Improving the Salinity Tolerance in Wheat Plants Using Salicylic and Ascorbic Acids
Bibliographic record
Abstract
A pot experiment was conducted during 2013/2014 and 2014/2015 successive growing winter seasons under greenhouse conditions at the Experimental Station, Fac. of Agric., Zagazig Univ., Sharkia Governorate, Egypt to evaluate the response of wheat plants (Triticum aestivum L.) cv. Sakha 93 to different levels of foliar spray of some antioxidant tested substances as ascorbic and salicylic acids at a rate of 0.1 and 0.2%, with respect to vegetative criteria, some physiological properties i.e. phenol components, proline concentration, yield components, NPK-uptake as well as anatomical structure of flag leaf blade grown under salt stress conditions, 3.21 dSm-1 , 6.32 dSm-1 and 10.65 dSm-1 of soil salt. Data indicated that, all studied vegetative criteria of wheat plants, decreased under salt stress condition. Spraying antioxidant substances seemed to partially overcome the harmful effects of salt stress on vegetative criteria. Significant increase in the concentrations of phenols component and proline concentration in response to salt stress treatments. Also, application of tested antioxidant significantly reduced phenols component and increase proline concentration in leaves under water stress condition. Dry matter of straw and grain and yield quality, straw and grains N, P and K-uptake were decreased with increasing the soil salinity level. This trend was found true under all foliar sprays with salicylic and ascorbic acids at different rates. The highest values of straw and grain yield, biological yield, weight of 1000 grain, protein content and yield efficiency, straw and grains N, P and K-uptake of wheat plants occurred with ascorbic acid 0.2% “AA2” treatment followed by ascorbic acid 0.1% “AA1”, salicylic acid 0.2% “SA2”, salicylic acid 0.1% “SA1” and untreated plants that descending order in the two seasons.
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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 | 0.001 |
| 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".