<i>Bacillus safensis</i> LS01 provides biological control of potato common scab with potential effects from secondary metabolites
Bibliographic record
Abstract
AIMS: Potato common scab (CS), caused by pathogenic Streptomyces, is a devastating disease affecting potato crops worldwide. Antagonistic microorganisms have been used as biological control agents to inhibit Streptomyces scabies and reduce the use of synthetic pesticides. However, identifying beneficial microorganisms for controlling CS remains undetermined. METHODS AND RESULTS: Strain LS01 was isolated from the geocaulosphere soils of healthy potato tubers. In vitro and pot experiments demonstrated that strain LS01 significantly inhibited the mycelial growth and sporulation of S. scabies, thereby reducing the severity of CS. Sequencing of the 16S rRNA of LS01 indicated that the strain belonged to the species Bacillus safensis. Whole-genome sequencing, metabolomic analysis with liquid chromatograph mass spectrometer, and uultra-high performance liquid chromatography with quadrupole time-of-flight mass spectrometry analyses indicated that hygromycin B and plantazolicin may be the active secondary metabolites by which B. safensis LS01 inhibits S. scabies. CONCLUSIONS: Bacillus safensis LS01 is a potential biocontrol agent for CS, with its secondary metabolites exerting effective inhibitory effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
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".