Inactivation of <i>Escherichia coli</i> on Romaine Lettuce Using a Gas‐Phase Hydroxyl‐Radical Process: From Laboratory Scale to Commercial Processing
Bibliographic record
Abstract
The following reports on the efficacy of a gas‐phase hydroxyl radical‐based process for decontaminating shredded lettuce on a laboratory and simulated commercial scale. The process is based on the ultraviolet light at 254 nm UV‐C‐mediated degradation of hydrogen peroxide mist and ozone gas to generate antimicrobial hydroxyl radicals. Escherichia coli K12 was applied as a surrogate for E. coli O157:H7, and at laboratory scale, the hydroxyl‐radical process (1.5% vol/vol H2O2 delivered at 40 ml/min, UV‐C dose 114 mJ/cm2, 20 ppm ozone, 29°C chamber temperature, and 30 s residence time) could support a 1.63 ± 0.61 log CFU reduction. This is compared to the 0.57 ± 0.18 log CFU reduction obtained for a chlorine‐based wash. In scale‐up, batches (2‐10 kg) of E. coli inoculated romaine lettuce were passed through sequential hydroxyl‐radical reactors. Here, the units were elevated to create a cascade effect, with the hydrogen peroxide mist being introduced as an intermister between the reactors. It was found that the three units placed in sequence with intermisters supported a 2.05 ± 0.10 log CFU reduction of E. coli, thereby verifying that homogenous treatment had been achieved. Additional trials operated the hydroxyl‐radical process at 4°C without loss of performance. The hydroxyl‐radical process was not negatively affected by applying a pretreatment wash. The study has demonstrated that the hydroxyl‐radical process can be applied as an alternative to postharvest wash to enhance the food safety of romaine lettuce.
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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) | 0.001 | 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".