Multivariate Analysis Reveals the Variability in Morphological and Chemical Characteristics of Fenugreek (<i>Trigonella foenum-graecum</i> L.) Populations
Bibliographic record
Abstract
On January 2, 2024, Ziba Bakhtiar and his research team published an article titled "Variability in proximate composition, phytochemical traits, and antioxidant properties of Iranian agro-ecotypic populations of fenugreek ( Trigonella foenum-graecum L.)" in the journal Scientific Reports. The article investigates the variability in proximate composition, phytochemical characteristics, and antioxidant properties of different agro-ecotypic populations of fenugreek ( Trigonella foenum-graecum L.) in Iran. By analyzing leaf and seed samples from 31 Iranian fenugreek agro-ecotypic populations, the study found that the seeds contain higher levels of ash, fat, crude fiber, protein, and carbohydrates, and their energy value is significantly higher than that of the leaves. The antioxidant activity and capacity of the leaves were also studied in detail, revealing a positive correlation with total phenolic and total flavonoid contents. The research demonstrates significant differences and correlations among these traits, which are important for further studies on food production systems.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".