Comparative Analysis of Bioactive Phenolic Compounds and Fatty Acids in Seeds and Seedlings of Canadian Alfalfa, Sainfoin, and Fenugreek
Bibliographic record
Abstract
The interest in under-utilized crops as a functional food for animals and humans has been increasing recently with advancing research and the need for crop improvement. Canadian forage crops including alfalfa (Medicago sativa L.) and fenugreek (Trigonella foenum-graecum L.) are marketed in various forms due to their traditionally known health benefits. Sainfoin (Onobrychis viciifolia Scop.) is another forage crop with potential health benefits containing beneficial nutraceuticals. In this study, we assessed selected bioactive phenolic compounds and fatty acids in seeds and seedlings of Canadian-grown alfalfa, sainfoin, and fenugreek. Various phenolic compounds were detected in all three forage crop seeds and seedlings. In general, Sainfoin seeds were high in phenolic compounds relative to that of alfalfa and fenugreek. Chlorogenic acid, epigallo catechin, and gallic acid were at high concentrations at 56.6, 86.8, and 64.7 µg.g−1, respectively, compared to other phenolic compounds in sainfoin seeds. The fatty acids content (%) was significantly affected by the seedling stage and crop type. Some of the bioactive compounds present in seeds were not detected in seedling stages. The comparative bioactive phenolic compounds and fatty acid assessments of these forage legumes could potentially be used as biomarkers for the selection and development of favorable cultivars for animal and human nutrition. In addition, these crops could be used for isolating these bioactive compounds, and thus increasing their agri-food value.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".