Assessing Aerated Vermicompost Tea Combined with Microbial Biological Control Agents for Suppression of <i>Fusarium</i> and <i>Rhizoctonia</i>
Bibliographic record
Abstract
Biological control of plant diseases is important in organic greenhouse vegetable production, where fungicide use is limited. Organic producers use microbially diverse substrates, including composts, as media for plant growth. Previous research into the impact of vermicompost on the efficacy of applied biocontrol agents is limited. An in vitro assay was developed to test the efficacy of two biological control agents in a competitive microbial background. Suppression of the pathogen Fusarium oxysporum f. sp. radicis-cucumerinum by Clonostachys rosea f. catenulata (Gliocladium catenulatum strain J1446 [Prestop]) and Bacillus subtilis strain QST 713 (Rhapsody), was assessed on agar media amended with aerated vermicompost tea (ACT). Pathogen growth was reduced more by C. rosea than ACT alone, and C. rosea was equally effective when combined with ACT. In contrast, B. subtilis reduced pathogen growth less than ACT and, when combined, reduced pathogen growth no more than ACT alone. Both biocontrol agents were similarly tested with ACT against F. oxysporum f. sp. radicis-cucumerinum and Rhizoctonia solani on cucumber and radish. Additive, neutral, and antagonistic responses, depending on host, pathogen, and biocontrol agent, were observed. ACT alone provided more consistent disease suppression on cucumber compared with B. subtilis or C. rosea. In combination, disease suppression was most often better than each biocontrol alone but not better than ACT alone. ACT had antagonistic or additive interactions with C. rosea in the radish/R. solani pathosystem, depending on the experiment. The specific and general suppression of plant diseases by biological control agents in microbially rich environments is variable and warrants further study.
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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) | 0.000 | 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 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".