Preliminary phenotypic and molecular screening for potential bacterial biocontrol agents of<i>Leptosphaeria maculans,</i>the blackleg pathogen of canola
Bibliographic record
Abstract
Leptosphaeria maculans causes blackleg disease of canola (Brassica napus L.). Bacteria isolated from soil, canola stubble and plant parts were assayed for suppression of blackleg. In plate assays, the bacteria isolated from canola stubble had the highest agar-diffusible antifungal activity (75%), which was fungitoxic. In plant cotyledon assays, endophytes had the highest disease suppression. Bacteria with the highest disease suppression in cotyledon assays also had significant disease suppression at the three- to four-leaf stage. PCR screening for bacterial biosynthetic genes, commonly thought to be involved in plant disease suppression, revealed 22 bacteria to be positive for pyrrolnitrin. Pseudomonas chlororaphis and P. aurantiaca isolates contained the phenazine biosynthetic gene. Three Bacillus cereus isolates had the zmaR resistance gene. This study generated a novel set of primers specific to the zwittermicin A biosynthetic cluster. The PCR screening has confirmed the presence of genes encoding pyrrolnitrin (55%), phenazine (10%), zwittermicin A biosynthesis (7.5%) and zwittermicin A resistance (7.5%) from the canola phyllosphere and rhizosphere, which seems more widely distributed than genes for 2,4-diacetylphloroglucinol and pyoluteorin.
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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) | 0.000 | 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) | 0.001 | 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".