Nutrient Distribution and Phenolic Antioxidants in Air-Classified Fractions of Beach Pea (<i>Lathyrus maritimus</i> L.)
Bibliographic record
Abstract
Beach pea (Lathyrus maritimus L.) cotyledons and hulls were air-classified into different fractions. The crude protein content (%N x 6.25) of samples ranged from 32.8 to 35.3% in cotyledons and 14.7 to 16.8% in hulls. Crude fiber content was higher in hulls fraction 1 (37.13%) and fraction 2 (36.85%) than in cotyledons (2.83, 2.99, and 3.08% in fractions 1, 2, and 3, respectively). Condensed tannins of cotyledons ranged from 5.76 to 6.90% and of hulls ranged from 52.49 to 57.24%, expressed as catechin equivalents. Minerals, namely P, K, and Zn, were higher in cotyledons, but Ca and Mn were more prevalent in hulls. Nonprotein nitrogen was concentrated in hulls, whereas phytic acid was more abundant in the cotyledons. The UV absorption pattern showed that flavonoids were present in fractions (I-III) from hulls separated on Sephadex LH-20. Fraction III from hulls had the highest content of total phenolics and condensed tannins, but no condensed tannins were detected in fractions I and II from hulls. The antioxidant activity of fractions separated on Sephadex LH-20 from hulls and crude extracts in a beta-carotene-linoleate model system was in the order of fraction III > crude extract > fraction II > fraction I. Spots on silica gel TLC plates, sprayed with a solution of beta-carotene and linoleic acid, indicated that many of the individual compounds were antioxidative in nature. Further, separation of fraction III from hulls on a semipreparative HPLC showed the presence of (+) catechin and (-) epicatechin as the main low-molecular-weight phenolic compounds present.
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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".