Free Radical Scavenging Properties and Phenolic Content of Chinese Black-Grained Wheat
Bibliographic record
Abstract
Free radical scavenging properties and phenolic content of extracts from a novel Chinese black-grained wheat were evaluated for comparison with selected wheat controls. Extracts of bran and whole meal were compared for their scavenging activities against the 2,2-diphenyl-1-picryhydrazyl (DPPH) free radical. The total phenolic content and phenolic acid levels were determined using colorimetric and high-performance liquid chromatography (HPLC) methods, respectively. There were significant differences in radical scavenging activities and phenolic contents among bran or whole meal samples of Chinese black-grained wheat and selected wheat controls. Chinese black-grained wheat had the strongest scavenging activity and the highest total phenolic content among the wheat samples. The scavenging activity and total phenolic content of wheat bran was generally twice as high as that of whole meal. A positive correlation was found between DPPH radical scavenging activity and total phenolic content of bran (R = 0.86) and whole meal (R = 0.96). In addition, HPLC analysis detected the presence of gallic, p-hydroxybenzoic, caffeic, syringic, p-coumaric, vanillic, gentisic, o-coumaric acid, and ferulic acids in wheat bran. Ferulic acid content was highest among the phenolic acids. Chinese black-grained wheat may be considered as a potential source of natural antioxidants given its high free radical scavenging ability and phenolic content. Additional research is needed to further investigate other phenolic compounds and evaluate their contribution to the antioxidant activity in order to understand the nutraceutical value of the novel black-grained wheat genotype.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".