Effect of Domestic Cooking on Carotenoids, Tocopherols, Fatty Acids, Phenolics, and Antioxidant Activities of Lentils (<i>Lens culinaris</i>)
Bibliographic record
Abstract
The phytochemicals and antioxidant activity in lipophilic and hydrophilic (extractable and bound) fractions of lentils before and after domestic cooking were investigated. The hydrophilic fractions in lentils contributed much more to the antioxidant activity than the lipophilic fraction. The phenolic content of lentils was mainly composed of extractable compounds. Significant changes (P < 0.05) in carotenoid, tocopherol, total phenolic, and condensed tannin contents of both extractable and bound phenolics fractions, as well as in antioxidant activities, were found in lentils before and after cooking. More specifically, cooking was found to favor the release of carotenoids and tocopherols and flavonols (kaempferol glycosides), but led to losses of flavanols (monomeric and condensed tannin). Whereas reduced flavanols and other phenolic compounds may have negatively affected the antioxidant activity, other components, especially the lipophilic antioxidants, were increased. The present study suggests that incorporation of cooked lentils into the diet will not cause significant loss to the phytochemical antioxidants and thus will retain the potential health benefits.
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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 | 0.000 | 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) | 0.001 | 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".