Alleviate the Drought Stress on Triticum aestivum L. Using the Algal Extracts of Sargassum latifolium and Corallina elongate Versus the Commercial Algal Products
Bibliographic record
Abstract
Herein, two seaweed extracts (Sargassum latifolium and Corallina elongate), and two commercial seaweed products (Canada power and Oligo-X) with a concentration of 5% were used to alleviate the drought stress on wheat plants. The extract of C. elongate had the highest capacity to ameliorate the deleterious effects of water scarcity followed by S. latifolium and the commercial products. The drought stress reduced wheat shoots length and the contents of pigments (chlorophyll and carotenoids), carbohydrates, and proteins. While the highest increment in the total carbohydrates and protein contents of the wheat shoot after two stages, 37-and 67-days-old, were noted in drought-stressed plants treated with C. elongate extract with values of (34.6% and 22.8%) and (51.9% and 39.5%), respectively, compared to unstressed plants. Decreasing the activity of antioxidant enzymes, peroxidase, superoxidase dismutase, and polyphenol oxidase in drought-stressed plants treated with algal extracts indicated amelioration of the response actions. Analysis of phytohormones in wheat plants exhibited increasing GA3 and IAA contents with percentages of (20.3–13.8%) and (72.7–25%), respectively. Interestingly, all morphological and metabolic characteristics of yield were improved due to the algal treatments compared with untreated drought-stressed plants. Overall, the algal extracts, especially those from seaweed of C. elongate, could represent a sustainable candidate to overcome the damage effects of water deficiency in the wheat plant.
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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 | 0.000 |
| 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".