Nutrient homeostasis, metabolism of reserves, and seedling vigor as affected by seed priming in coarse rice
Bibliographic record
Abstract
The influence of seed priming on germination, seedling vigor, ion homeostasis, and starch metabolism in coarse rice was studied. Priming treatments included pregermination (a traditional soaking method being used for rice nursery preparation), hydropriming for 48 h, osmohardening with KCl or CaCl2(ψs –1.25 MPa solution) for 24 h, ascorbate priming (10 mg·L–1) for 48 h, and hardening for 24 h. Compared with controls, all priming treatments (except pregermination) reduced the time to start germination, improved the rate of germination and synchronization, and the length of shoot and root, seedling fresh and dry mass, number of secondary roots, the concentration of reducing sugars, and α-amylase activity, although the extent of these changes was different in seeds subjected to different treatments. These seed treatments resulted in higher germination that might be due to overcoming dormancy. Osmohardening with KCl was more effective than CaCl2for these parameters. Nitrogen concentration remained unaffected in seedlings; however, Ca2+concentrations in both seeds and seedlings were greater in seeds osmohardenerd with CaCl2than with all other treatments, including the control. Seed priming enhanced K+concentration in both seeds and seedlings, leading to improved α-amylase activity. There were positive correlations between seed K+concentration and amylase activity, and the concentration of reducing sugars with amylase activity, seedling dry mass, or number of secondary roots. Osmohardening with KCl performed better than all other treatments including control. Priming improved the K+balance that activates α-amylase, a basis for seed invigoration.
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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".