Antioxidant Activity in Relationship to Phenolic Content of Diverse Food Barley Genotypes
Bibliographic record
Abstract
The antioxidant activity and phenolic composition of 21 mostly hull-less food barley of diverse origin were determined. The 1,1-diphenyl-2-picrylhydrazyl (DPPH) and superoxide radicals scavenging capacity assays were used to measure antioxidant activity. A photochemi- luminescence technique was used to measure water (ACW) and lipid (ACL) soluble substances. The DPPH radical scavenging capacities of the samples were significantly different (p<0.05), ranging between 13 and 27%. Significant differences existed in the ACW and ACL values. The total phenolic contents were determined using the Folin-Ciocalteu method; values ranged from 2,672 to 3,947 µg ferulic acid equivalents /g of barley. Tannin contents determined using the vanillin HCl method were significantly different and varied between 36 and 58 µg catechin equivalents /g of barley. Two hulless genotypes Peru 45, and Ex87xCI 19973 displayed consistently high values of the antioxidant parameters and can be used as antioxidant rich food ingredients. Peru 16, a genotype which had an intact hull that was removed prior to analysis also displayed good antioxidant properties. Due to the difficulty involved in processing, Peru 16 will have to be developed into a hull-less genotype through breeding before adoption for food use. Lack of correlation between tannin and total phenolic contents warrants the need for more detailed chemical analyses and evaluation of functional properties of phenolic compounds of diverse barley materials.
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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) | 0.001 | 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".