Antioxidant activity of extracts of defatted seeds of niger (<i>Guizotia abyssinica</i>)
Bibliographic record
Abstract
Abstract Niger (Guizotia abyssinica) seed was ground and then defatted with hexane. The meal remaining after oil extraction was tested as a source of antioxidants. Three solvent systems, A [80∶20 (vol/vol) ethanol/water], B [80∶20 (vol/vol) acetone/water], and C (water) were evaluated as extraction media. Crude extracts were examined for their antioxidant activity in a β‐carotene‐linoleate and a meat model system. Extract A exhibited superior antioxidant activity, compared to extracts B and C, and its composition was studied further by using column chromatography and HPLC. Four fractions (I–IV) were obtained, of which fractions III and IV showed activity in the β‐carotene‐linoleate model system. Fraction IV was also highly effective in scavenging the 2,2‐diphenyl‐1‐picrylhydrazyl radical but was less active when used in a bulk oil model system. Preparative TLC showed fraction IV as consisting of two components. UV spectroscopy suggested that the major active component pressent was a chlorogenic acid‐related compound. Furthermore, HPLC analysis established that chlorogenic acid was dominant in the free phenolics fraction (2.6 mg/g). Upon hydrolysis, however, a substantial amount of caffeic acid (42.8 mg/g) was released, presumably from esterified and glycosylated chlorogenic acid. Thus, niger extracts derive their antioxidant activity, at least in part, from the chlorogenic acid‐related compounds.
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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 | 0.000 |
| 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".