Antioxidant and antileukemic properties of selected fenugreek (Trigonella foenum-graecum L.) genotypes grown in western Canada
Bibliographic record
Abstract
Acharya, S. N., Acharya, K., Paul, S. and Basu S. K. 2011. Antioxidant and antileukemic properties of selected fenugreek (Trigonella foenum-graecum L.) genotypes grown in western Canada. Can. J. Plant Sci. 91: 99-105. Fenugreek (Trigonella foenum-graecum L.) is an annual forage legume known to have a number of important medicinal properties such as being anti-diabetic and hyperchloesterolaemic among others. In this study we have investigated the anti-oxidant and antileukemic properties of five fenugreek genotypes (L3068, L3375, Tristar, PI143504 and Amber) grown in western Canada for their potential use as nutraceuticals. Our preliminary experiments conducted in two different laboratories showed that the seeds grown in western Canada have anti-oxidant and antileukemic properties and the genotypes differ in the two traits studied. All the genotypes were found to be good scavengers for hydroxyl and free radicals. Among all the varieties, L3068 showed a higher EC50 value i.e., lower inhibitory activity for lipid peroxidation than the standard catechin. Although all five extracts showed significant antioxidant activity, the crude extract of Tristar was the most effective. Out of the five cultivars of fenugreek, Amber and L3375 showed a robust antileukemic activity followed by Tristar. Hence we conclude that Tristar has the best potential among all the genotypes tested to be used as a future nutraceutical crop when grown in western Canada.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".