Content of Insoluble Bound Phenolics in Millets and Their Contribution to Antioxidant Capacity
Bibliographic record
Abstract
Soluble and insoluble-bound phenolic extracts of several varieties of millet (kodo, finger, foxtail, proso, pearl, and little millets) whole grains were evaluated for their phenolic contents and antioxidative efficacy using trolox equivalent antioxidant capacity (TEAC), reducing power (RP), and beta-carotene-linoleate model system as well as ferrous chelating activity. In addition, ferulic and p-coumaric acids were present in soluble and bound phenolic fractions of millets, and their contents were determined using high-performance liquid chromatography (HPLC) and HPLC-mass spectrometry (MS). Kodo millet had the highest total phenolic content, whereas proso millet possessed the least. All millet varieties showed high antioxidant activities, although the order of their efficacy was assay dependent. HPLC analysis of millet phenolic extracts demonstrated that the bound fractions contained more ferulic and p-coumaric acids compared to their soluble counterparts. The results of this study showed that soluble as well as bound fractions of millet grains are rich sources of phenolic compounds with antioxidant, metal chelating, and reducing power. The potential of whole millets as natural sources of antioxidants depends on the variety used. The importance of the insoluble bound fraction of millet as a source of ferulic acid and p-coumaric acid was established, and their contribution to the total phenolic content must be taken into account in the assessment of the antioxidant activity of millets.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".