Biological and chemical characterization of antimicrobial activity in <i>Arthrobacter</i> spp. isolated from disease‐suppressive compost
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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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 it