Observations on water distribution in soybean seed during hydration processes using nuclear magnetic resonance imaging
Bibliographic record
Abstract
Water in seeds plays an important role not only in physiological but also in chemical processes. In addition to the requirements of water for germination, seeds of legumes used for human consumption require hydration to prepare them for cooking. The site of water entry, however, and its movement during imbibition in legumes and particularly in soybean is still not clear. One of the best and most precise methods of tracing water movement in plant tissue is nuclear magnetic resonance (NMR) imaging. In our study, we applied NMR imaging to reveal the water distribution in soybean seeds during the first 24 h of hydration. It has been found that hydration during this period is a multistage process. Water enters the seed through the micropyle and hilum and the concentration of water there is very high during the entire imbibition process. Inside the seed, water first fills the voids between cotyledons, and between the cotyledons and the seed coat. Water then enters the embryonic axis, and from it, is distributed into cotyledons. The highest water concentration after 24 h of imbibition was observed in the embryonic axis. The external part of the cotyledons was hydrated at a slower rate than the internal tissue. Key words: Soybean, Glycine max L., nuclear magnetic resonance imaging, water imbibition, water distribution
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".