Genetic Variability for Adaptive, Morphological, and Reproductive Traits in Selected Cold‐Hardy Germplasm of Common Bermudagrass
Bibliographic record
Abstract
Common bermudagrass [Cynodon dactylon (L.) Pers.] has been widely used as a major warm‐season turf and forage grass in the southern United States and in other regions with similar climates around the world. However, it will suffer severe winterkill when grown beyond its region of adaptation. Cold‐hardy bermudagrass germplasm have been developed, but its genetic variation for important turfgrass traits remains unknown. The objective of this study was to quantify genetic variability and determine relationships among adaptive, morphological, and reproductive traits in selected cold‐hardy common bermudagrass germplasm, including 48 clonal plants from ‘Riviera’ and 50 clonal plants from ‘Yukon’. Large genetic variability existed for 12 of 13 adaptive, morphological, and reproductive traits within this germplasm. Spring greenup was found to be positively correlated with turf density and fall color retention. Leaf spot disease had negative correlations with spring greenup and inflorescence prolificacy, and percentage seed set was negatively associated with raceme length. Broad‐sense heritability estimates were 0.03 to 0.25 for first internode length and fourth leaf blade width, 0.36 for first internode diameter, 0.64 for fourth leaf blade length, and 0.72 to 0.80 for inflorescence prolificacy, raceme length, and percentage seed set. The large genetic variability within the winter‐hardy germplasm will provide value in selecting superior parental plants, for producing improved interspecific hybrids, and in forming improved synthetic cultivars and breeding populations.
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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 | 0.000 |
| 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) | 0.001 | 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".