0.001 | 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) | 0.000 | 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".