Native bacterial communities and <i>Listeria monocytogenes</i> survival in soils collected from the Lower Mainland of British Columbia, Canada
Bibliographic record
Abstract
Soil is an important reservoir for Listeria monocytogenes, a foodborne pathogen implicated in numerous produce-related outbreaks. Our objectives were to (i) compare the survival of L. monocytogenes among three soils, (ii) compare the native bacterial communities across these soils, and (iii) investigate relationships between L. monocytogenes survival, native bacterial communities, and soil properties. Listeria spp. populations were monitored on PALCAM agar in three soils inoculated with L. monocytogenes (∼5 × 106 CFU/g): conventionally farmed (CS), grassland transitioning to conventionally farmed (TS), and uncultivated grassland (GS). Bacterial diversity of the soils was analyzed using 16S rRNA targeted amplicon sequencing. A 2 log reduction of Listeria spp. was observed in all soils within 10 days, but at a significantly lower rate in GS (Fisher’s least significant difference test; p < 0.05). Survival correlated with increased moisture and a neutral pH. GS showed the highest microbial diversity. Acidobacteria was the dominant phylum differentiating CS and TS from GS, and was negatively correlated with pH, carbon, nitrogen, and moisture. High moisture content and neutral pH are likely to increase the ability of L. monocytogenes to persist in soil. This study confirmed that native bacterial communities and short-term survival of L. monocytogenes varies across soils.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".