Genetic Variation of RAPD Markers for North American White Clover Collections and Cultivars
Bibliographic record
Abstract
New white clover (Trifolium repens L.) cultivars with improved winter hardiness and persistence are needed for pasture-based cropping systems in temperate regions of North America. This study evaluated, quantified, and compared genetic variation of populations developed from five recently collected germplasms from Georgia (GA), Iowa (IA), Pennsylvania (PA), West Virginia (WV), and Prince Edward Island (PEI), Canada, and three improved cultivars (‘Regal’, ‘Sacramento’, and ‘Will’). ‘Aurora’ alsike clover (T. hybridum L.) was included for comparison. Random amplified polymorphic DNA (RAPD) profiles of these populations were compared. Euclidean metric distance matrices were calculated for all possible pairwise combinations and were evaluated by analysis of molecular variance (AMOVA). An interpopulation distance matrix [Φst, an analog of F as described by Excoffier et al. (1992)] for the nine populations was used to calculate a dendrogram based on the unweighted paired group method of arithmetic averages. As anticipated, alsike clover was separated from white clover. At a higher level of similarity, the white clovers were separated into only two groups. One group consisted of GA, IA, PA, and PEI germplasms collected from long-established pastures. The second group included Regal, Sacramento, and Will cultivars and the WV collection. Although Will was originally derived from pasture collections, it has a larger leaf size than any of the five white clover collections. The surprising genetic similarities of eight populations derived from different climates and geographic regions of the continent may indicate a common European origin for much of the naturalized white clover in North American pastures.
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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 | 0.001 |
| 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".