The occurrence of Listeria monocytogenes is associated with built environment microbiota in three tree fruit processing facilities
Bibliographic record
Abstract
BACKGROUND: Multistate foodborne disease outbreaks and recalls of apples and apple products contaminated with Listeria monocytogenes demonstrate the need for improved pathogen control in the apple supply chain. Apple processing facilities have been identified in the past as potential sources of persisting L. monocytogenes contamination. In this study, we sought to understand the composition of microbiota in built apple and other tree fruit processing environments and its association with the occurrence of the foodborne pathogen L. monocytogenes. RESULTS: Analysis of 117 samples collected from three apple and other tree fruit packing facilities (F1, F2, and F3) showed that facility F2 had a significantly higher L. monocytogenes occurrence compared to F1 and F3 (p < 0.01). The microbiota in facility F2 was distinct compared to facilities F1 and F3 as supported by the mean Shannon index for bacterial and fungal alpha diversities that was significantly lower in F2, compared to F1 and F3 (p < 0.01). Microbiota in F2 was uniquely predominated by bacterial family Pseudomonadaceae and fungal family Dipodascaceae. CONCLUSIONS: The composition and diversity of microbiota and mycobiota present in the investigated built food processing environments may be indicative of persistent contamination with L. monocytogenes. These findings support the need for further investigation of the role of the microbial communities in the persistence of L. monocytogenes to support the optimization of L. monocytogenes control strategies in the apple supply chain.
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How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".