ANTIOXIDANT ACTIVITY OF PHENOLIC FRACTIONS OF WHITE BEAN (<i>PHASEOLUS VULGARIS</i>)
Bibliographic record
Abstract
ABSTRACT An extract from white bean seeds was prepared using 80% (v/v) acetone. Four fractions (I‐IV) ‐were separated from the crude extract on a Sephadex LH‐20 column using methanol as the mobile phase. The antioxidant activity of fractions was investigated in a β‐carotene‐linoleate model system. For individual fractions, IV spectra were recorded and the content of total phenolics was determined. Fractions were also characterized based on the number of phenolic compounds, and their antioxidant activity determined by TLC analysis. The presence of caffeic, p‐coumaric, ferulic, and sinapic acids in the form of free and estrified compounds was found in fraction IV. One dominant phenolic compound was present in fraction III after acid hydrolysis with a maximum absorption at 278 nm. Results of the β‐carotene‐linoleate model system indicated that antioxidant activity of separated fractions did not correlate exactly with their content of total phenolic compounds and were in the order of IV>III>II>I. Individual fractions contained several phnolic compounds as noted by TLC. Spots on the plates sprayed with a solution of p carotene‐linoleate indicated that these compounds can act as natural antioxidants. Absorption maxima in the W spectra showed that jlavonoids, and not phenolic acids, were the main phenolic compounds present in the separated fractions.
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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".