Effect of Hydrogen Peroxide in the Growth of Yellow Passion Fruit Seedlings Under Salinity Stress
Bibliographic record
Abstract
Hydrogen peroxide (H2O2) is a molecule that can flag plants under biotic and abiotic stress conditions. Among the kinds of stress, the salinity stress is the one that most usually affects plants. Consequently, the purpose hereof was to use hydrogen peroxide (H2O2) to mitigate the possible harmful effects of salinity in yellow passion fruit seedlings. We employed a randomized block design, in a 5 × 3 factorial scheme, corresponding to five irrigation water electric conductivity levels (0.3; 1.3; 2.3; 3.3; and 4.3 dS m-1) and three hydrogen peroxide concentrations (0; 5; and 15 μmol L-1), with four repetitions. The treatments were applied foliarly 7 and 15 days after the seedlings’ germination with hand sprayers. Sixty days after sowing, we evaluated the seedlings’ growth and quality variables, which finally proved that hydrogen peroxide mitigates the harmful effect of the irrigation water’s salinity up to 2 dS m-1 in the growth of yellow passion fruit seedlings at the concentration of 5 μmol/L. Nonetheless, excessive concentrations (15 μmol L-1) associated with high salt concentrations were proven detrimental to the seedlings’ phenological growth and quality.
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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) | 0.001 | 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".