AFLP analysis of genetic variation within the two economically important Anatolian grapevine (<i>Vitis vinifera</i>L.) varietal groups
Bibliographic record
Abstract
The Anatolian region of modern-day Turkey is believed to have played an important role in the history of grapevine (Vitis vinifera L.) domestication and spread. Despite this, the rich grape germplasm of this region is virtually uncharacterized genetically. In this study, the amplified fragment length polymorphisms (AFLP)-based genetic relations of the grapevine accessions belonging to the 2 economically important Anatolian table grape varietal groups known as V. vinifera 'Misket' (Muscat) and V. vinifera 'Parmak' were studied. Thirteen AFLP primer combinations used in the analyses revealed a total of 1495 (35.5% polymorphic) and 1567 (34.6% polymorphic) DNA fragments for the 'Misket' and 'Parmak' varietal groups, respectively. The unweighted pair-group method with arthimetic averaging (UPGMA) cluster analysis and principal coordinate analysis (PCA) conducted on polymorphic AFLP markers showed that both varietal groups contain a number of synonymous (similar genotypes known by different names) as well as homony mous (genetically different genotypes known by the same name) accessions. Our results also showed that 6 of the Anatolian 'Misket' genotypes were genetically very similar to V. vinifera 'Muscat of Alexandria', implying that these genotypes might have played some role in the formation of this universally known grape cultivar. Finally, the close genetic similarities found here between 'Muscat of Alexandria' and V. vinifera 'Muscat of Hamburg' support the recent suggestion that 'Muscat of Hamburg' probably originated from 'Muscat of Alexandria' through spontaneous hybridizations. Overall, the results of this study have implications for not only preservation and use of the Anatolian grape germplasm, but also better understanding of the historical role that this region has played during the domestication of grapes.
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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".