Biological control of the soil-borne fungal pathogen <i>Fusarium oxysporum</i> f <i>.</i> sp. <i>lycopersici</i> —a review
Bibliographic record
Abstract
) is one of the most widely cultivated vegetables worldwide, yet its productivity is severely constrained by Fusarium wilt caused by FOL. The pathogen invades the root system and vascular tissues, leading to systemic wilting, plant collapse, and significant yield losses. Although chemical fungicides have been extensively used for management, their long-term effectiveness is declining due to the emergence of fungicide-resistant strains and the associated environmental and health hazards. This growing challenge underscores the urgent need for sustainable alternatives. In this review, we critically synthesize recent advances in the biological control of FOL, focusing on antagonistic fungi, beneficial bacteria, and the role of organic amendments in creating suppressive soils. Unlike earlier reviews that address these components separately, we emphasize their integration within holistic disease management frameworks. We also highlight promising directions, including microbial consortia, molecular insights into pathogen-antagonist interactions, and the potential of combining biological control with precision agriculture tools. Collectively, these strategies offer a sustainable pathway for mitigating Fusarium wilt and ensuring resilient tomato production systems.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".