The Influence of H2O2 Application Methods on Melon Plants Submitted to Saline Stress
Bibliographic record
Abstract
The salinity in irrigation water is one of the most important causes to decline cultivated plants yield. The H2O2 application has shown efficiency as a stimulator and activator for antioxidative defense system in plants submitted to biotic and abiotic stresses. The objective of this study was to evaluate methods for hydrogen peroxide application as a strategy to minimize the effects of saline stress on melon plants. The experiment was designed in complete randomized blocks and set in 2 × 4 factorial scheme, consisting two levels for irrigation water salinity (S1 = 0.3 and S2 = 2.0 dS m-1) and four methods for hydrogen peroxide application (15 mM), (T1 = no peroxide application, T2= imbibition of seeds, T3 = at sowing, T4 = Foliar spraying), with five repetitions. It was evaluated the following variables at 58 days after transplanting: plant height, stem diameter, number of leaves, number of flowers, shoot dry mass, root dry mass and total dry mass. The results showed that salinity affected the growth, biomass accumulation and plant quality severely, with the highest losses promoted by the electrical conductivity of 2.0 dS m-1.
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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 | 0.001 |
| 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".