Physiological and biochemical alterations in soybean by banana peel biochar under different degrees of salt stress
Bibliographic record
Abstract
Abstract Salt influences cellular membranes by the excessive production of reactive oxygen species, while osmolytes play a vital role in protecting plants from oxidative stress caused by salt. Biochar may alleviate the effects of salinity-induced stress on crops. The study investigated the impact of biochar supplementation on osmolyte modifications and antioxidant activity in soybean ( Glycine max cv. AARI) under salt stress conditions. Soybean plants were exposed to 3 salinity levels (without salinity, 5, and 10 dSm − 1 NaCl), and different levels of biochar (without biochar, 12.5%, and 25% w/w). Root and shoot dry weight were reduced by 17% and 21%, respectively, under both salt-induced stress regimens. Salinity elevated the activities of superoxide dismutase (SOD), polyphenol oxidase (PPO), peroxidase (POD), ascorbate peroxidase (APX), and catalase (CAT) as well as O 2 • − (oxygen radicals), MDA (malondialdehyde), and H 2 O 2 (hydrogen peroxide) levels by 3.1-fold, 1.8-fold, 3.1-fold, 2.8-fold, 4.4-fold, 1.4-fold, 2.2-fold, and 2.3-fold in plants relative to control group. Furthermore, higher concentrations of soluble protein, soluble carbohydrates, glycine betaine, and proline were more pronounced at 10 dSm − 1 than at 5 dSm − 1 . In contrast, incorporating biochar into soil enhanced both root and shoots dry weight by 47% and 53% respectively, compared to the absence of biochar application. Furthermore, the antioxidant levels in soybean seedlings cultivated in soil treated with biochar, particularly at a concentration of 25% biochar, decreased. Adding biochar led to a notable decrease in H 2 O 2 (27%), O 2 •− (19%), and MDA (22%) concentrations, along with a reduction in the accumulation of osmotic substances in both roots and leaves. The findings demonstrate that the incorporation of biochar can safeguard soybean seedlings from NaCl-induced stress by alleviating oxidative damage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".