Biological and chemical characterization of antimicrobial activity in <i>Arthrobacter</i> spp. isolated from disease‐suppressive compost
Bibliographic record
Abstract
Antagonistic bacteria can act as biocontrol agents against various phytopathogens. Recently, Arthrobacter spp. demonstrated antifungal activity, but were not further characterized. In this study, the antimicrobial activity of Arthrobacter humicola strains M9-1A, M9-2, and M9-8, and Arthrobacter psychrophenolicus strain M9-17 were evaluated against nine plant pathogens in vitro, and their cell-free filtrates were additionally assessed for inhibition of Alternaria alternata and suppression of black mold disease on tomato fruit. Results indicated that A. humicola M9-1A and A. psychrophenolicus M9-17 were the most inhibitory, reducing growth of seven of the pathogens studied. Cell-free filtrates of A. psychrophenolicus M9-17 reduced the growth of most pathogens. All cell-free bacterial filtrates, except those from A. humicola M9-2, suppressed black mold on tomato fruit. Disk diffusion assays with ethyl acetate soluble culture filtrate extracts of all bacteria reduced the mycelial growth of A. alternata. Clear inhibition zones were observed for A. psychrophenolicus M9-17 extracts using drop bioassays. The antifungal compound N-acetyltryptamine was purified and characterized from the A. psychrophenolicus M9-17 cell-free ethyl acetate soluble extract. This study suggests that antibiosis may play a key role in the antimicrobial activity of Arthrobacter spp.
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) | 0.000 | 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) | 0.001 | 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".