Phenolic Compositions and Antioxidant Activities Differ Significantly among Sorghum Grains with Different Applications
Bibliographic record
Abstract
Sorghum grains with different applications had different phenolic profiles, which were corresponded to various antioxidant capacities. In this study, total phenolic, proanthocyanidins and flavonoids contents, as well as contents of individual phenolic compounds from sorghum grains with various applications were determined, and their antioxidant capacities were evaluated. Total phenolic contents (TPC) and total proanthocyanidins contents (TPAC) showed strong correlation with antioxidant activities (r > 0.95, p < 0.01). Hongyingzi (S-1), one of the brewing sorghums, showed the highest level of TPC and TPAC, while white grain sorghum (S-8) had the lowest. Except for black grain sorghum (S-7), that contained the highest contents of ferulic acid, brewing sorghum grains contained the higher contents of the most individual phenolic compounds, especially the variety S-1. The correlation among individual phenolic compounds and antioxidant activities indicated that the free forms of protocatechuic acid (r = 0.982 of FRAPassay, p < 0.01) and taxifolin (r = 0.826 of FRAP assay, p < 0.01) may be the main functional compounds. These results indicate that brewing sorghum grains can also be utilized as effective materials for functional foods.
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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 | 0.001 |
| 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) | 0.001 | 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".