Osmotic adjustment and plant adaptation to environmental changes related to drought and salinity
Bibliographic record
Abstract
The salinization and water deficit of soil are widespread environmental problems in limiting plant survival, growth, and productivity. However, some plants could adopt some strategies to resist salinity and drought stresses. Among these strategies, the mechanism of osmotic adjustment could help plants and algae to avoid ion toxicity and maintain water uptake in both stresses by accumulating large quantities of osmolytes. Two types of osmolytes, organic solutes and inorganic ions, play a key role in osmotic adjustment. Different osmolytes and their osmotic adjustment actions are different according to their distribution in different plants. Organic solutes, known as compatible solutes, include amino acids, glycerol, sugars, and other low molecular weight metabolites, serve a function in cells to lower or balance the osmotic potential of intracellular and extracellular ions in resistance to osmotic stresses. Inorganic ions for osmotic adjustment are mainly Na + , K + , Ca 2+ , and Cl – . Inorganic ions make great contribution in osmotic adjustment by ion transport processes with related ion antiporters and ion channels. The aim of this review is to integrate recent data on the mechanisms of osmotic adjustment by osmolytes in plants and algae, and to illustrate the variety of related molecular mechanisms, to introduce new concepts and techniques into this research field. Genetic manipulation including the application of transgenic techniques in plants provides promising strategies to elevate the tolerance capability of plants under osmotic stress conditions.
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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 | 0.001 | 0.001 |
| 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".