Assessment of Adaptability Parameters of Cocksfoot in the Conditions of the Komi Republic
Bibliographic record
Abstract
Abstract Studies were carried out in order to determine the parameters of adaptability and yield of green mass of collection samples of cocksfoot followed by the selection of the most valuable of them for further breeding work. The work was carried out under the conditions of the Komi Republic in the period from 2016 to 2018. The paper studied promising populations of cocksfoot (Dactylis glomerata L.) of various ecological and geographical origin, which were obtained from the world collection of the Federal Research Center Vavilov All-Russia Institute of Plant Genetic Resources (VIR) by economic characteristics and adaptability parameters. The objects of studies included fifteen domestic populations, including five from the Komi Republic (42733, 42734, 42736, 43024, 45945), three from Arkhangelsk oblast (44342, 36684, 44343), two from Pskov oblast (51856, 51858), one each from Leningrad, Tomsk, and Tyumen oblasts (35060, 46893, 27073, respectively), and four foreign populations—two from Norway (41826, 44021) and one each from Finland and Canada (47268, 33392, respectively). The meteorological conditions during the growing season in the years of the study reflected the unstable nature of the fallout and distribution of precipitation. According to a set of economically valuable parameters, samples 45945, 47268, and 41826 were identified with a yield of green mass of 205–237 c/ha on average for two cuttings. Samples 36684, 47268, and 33392 with values of adaptability parameters for stress resistance from –18 to –96 units, with a coefficient of variation of 5.0–25.2%, and with a selection value of 130–168 units were classified as the most stable and plastic ones. They provide valuable starting material for further study and breeding work.
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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 | 0.001 |
| 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) | 0.001 | 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".