Estimation of base germination temperature of ten seeded-type bermudagrass cultivars
Bibliographic record
Abstract
Summary Several studies have demonstrated that the establishment of bermudagrass [ Cynodon dactylon (L.) Pers.] in transition zones should take place as early as possible in spring in order to avoid damage in the winter of the first year. To define the base germination temperature of some commercial common bermudagrass cultivars in Europe, a laboratory study was conducted from April to May 2013 at the Agricultural Research Council Laboratory of Tavazzano (Lodi). Ten bermudagrass cultivars: 'Gobi', 'Sunbird', 'SR9554', 'Princess77', 'Yukon', 'Riviera', 'Transcontinental', 'Casinò Royal', 'Savannah', and 'La Paloma' were tested at alternating temperature regimes 0/10°C, 5/15°C, 10/20°C, 15/25°C to assess final germination percentage and seed vigour through calculation of the Germination Rate Index and Corrected Germination Rate Index. This study shows that seeded bermudagrass cultivars have significantly different germination capacity at the tested temperatures. In addition, findings indicate that seeded bermudagrass can even germinate at temperatures of 10/20°C, corresponding to an average temperature of 15°C. Among tested cultivars 'Riviera' showed the slowest germination.
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 | 0.000 | 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".