Post-harvest Management of Alternaria Induced Rot in Tomato Fruits With Essential Oil of Zanthoxylum armatum DC
Bibliographic record
Abstract
Alternaria fruit rot is a major disease caused by Alternaria alternata (Fr.) Keissl., a prolific fungal pathogen. Among post-harvest diseases of tomato, fruit rot induced by A . alternata is the most damaging. Antifungal agents are widely used to control post-harvest management of tomato fruits. However, negative impacts of fungicidal residues in edible fruits and vegetables on human health cannot be over ruled. Eco-friendly ways of controlling Alternaria rot in tomato fruits offer a novel way of tomato rot management. The current study proposes an alternate method in controlling tomato fruit rots through Zanthoxylum armatum DC essential oil (EO) application. Gas chromatography-mass spectrometry profiling showed eucalyptol and sabinene as major components of Z . armatum EO. Furthermore, EO applied (0.5–4.5 μl/ml) showed significant inhibition of A. alternata growth ( p > 0.05) at 4.5 μl concentration tested. Lipid peroxidation assays revealed significant reduction in membrane damage in tomato fruits treated by EO compared to alone inoculated fruits with A . alternata . Elevated activities of superoxide dismutase, catalase, ascorbate peroxidase, and glutathione reductase coupled with enhanced antioxidants such as ascorbic acid, glutathione, proline, and total phenols in EO-treated fruits may be linked with better fruit rot management than control fruits inoculated with A . alternata -induced rot alone. Mycelia and spore production was dramatically reduced in EO applied tomato fruits over A . alternata alone in tomato fruits ( p > 0.05). Interestingly, free radical scavenging activities of EO applied tomato fruits showed significant improvement compared to only pathogen-inoculated tomato fruits. Findings propose practical utility of Z . armatum EO as a plant-based antifungal for post-harvest management of Alternaria rot in tomato fruits.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".