Microbial population profiles of the microflora associated with pre- and postharvest tomatoes contaminated with<i>Salmonella typhimurium</i>or<i>Salmonella montevideo</i>
Bibliographic record
Abstract
AIMS: To determine the microflora profiles of pre- and postharvest tomatoes contaminated with Salmonella montevideo or S. typhimurium DT104. METHODS AND RESULTS: Salmonella montevideo or S. typhimurium was inoculated onto the flowers of tomato plants with the microflora of the subsequent fruit examined using a combination of Source Carbon Utilization and 16S rDNA-PCR profiling. From 16S rDNA profiles it was evident that tomatoes derived from Salmonella inoculated plants harboured a different microbial population compared to nontreated controls. The same result was observed for tomatoes inoculated at postharvest and subsequently stored for 14 days at 15 degrees C. From sequencing analysis it was found that tomatoes derived from Salmonella inoculated plants but testing negative for the enteric pathogen, frequently harboured Enterobacter and Bacillus spp. In contrast, both bacterial types were not found associated with tomatoes testing positive for Salmonella. CONCLUSIONS: Salmonella introduced onto tomatoes at pre- or postharvest alters the composition of the microbial community. The presence of Enterobacter and Bacillus spp negatively affects the persistence of Salmonella on preharvest tomatoes. SIGNIFICANCE AND IMPACT OF THE STUDY: Salmonella appears to modify rather than become integrated into the microbial communities associated with tomatoes. Yet, the presence of antagonistic bacteria appears to reduce the persistence of the enteric pathogen.
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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 | 0.000 |
| 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".