Genetic structure and ecological niche space of lentil's closest wild relative, <i>Lens orientalis</i> (Boiss.) Schmalh.
Bibliographic record
Abstract
Crops arose from wild ancestors and to understand their domestication it is essential to compare the cultivated species with their crop wild relatives. These represent an important source of further crop improvement, in particular in relation to climate change. Although there are about 58,000 Lens accessions held in genebanks, only 1% are wild. We examined the geographic distribution and genetic diversity of the lentil's immediate progenitor L. orientalis. We used Genotyping by Sequencing (GBS) to identify and characterize differentiation among accessions held at germplasm collections. We then determined whether genetically distinct clusters of accessions had been collected from climatically distinct locations. Of the 195 genotyped accessions, 124 were genuine L. orientalis with four identified genetic groups. Although an environmental distance matrix was significantly correlated with geographic distance in a Mantel test, the four identified genetic clusters were not found to occupy significantly different environmental space. Maxent modelling gave a distinct predicted distribution pattern centred in the Fertile Crescent, with intermediate probabilities of occurrence in parts of Turkey, Greece, Cyprus, Morocco, and the south of the Iberian Peninsula with NW Africa. Future projections did not show any dramatic alterations in the distribution according to the climate change scenarios tested. We have found considerable diversity in L. orientalis, some of which track climatic variability. The results of the study showed the genetic diversity of wild lentil and indicate the importance of ongoing collections and in situ conservation for our future capacity to harness the genetic variation of the lentil progenitor.
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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 | 0.001 | 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".