Occurrence of Salmonella, Campylobacter, Yersinia enterocolitica, Escherichia coli O157 and Listeria monocytogenes in Swine
Bibliographic record
Abstract
The objective of this study was to investigate the occurrence of major bacterial foodborne pathogens in swine. In total, 359 samples from manure storage tanks (91) and fresh pooled faeces (268) obtained from finisher (110), sows (78) and weanlings (80) were collected and tested. Campylobacter, Salmonella, Yersinia enterocolitica, Escherichia coli O157 and Listeria monocytogenes were isolated from 36.5%, 31.5%, 5.8%, 3.3% and 3.3% of samples respectively. All E. coli O157 isolates found on 10 farms were tested but none was determined to be E. coli O157:H7. Salmonella and Campylobacter were more likely to be detected from stored manure rather than from fresh faecal samples. Yersinia enterocolitica tended to be detected more commonly from fresh samples than from manure pits. Listeria monocytogenes was not recovered from manure pits or from sow faecal samples and only infrequently found in the faeces of weanling pigs and finisher pigs. The proportion of positive samples showed a seasonal change. Salmonella was twice as likely not be recovered in winter, whereas the chance of culturing Campylobacter was higher in winter. The 113 Salmonella isolates recovered on 24 farms and the four most common serovars were Salmonella Typhimurium var. Copenhagen (31.0%), Salmonella Derby (12.4%), S. Typhimurium (10.6%) and Salmonella Agona (10.6%). Of 131 Campylobacter isolates recovered on 21 farms, 118 isolates were Campylobacter coli and 13 isolates could not be speciated. Fifteen of 21 Y. enterocolitica isolates found on 15 farms were detected in finisher pigs. The sero/biogroups of Y. enterocolitica were O3/biotype 4 (16 isolates), O6,30/biotype 1A (three isolates), O5/biotype 1A (one isolate) and O8/biotype 1B (one isolate). These findings provide baseline information on the distribution of important zoonotic pathogens in swine and indicate that pigs should be considered as a possible source of foodborne diseases in humans.
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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 | 0.001 |
| 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 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".