Efficacy of Residual Ozone on Surrogate Microorganisms for Waterborne Pathogens in Bottled Water
Bibliographic record
Abstract
Ozone is a powerful disinfectant that is widely used in the bottled water (BW) industry. Primary ozone disinfection of water for bottling occurs in a reaction tank with a specific contact time. Residual ozone in the bottled water may still possess disinfection activity. The purpose of this study was to evaluate the efficacy of residual ozone in BW in reducing the populations of surrogate microorganisms for waterborne pathogens (Escherichia coli [BAA-1427], Enterococcus faecalis [ATCC 19433] and Burkholderia cepacia [ATCC 25416]). The effect of water pH and total dissolved solids (TDS) on the disinfection process was also evaluated. A pilot scale ozone delivery system and filler were assembled to allow filling of 0.5 L polyethylene terephthalate (PET) plastic water bottles with ozonated (0.1, 0.2, 0.3, and 0.4 mg/L) water. Ozonated water was inoculated with microorganisms to attain ca. 6.0 log and 4.0 log CFU/mL, and microbial populations were determined after 5, 30, 60, and 180 min at 25 °C. Samples (100 mL) were filtered through Neogen NEO-GRID membrane filters and placed on tryptic soy agar, incubated for 48 h at 37 °C, and enumerated. Ozone dissipation in BW was measured with and without biological load (6.0 log CFU/mL) at 21 and 38°C for 6 h. Greater reductions (P ≤ 0.05) in E. faecalis (4.61 and 3.68 log CFU/mL) and B. cepacia (5.24 and 4.12 log CFU/mL) were observed at 0.4 and 0.1 mg/L ozone in BW, respectively. Longer contact time (>5 min) did not result in greater reduction (P > 0.05) in microbial populations. Faster ozone dissipation (P ≤ 0.05) was observed at 38 °C and the dissipation rate increased with biological load. Except at higher pH (9.0) and TDS (50 and 300 mg/L) concentrations, the residual ozone in BW (≥0.1 mg/L) can provide ≥4.0 log reductions in pathogen surrogates E. coli, E. faecalis, and B. cepacia, providing an additional measure of microbiological safety in BW.
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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 | 0.001 | 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) | 0.000 | 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".