MORPHOLOGICAL CHARACTERIZATION OF SOME COLLECTED NATIVE PURSLANE (PORTULACA OLERACEA L.) GENOTYPES
Bibliographic record
Abstract
Purslane (Portulaca oleracea L.), an annual herb commonly found across various regions of the world, is often considered either a weed or a valuable vegetable crop. This study aimed to evaluate the morphological variation among ten purslane genotypes collected from different regions of Iran. The trial was conducted in a greenhouse environment via a completely randomized scheme with four replicates, during which eleven traits were assessed. The genotype × trait interaction biplot model accounted for 90% of the observed variability, revealing four distinct genotypic groups. Notably, the Mashhad genotype exhibited the highest values for the flower number per branch, dry shoot weight, fresh shoot weight, branch number of the main stem, and the number of seeds per capsule. A positive correlation was observed among the flower number per plant, capsule number per branch, and flower number per branch, while these traits were negatively associated with main stem length, leaf length, and leaf width. The Mashhad genotype, along with those from Bandar-Abbas and Parsabad, demonstrated superior performance and distinctiveness, with the number of seeds per capsule and the number of branches on the main stem showing the highest discriminative potential. When evaluating dry shoot weight, the Mashhad genotype, followed by those from Parsabad and Bandar-Abbas, emerged as the most desirable, whereas the genotypes from Ardabil and Sirjan were the least desirable in this characteristic. The significant diversity identified among these purslane genotypes could be instrumental in enhancing the breeding of this crop for specific target traits.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".