Silicon mediates the changes in water relations, photosynthetic pigments, enzymatic antioxidants activity and nutrient uptake in maize seedling under salt stress
Bibliographic record
Abstract
Abstract It was hypothesized that silicon (Si) could regulate the salinity induced changes for adequate physiological adaptations against salt stress. Therefore, a pot study was conducted to assess the role of soil applied Si to improve the salt tolerance in maize seedling. Fifteen‐day‐old seedlings were subjected to four saline treatments with four replicates, namely control (no NaCl nor Si added), only Si (4 mmol L−1 Si), only salinity (40 mmol L−1 NaCl) and salinity + Si (40 mmol L−1 NaCl with 4 mmol L−1 Si) as salt concentration. Salt stress imposed negative impacts on plant growth attributes (root and shoot length, fresh and dry weight of root and shoot, seedlings biomass), water relations and photosynthetic pigments. In contrast, the supplementation of Si under stressed and normal growing conditions stimulated plant growth attributes, water relations and photosynthetic pigments. An increase in antioxidant enzyme activity was noted under stressed conditions, which was more pronounced in plants that experienced Si application. Silicon application under stressed conditions lowered the total soluble protein contents. It also regulated the ionic contents of the cell by restricting the sodium (Na+) and improving potassium (K+) contents. To conclude that soil applied Si was found a potential nutrient for reducing the negative effects of salinity and improving the growth of maize seedlings.
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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".