DNA Fingerprinting of Seeded Bermudagrass Cultivars
Bibliographic record
Abstract
Bermudagrasses ( Cynodon spp.) are important for turf and forage in temperate and tropical climates, with cultivars historically propagated clonally. Over the past two decades the number of seed‐propagated commercial cultivars has dramatically increased, but information is lacking on the extent of the genetic diversity among these new cultivars. Accordingly, this research was undertaken to assess the genetic relatedness of 17 seed‐propagated turf‐bermudagrass cultivars using DNA amplification fingerprinting (DAF). Four DAF and four Minihairpin‐DAF (MHP‐DAF) primers were used in this study. The DAF and MHP‐DAF primers amplified 90 and 131 amplicons, respectively. A total of 13 out of the 17 cultivars were practically indistinguishable using the DAF primers with an average similarity [similarity coefficient (SC)] of 0.982 while the MHP‐DAF primers distinguished all cultivars readily. Results from the DAF and MHP‐DAF analysis indicated that 14 out of the 17 cultivars were related to Arizona common germplasm with average SC of 0.833 in the MHP‐DAF analysis. Arizona common germplasm is naturalized to the Colorado River Valley production areas of Arizona and California. The three most distinct cultivars—‘Princess 77’, ‘Yukon’, and ‘SWI‐11’—had an average SC of 0.668. The most distinct cultivar was Yukon with an average SC of 0.604. Yukon showed 59 DNA signatures not observed in the other cultivars studied with DAF and MHP‐DAF. These results indicated that a majority of seeded‐type bermudagrasses developed over the past two decades depend on a narrow genetic base and that several recent cultivars are markedly genetically distinct, indicating a recent and significant broadening of the germplasm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".