Plant Extract Treatments Induce Resistance to Bacterial Spot by Tomato Plants for a Sustainable System
Why this work is in the frame
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Bibliographic record
Abstract
The aim of this study is to assess the effect of extracts of Nerium oleander, Eucalyptus chamadulonsis and Citrullus colocynthis against bacterial spot disease of tomato and to investigate the induction of resistance by tomato (Solanum lycopersicum) in order to promote a sustainable management system. The antibacterial activity of aqueous and ethanol plant extracts was tested against Xanthomonas axonopodis pv. vesicatoria, isolate PHYXV3, in vitro and in vivo. The highest antibacterial activity in vitro was obtained with C. colocynthis, N. oleander and E. chamadulonsis, respectively. In vivo, ethanol extracts of N. oleander and E. chamadulonsis were more effective than aqueous extracts in reducing pathogen populations on tomato leaves. Under greenhouse conditions, application of the plant extracts at 15% (v/v) to tomato plants significantly reduced disease severity and increased the shoot weight of ‘Super Marmande’ tomato. In most cases, plant extracts significantly increased total phenol and salicylic acid content of tomato plants compared to either healthy or infected ones. In addition, C. colocynthis and E. chamadulonsis extracts significantly increased peroxidase activity while only E. chamadulonsis increased polyphenol oxidase after infection with the causal agent. The results indicated that the plant extracts showed promising antibacterial activity and could be considered an effective tool in integrated management programs for a sustainable system of tomato bacterial spot control.
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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 it