Populations of Medicago minima (L.) Bart. in Iran: High Morphological Variability Irrelevant to ITS Sequences and Geographical Proximity
Bibliographic record
Abstract
Medicago minima (L.) Bartal. has received little agricultural development to date, while having potentially useful traits compared to other “medics”, e.g., annual species of section Spirocarpos. However, the range of variation in M. minima requires further studies. This research assessed the diversity of the pod morphological traits of 13 populations in the southwest, west, northwest, and north of Iran. In addition, variation in nuclear ribosomal Internal Transcribed Spacer (nrITS, ITS 1+5.8s+ITS 2) was evaluated. No geographical patterns of variation in the pod traits were found. The molecular phylogenetic assessments of 7 populations indicated low variability, thus being grouped into a well-supported monophyletic clade (99% Bootstrap support/1.00 Posterior Probability (PP)). Nevertheless, the pod morphological traits exhibited significant variations, most notably in Glandular Hairs (GH), with a coefficient variation of 58%. For breeding and possibly conservation purposes, the following populations demonstrated potentially useful characteristics: (1) Baghcheh population with the highest number of seeds per pod (4.6) and angle of spine insertion (2.87◦); (2) Khoramabad population with a higher number of spines on the middle coil (65.27); and (3) Sarvabad population with the greatest fruit length (3.71 mm), fruit diameter (4.17 mm), Seed Length Trait (SLT) (2.37 mm), and Seed Width Trait (SWT) (1.35 mm). In qualitative traits, Khoramabad, Baghcheh, Marivan, and Paveh populations had higher scores, particularly for glandular pubescence and Simple Hairs (SH) on their pods. Results of the correlation analysis were often null or negative; however, altitude indicated a positive relationship with glandular pubescence and SH. No obvious correlations were found between pod morphology and ITS variation and geographical proximity.
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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 | 0.000 | 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) | 0.000 | 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 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".