Chestnut cultivar diversification process in the Iberian Peninsula, Canary Islands, and Azores
Bibliographic record
Abstract
This is a large-scale molecular study based on simple sequence repeat (SSR) loci of the diversification process in chestnut cultivars from Portugal and Spain, from the northern Iberian Peninsula to the Canary Islands and the Azores. A total of 593 grafted chestnut trees (Castanea sativa Mill.) were analysed with 10 SSRs: 292 from Portugal and 301 from Spain. Some of the trees studied were more than 300 years old. Accessions were analysed using a model-based Bayesian procedure to assess the geographical structure and to assign individuals to reconstructed populations based on the SSR genotypes. We found 356 different genotypes with a mean value of clonality of 33% owing to grafting. Mutations accounted for 6%, with hybridization being the main diversification process that can explain the great diversity found. Ten main cultivar groups were detected: four in northern Spain, five in the centre of the Iberian Peninsula, and one in southern Spain related to the centre of the Iberian Peninsula. This work demonstrated that cultivar origin and the diversification process was a combination of clonal propagation of selected seedlings, hybridization, and mutations, which allowed high levels of diversity to be maintained with respect to selected clones for fruit production. Furthermore, seedlings and graft sticks facilitated the transport to new destinations in the colonization process, transporting sometimes more than 3000 km if we consider the Azores and the Canary Islands.
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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".