Variation in Diosgenin Levels among 10 Accessions of Fenugreek Seeds Produced in Western Canada
Bibliographic record
Abstract
A collection of 10 accessions of fenugreek (Trigonella foenum-graecum L.), an annual legume, was grown during two summers at three plot locations in western Canada to assess whether genetic (accession) and environmental factors (site and year of production) influenced levels of diosgenin, a steroidal sapogenin. The 60 harvested seed samples, each analyzed by single determinations on three subsamples of defatted and dried seed material, were hydrolyzed by a microscale procedure in water containing 2-propanol (70%) and sulfuric acid (1 M). The extracts were analyzed by capillary gas chromatography with 6-methyldiosgenin as internal standard. Diosgenin levels from mature seeds ranged from 0.28 to 0.92% (28-92 microg/10 mg). Analysis of variance on combined diosgenin levels from the three sites and two years revealed that accession, accession x year, and site x year effects were significant for diosgenin content, whereas site, year, and site x accession effects were not. Four accessions, CN 19062, CN 19067, CN 19070, and CN 19071, were identified with high levels of diosgenin on the basis of the 2-year data set. In these accessions, mean levels of diosgenin plus yamogenin from seven site years were estimated at 0.70, 0.98, 0.84, and 0.87%, respectively.
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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 | 0.001 | 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".