Genetic diversity in colonial bentgrass (<i>Agrostis capillaris</i>L.) revealed by<i>Eco</i>RI–<i>Mse</i>I and<i>Pst</i>I–<i>Mse</i>I AFLP markers
Bibliographic record
Abstract
Colonial bentgrass (Agrostis capillaris L.) is a potential source for genetic improvement of resistance to environmental stress and disease for other bentgrass species (Agrostis spp.). To conserve and study the existing genetic resources of colonial bentgrass for use in breeding, genetic diversity was investigated using amplified fragment length polymorphism (AFLP) markers. Included in this study were 22 accessions from US Department of Agriculture germplasm collected from 11 countries, in conjunction with 14 accessions from northern Spain and 3 commercial cultivars. Ten EcoRI-MseI and 6 PstI-MseI AFLP primer combinations produced 181 and 128 informative polymorphic bands, respectively. Cluster analysis of genetic similarity estimates revealed a high level of diversity in colonial bentgrass species with averages of 0.51 (EcoRI-MseI) and 0.63 (PstI-MseI). Greater genetic diversity was detected by the EcoRI-MseI AFLP primer combinations. A low but significant positive correlation (r = 0.44, p = 0.0099) between the 2 Jaccard similarity matrices was obtained by the Mantel test. Commercial cultivars of bentgrass showed a narrow genetic background. The assessment of genetic diversity among colonial bentgrass accessions suggested the potential value of the colonial bentgrass germplasm in turfgrass cultivar improvement.
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 | 0.000 |
| 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".