Water status influences common events of soluble carbohydrate accumulation during soybean seed development and germination
Bibliographic record
Abstract
Seed development and germination are two distinct physiological stages that are normally separated by a metabolically quiescent period in orthodox seeds. Comparison of seed water status during these two processes and how it influences the biochemical activities remains unclear. The objective of this study was to compare soybean (Glycine max (L.) Merrill cv. Ohio FG1) seed development and germination, including the first 6 h after radicle protrusion, with respect to soluble carbohydrate occurrence at different stages characterized by water content and osmolality. Cyclitols and sugars were monitored at nine stages of development and during the first 30 h of germination. Three phases of water loss and osmolality increase found during seed development were correlated with three phases of water absorption and osmolality decrease during seed germination. This study provided evidence that soybean seed cotyledons and axes have similar patterns of water content and osmolality during seed development and germination and that three major events of soluble carbohydrate occurrence are shared by soybean seed parts during development and germination.Key words: seed development, seed germination, soluble carbohydrates, soybean, water status.
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) | 0.000 | 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".