Cl− More Detrimental Than Na+ in Rice Under Long-Term Saline Conditions
Bibliographic record
Abstract
Rice is considered sensitive to salinity and hence, improving the salinity tolerance of rice is desired to increase productivity. Most research on salinity tolerance for the growth and grain yield of rice focuses on the toxicity of sodium (Na+) and not chloride (Cl−); the information on the negative effects of Cl− on rice is still limited. To learn the difference in the long-term effects of Na+ and Cl− on the whole plant and grain productivities, three rice varieties differing in salinity tolerance were grown in pots irrigated by water with NaCl and KCl in the same molar concentration. The whole plant dry weight and grain yield in all varieties decreased to the same extent after NaCl and KCl treatments compared to the control during the full heading and maturity stages. However, Na+ content in shoots of all varieties under NaCl treatment were higher at all stages than that under KCl treatment and the control. In the most cases, the Cl− content in plants was similar in the NaCl and KCl treatment groups. There was a negative significant correlation between the relative dry weight and grain yield (treated/control) and the Cl− content in the plants. From these results, it was suggested that plant dry weight and grain yield under long-term salinity conditions was reduced by Cl− toxicity rather than Na+ toxicity.
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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 | 0.001 | 0.001 |
| 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".