Increased cucumber salt tolerance by grafting on pumpkin rootstock and after application of calcium
Bibliographic record
Abstract
Self-grafted and pumpkin rootstock-grafted cucumber plants were subjected to the following four treatments: 1) aerated nutrient solution alone (control), 2) nutrient solution with 10 mM Ca(NO3)2 (Ca), 3) nutrient solution with 90 mM NaCl (NaCl), and 4) nutrient solution with 90 mM NaCl + 10 mM Ca(NO3)2 (NaCl+Ca). The NaCl treatment decreased the plant dry mass and content of Ca2+ and K+ but increased the Na+ content in roots and shoots. Smaller changes were observed in pumpkin rootstock-grafted plants. Supplementary Ca(NO3)2 ameliorated the negative effects of NaCl on plant dry mass, relative growth rate (RGR), as well as Ca2+, K+, and Na+ content especially for pumpkin rootstock-grafted plants. Supplementary Ca(NO3)2 distinctly stimulated the plasma membrane (PM) H+-ATPase activity which supplies the energy to remove excess Na+ from the cells. The expressions of gene encoding PM H+-ATPases (PMA) and gene encoding a PM Na+/H+ antiporter (SOS1) were up-regulated when Ca(NO3)2 was applied. The pumpkin rootstock-grafted plants had higher PM H+-ATPase activity as well as higher PMA and SOS1 expressions than the self-grafted plants under NaCl + Ca treatment. Therefore, the addition of Ca2+ in combination with pumpkin rootstock grafting is a powerful way to increase cucumber salt tolerance.
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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) | 0.001 | 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 | 0.001 |
| 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".