Molecular genetic diversity of the French-American grapevine hybrids cultivated in North America
Bibliographic record
Abstract
French-American hybrid grapevines are most popular in eastern and mid-western North America: they are hardy cultivars derived from crosses between the European Vitis vinifera and American wild vines. The aim of this study was to characterize their genetic background using 6 microsatellite (SSR) markers and a set of 33 diagnostic RAPD markers. The latter were reproducible with different PCR thermal cyclers. Two SSR loci were found to be synonymous, VrZAG47 and VVMD27. The DNA profile frequencies estimated for each cultivar were much lower with multi-locus SSR data than that obtained from multi-fragment RAPD data. There was no significant correlation between the multi-locus DNA profile frequencies derived from SSRs and those from RAPDs. Estimates of genetic diversity derived from SSRs were generally higher and the average similarity between cultivars was generally lower than values reported for subgroups of V. vinifera, in accordance with expectations for hybrid cultivars. The phenetic relationships depicted by UPGMA (unweighted pair-group method with arithmetic averaging) and neighbor-joining analyses of microsatellite data were congruent and, to a large extent, in agreement with the known pedigree or history of each cultivar. A major dichotomy was observed between one group where the known genetic background was dominated by the North American Vitis riparia and Vitis labrusca, and another one where the genetic background was dominated by the European V. vinifera. Two Kulhmann varieties thought to be synonymous were found to be different, though closely related.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 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".