Alleviating Salt Stress in Barley by Use of Plant Growth Stimulants and Potassium Sulfate
Bibliographic record
Abstract
Salt impedes plant growth and yield. This study was conducted to explore the effect of plant growth stimulants (seaweed extract, humic acid) and potassium sulfate in alleviating salt stress in barley (Hordeum vulgare L.). Initially, 10 barley genotypes were germinated in a growth chamber at five salt levels (0, 0.5, 1.0, 1.5, and 2.0%). Increasing salt concentration reduced germination percent, the speed of germination, and seedling weight. One salt-tolerant genotype (Sharqiya Estate) and one salt-sensitive genotype (Red Sea) were selected and planted in greenhouse pots containing 2 kg of sand, then subjected to 10 and 15 dS m-1 salt levels using CaCl2.2H2O: NaCl (2:1) mixed with Hoagland solution. Four treatments consisting of (1) control (Hoagland solution), (2) seaweed extract at 4 Kg ha-1, (3) humic acid at 28 L ha-1, and (4) potassium sulfate at 300 Kg ha-1 were applied to each genotype under both salt levels. Seaweed extract resulted in higher shoot dry weight in the salt-sensitive genotype under both salt levels and maintained a low Na+/K+ ratio compared with humic acid and potassium sulfate. It also resulted in higher relative yield, relative water content, higher proline, and lower electrolyte leakage in the susceptible genotype at 10 dS m-1, but the result was not different from humic acid and potassium sulfate treatments at 15 dS m-1. Seaweed extract resulted in the highest catalase activity at 15 dS m-1 in both genotypes, with higher magnitude in the salt-tolerant genotype. These results suggest that seaweed extract has potential in improving barley growth under salt stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".