Effects of temperature, light and other treatments on seed germination of <i>Leymus chinensis</i>
Bibliographic record
Abstract
Leymus chinensis (Trin.) Tzvel., a perennial cool-season grass distributed widely in eastern Asia, is an ideal species for the rangeland industry and soil conservation, but the seed has a long dormant period and low germination rates. This study examined the effects of temperature, light and various treatments including stratification, H2SO4, NaOCl, gibberellic acid (GA3) and 6-benzyl adenine (BA), on the germination of Leymus chinensis seed. Seed stored over 1 yr and germinated at a temperature regime of 25/15°C with a 12/12-h photoperiod germinated best, and had a germination rate of 30.3%, with a minimum germination time of 12 d. In these germination conditions, germinated seeds were counted after 15 d to determine the effects of other treatments upon freshly harvested seed germination. The final germination rate for freshly harvested seeds stratified at 4°C for 0 to 10 wk ranged from 8.5 to 37.3%. Germination rates were 14.0 and 14.8% when seeds were treated with 70% H2SO4 for 3 and 6 min, respectively. Seed treated with 5.0% NaOCl germinated 17.5 and 16.0% when treated for 10 and 20 min, respectively. When seeds were soaked in 1000 mg L-1 GA3 solution for 24 h, 42.3% germinated, while treatment with 50 mg L-1 of BA resulted in 50.3% germination. The results indicate that various dormancy mechanisms may exist in the species. These findings will be helpful to farmers and breeders in selecting suitable treatments to improve seed germination and establishment. Key words: Seed dormancy, grassland and sand-dune reclamation, photoperiod, Northern China, Poaceae, seed priming
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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 | 0.000 | 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".