Genetic variability of principal isoflavones in red clover
Bibliographic record
Abstract
Isoflavones, known for their health benefits, are abundant in red clover (Trifolium pratense L.). Total isoflavone concentrations can be 30 times that of soybean, indicating that red clover is a good source of nutraceutical and functional food ingredients. In this study, tissue samples of 13 red clover cultivars were taken at two growth stages (late-bud stage and late-flowering stage) to determine the concentration of individual isoflavones using HPLC. Individual isoflavone concentrations and total isoflavone concentration differed significantly according to red clover cultivar. We found significant genetic variability for total isoflavone concentration and individual isoflavone concentrations; these differences were not related to ploidy level (diploid vs. tetraploid). Broad-sense heritability (H = genetic variance/total variance) ranged from 0 to 83% and was influenced by isoflavone type and sampling date. The results of this study suggest that there is significant genetic variability for isoflavone concentrations among currently available red clover cultivars. Key words: Trifolium pratense L., biochanin A, formononetin, growing stages, broad-sense heritability
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".