Abiotic Compounds as Inducers of Resistance to Fusarium Wilt in Tomatoes
Bibliographic record
Abstract
To study the effects of resistance inducers used to control fusarium wilt in tomatoes due to the fungus Fusarium oxysporum Schlecht f. sp. lycopersici, we evaluated the effects of ASM (acibenzolar-S-methyl), Agro-Mos, chitosan, Biopirol and neem oil on F. oxysporum f. sp. lycopersici mycelial growth and sporulation and systemic resistance in tomatoes. In vitro experiments comprised evaluations of the products’ effects on the mycelial growth and sporulation of the PDA (potato dextrose agar) growth medium-cultured pathogen. In vivo experiments included product application to tomato plants of the Santa Cruz cultivar that were grown for 25 days on autoclaved soil, followed by determinations of disease severity and peroxidase, polyphenol oxidase and Beta-1,3-glucanase enzyme activity levels, which are related to the process of resistance induction. Pathogen inoculation occurred after 5 days at a concentration of 106 conidia/mL. We evaluated the disease according to a rating scale. Enzymatic activity was determined according to specific protocols. Neem oil controlled pathogen mycelial growth and sporulation, while ASM influenced sporulation. The products reduced the severity of wilt in the plants. We highlight neem oil, Agro-Mos and Biopirol due to their ability to induce significant peroxidase, polyphenol oxidase and Beta-1,3-glucanase expression, respectively.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".