Enzymatic Activity in Essential Oil-Treated and Pathogen-Inoculated Corn Plants
Bibliographic record
Abstract
Bipolaris maydis and Exserohilum turcicum are important fungal pathogens that cause leaf blight in corn whose control have been difficult. Essential oils are a promising and environmentally friendly alternative for disease management, but the mechanisms of action remain poorly studied. Here, we aimed to assess the effect of B. maydis and E. turcicum as well as the essential oil of Morinda citrifolia in the activity of plant defense enzymes in corn plants. Experiments were carried out in a completely randomized design with three replications and six treatments as they follow: (T1): corn plants inoculated with B. maydis; (T2): corn plants inoculated with E. turcicum; (T3): corn plants treated with essential oil of M. citrifolia (0.25%) and inoculated with B. maydis; (T4): corn plants treated with essential oil of M. citrifolia (0.25%) and inoculated with E. turcicum; (T5): corn plants treated with essential oil of M. citrifolia (0.25%); and (T6): corn plants non-inoculated and treated with distilled water. Protein content (PC) and activities of the enzymes ascorbate peroxidase, catalase, chitinase (CHI), peroxidase (POX) and superoxide dismutase (SOD) were assessed. PC was significantly decreased, whereas CHI and SOD activity was higher in T1-T5 compared to T6. T4 and T5 significantly increased POX activity relative to T6. Therefore, our findings suggest that the essential oil of M. citrifolia may play an active role in disease control by activating defense enzymes in corn plants.
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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".