Modeling the combined effect of NaCl and pH against <i>Cronobacter</i> spp. using response surface methodology
Why this work is in the frame
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Bibliographic record
Abstract
Abstract The growth response of Cronobacter spp. to different levels of NaCl and pH was investigated using response surface methodology. Brain heart infusion (BHI) broth containing 0 to 10% (w/v) NaCl at pH values of 4.5 to 8.0 was inoculated with a cocktail of 5 Cronobacter spp. The mixtures were incubated at 37°C and were sampled at intervals of 0, 2, 4, 6, 8, and 24 hr. Cronobacter spp. were recovered on tryptose soy agar and response surface methodology was employed to investigate the effect of NaCl, pH or their combination on growth and viability. At pH ≤ 5.0, the viability of Cronobacter spp.was reduced below the detection limit after 4 h. In addition, ≥6% NaCl significantly affected Cronobacter spp. growth. However, the interactive effects of pH at 5.5 and 2 to 4% NaCl reduced Cronobacter growth. The response surface analysis indicated that combining NaCl with pH would cause a significantly greater reduction in Cronobacter viability than would be caused by each factor alone. These results showed that Cronobacter may be controlled in food products by concentrations of NaCl ≤4% at pH values ≤5.5. Practical applications Cronobacter spp. have been isolated from a wide range of foods including cheese, meat, grains, herbs, spices, fermented bread, tofu, infant foods, and fermented beverages Cronobacter spp. have a remarkable ability to survive under a variety of environmental stresses including those involving low water activity (a w ), acidic pH, osmotic challenge, and mild heating. In the current study, the results showed that the growth of Cronobacter in food products could be controlled by the combined effect of NaCl and pH at concentrations of NaCl ≤ 4% at pH values ≤ 5.5.
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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 | 0.003 | 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 it