Identification of flavonoids of Wheatgrass (Triticum aestivum L.) at various stages of growth and evaluation of their Antioxidant Activity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Wheatgrass are 6-10 days young plantlet of wheat (Triticum aestivum L.). Ethopharmacologically, the wheatgrass is recognized for its anti-aging and other health promoting properties. This study was aimed at identifying the phytochemical composition of wheatgrass (var. Chinese Spring) and evaluating its antioxidant potentials at different stages of growth (5th, 7th, 9th, 11th, 13th, 15th day). Phytochemical components were extracted with methanol and total phenolic contents (TPC) and total flavonoid contents (TFC) of the extracts were evaluated. DPPH (1,1ꞌ- diphenyl-2-picrylhydrazyl), bleaching of β-carotene and metal chelating activity was used to assess the antioxidant activity of the extract and further correlated with TPC and TFC. Based on comparison of IC50 data, DPPH radical scavenging activity of the extract was found to be best at 7th day of the growth and equivalent to standard gallic acid. The extract exhibited excellent metal chelating activity and β-carotene bleaching property on 9th day of growth and the IC50 corresponded with standard ascorbic acid and butylated hydroxytoluene (BHT), respectively. Preliminary screening with thin layer chromatography identified the probable flavonoids which could be quercetin, rutin or myricetin and their glcycosides. Significant correlation between antioxidant activity with TPC and TFC ascertained that phenolics and flavonoids were the major contributors of antioxidant activity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.001 |
| 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 it