<i>Callistemon Citrinus, Cymbopogon Citratus, and Oxalis Barrelieri </i>Extracts Stimulate Defence of Tomato Against <i>Fusarium</i> Wilt
Bibliographic record
Abstract
In Cameroon, tomato yields remain low due to attacks by pathogens and insects. Fusarium oxysporum f.sp. lycopersici (FOL) is a fungus responsible for Fusarium wilt, a disease responsible for important economic losses. To contribute to the control of this pathogen, the stimulatory effect of the tomato defence system of extracts of plants in the tomato/FOL interaction was evaluated. Tomato plants were treated with the aqueous extracts (AE) of Callistemon citrinus (C. citrinus), Cymbopogon citratus (C. citratus), and Oxalis barrelieri (O. barrelieri) at 10% (W/V). After 4 days of spraying with the extracts, the plants were inoculated with a virulent strain of Fusarium oxysporum f.sp. lycopersici (FOL) in pots experiments. Tomato roots were used to determine the contents of phenols, proteins, carbohydrates, amino acids (AA) and proline. The activities of antioxidant enzymes were evaluated: ascorbate peroxidase (APX), catalase (CAT), guaiacol peroxidase (GPX) and superoxide dismutase (SOD). The results showed that treatment of tomato plants with extracts and their infection with FOL induced an increase in the contents of phenols, proteins, carbohydrates, lipids, amino acids and proline in tomato roots, an increase in APX, GPX, SOD activities and a reduction in CAT activity. Our results suggest that the increase and reduction of enzymatic activities, and the increase in the synthesis of some metabolites could mitigate the oxidative damage that takes place during the expansion of the pathogen. Aqueous extracts of C. citrinus, C. citratus and O. barrelieri could be used as natural products to stimulate the tomato defence system against FOL.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".