Occurrence, characterization, and potential predictors of verotoxigenic Escherichia coli, Listeria monocytogenes, and Salmonella in surface water used for produce irrigation in the Lower Mainland of British Columbia, Canada
Bibliographic record
Abstract
Produce has become a major source of foodborne illness, and may become contaminated through surface water irrigation. The objectives of this study were to (i) determine the frequency of verotoxigenic E. coli (VTEC), Listeria monocytogenes, and Salmonella in surface waters used for irrigation in the Lower Mainland of British Columbia, (ii) assess the suitability of fecal coliforms and generic E. coli as hygiene indicators, and (iii) investigate the correlations of environmental factors with pathogen occurrence. Water samples were collected semi-monthly for 18 months from seven irrigation ditches across the Serpentine and Sumas watersheds. VTEC colonies on water filters were detected using a verotoxin colony immunoblot, and the presence of virulence genes vt1 and vt2 was ascertained via multiplex PCR. Detection of L. monocytogenes and Salmonella was completed using standard, Health Canada Compendium of Analytical Methods. Fecal coliforms and generic E. coli were enumerated by 3M™ Petrifilm™ and filtration methods, and meteorological and geographic data were collected from government records. VTEC, L. monocytogenes, and Salmonella were detected in 4.93%, 10.3%, and 2.69% of 223 samples, respectively. L. monocytogenes occurrence was greatest in the Serpentine watershed (χ2; p < 0.05), and was most common during the winter and fall (Fisher exact test; p < 0.05). Site dependence of VTEC and Salmonella occurrence was observed within watersheds (Fisher's exact test; p < 0.10). Pathogen occurrence correlated with fecal coliform counts (r = 0.448), while VTEC occurrence also correlated with precipitation over the five days before sampling (r = 0.239). The density of upstream livestock correlated with VTEC (rs = 0.812), and L. monocytogenes (rs = 0.841) detection. These data show that foodborne pathogens are present in the waters used for irrigation in the Lower Mainland of British Columbia, but their frequency may depend on spatial and temporal factors.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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".