Evaluation and Genome Analysis of Bacillus subtilis YB-04 as a Potential Biocontrol Agent Against Fusarium Wilt and Growth Promotion Agent of Cucumber
Bibliographic record
Abstract
Cucumber wilt caused by Fusarium oxysporum f.sp. cucumerinum (Foc) is a highly destructive disease that leads to reduced yield in cucumbers. In this study, strain YB-04 was isolated from wheat straw and identified as Bacillus subtilis. It displayed strong antagonistic activity against F. oxysporum f.sp. cucumerinum in dual culture and exhibited significant biocontrol of cucumber Fusarium wilt with a higher control effect than those of previously reported Bacillus strains and displayed pronounced growth promotion of cucumber seedlings. B. subtilis YB-04 could secrete extracellular protease, amylase, cellulose, and β-1,3-glucanase and be able to produce siderophores and indole acetic acid. Inoculation with B. subtilis YB-04 or Foc increased cucumber defense-related enzyme activities for PPO, SOD, CAT, PAL, and LOX. However, the greatest increase was with the combination of B. subtilis YB-04 and Foc. Sequencing the genome of B. subtilis YB-04 showed that it had genes for the biosynthesis of various secondary metabolites, carbohydrate-active enzymes, and assimilation of nitrogen, phosphorous, and potassium. B. subtilis YB-04 appears to be a promising biological control agent against the Fusarium wilt of cucumber and promotes cucumber growth by genomic, physiological, and phenotypic analysis.
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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) | 0.001 | 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 | 0.000 | 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".