Morphological and Molecular Profiling of Twelve Native Grapevine Varieties From Crete and Thira Islands of Southern Greece: Insights Into Intra-varietal Diversity
Bibliographic record
Abstract
As in the case with other countries with well-documented history in grape cultivation, the discrimination of Greek grapevine resources is an arduous and complicated task due to the use of numerous synonyms and homonyms, the evolution of many phenotypes within varieties and the doubtful origin of several Greek grapevine landraces. The aim of the present study was to present a comprehensive exploration and characterization of twelve autochthonous Greek grapevine cultivars grown in various regions of Crete and Thira islands of southern Greece, using both ampelographic traits and molecular markers. From 2018 to 2022, a total of 112 accessions from commercial vineyards were analyzed using 48 ampelographic characters developed by the International Organization of Vine and Wine (OIV) and 10 microsatellite loci (SSR). According to both methods, the results showed that: (a) nine of the twelve studied varieties appeared in a single cluster in the ampelography-based clustering with the exception of ‘Vilana’, ‘Moschato Spinas’ and ‘Mandilaria’ phenotypes that exhibited a relative significant intra-varietal variation, (b) the matrices produced from ampelographic data revealed a distance between the studied samples from Cretan and Thira vineyards and the reference samples from the national grapevine repository for ‘Athiri’ and ‘Aidani lefko’ varieties, (c) ‘Dafni’ exhibited a clear molecular-genetic distinction and was significantly separated from the other cultivars studied, (d) our data did not support the previously reported high similarity between the varieties ‘Vilana’ and ‘Vidiano’. The combination of ampelographic description and molecular determination of the SSR profile proved to be effective for studying genetic diversity and identifying grapevine cultivars.
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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) | 0.000 | 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".