Alfalfa Phytoestrogen Content: Impact of Plant Maturity and Herbage Components
Bibliographic record
Abstract
Abstract Legumes contain a range of non‐nutritional phytochemicals that may have health‐promoting effects in humans. In this study, we determined the concentrations of four phytoestrogens (coumestrol, apigenin, luteolin and quercetin) in field‐grown alfalfa (Medicago sativa L.). Differences between plants of different stages of maturity, between plant parts, and different canopy segments were assessed. The concentration of individual phytoestrogen in whole herbage varied between 15 and 225 μg g−1 dry matter (DM) and was strongly affected by stage of maturity. Coumestrol and apigenin concentrations were highest at early vegetative stages, luteolin and quercetin at early vegetative and late flowering stages. All phytoestrogens were found in lowest concentrations at the early flowering stage (average 68 μg g−1 DM); stage at which alfalfa is usually harvested when used as a forage source for animals. At vegetative stages, apigenin was the predominant phytoestrogen in herbage followed by coumestrol, the reverse being observed upon initiation of flowering; luteolin and quercetin were found at all stages in similarly lower concentrations. Concentrations of luteolin, quercetin and apigenin were 225, 410 and 690 % greater, respectively, in flowers than in leaves or stems; coumestrol concentration was similar between plant parts. In flowers and stems the predominant phytoestrogens were apigenin and quercetin, followed by coumestrol and luteolin. Similar concentrations (average 26 μg g−1 DM) of each of the four phytoestrogens were found in leaves. Concentrations through the herbage canopy varied and were greatest at >60 cm from the soil surface for apigenin and coumestrol, but greatest at >60 and 0–20 cm for quercetin and at 0–20 cm for luteolin. The results suggest that if alfalfa is to be used as a source of phytoestrogens and is harvested for the production of herbal supplements or nutraceuticals, management will need to be adapted.
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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 | 0.000 | 0.000 |
| 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".