Survival of <i><scp>E</scp>scherichia coli</i> <scp>O</scp>157:<scp>H</scp>7 during the Manufacture and Storage of Fruit Yogurt
Bibliographic record
Abstract
Abstract The objectives of the study were to assess the behavior of Escherichia coli O157:H7 during the manufacture of fruit yogurt at different fermentation and storage temperatures. Reconstituted milk was fermented at 37, 40 or 45C; the resultant product was stored at 4, 10 or 15C for 7 days. Samples of milk and yogurt were analyzed. E. coli O157:H7 and lactic acid bacteria (LAB) counts; pH of samples was recorded. During fermentation, E. coli O157:H7 grew in the presence or absence of LAB regardless of temperature. E. coli O157:H7 increased in presence of thermophilic LAB more than 2.75 log cfu/mL. The growth of LAB in all samples showed the same trend. The pH values of milk containing E. coli O157:H7 and LAB decreased gradually to reach 4.6 ± 0.1 at the end of fermentation period. During cooling, there was neither growth nor death of E. coli O157:H7 at 4 and 10C, while a slight increase at 15C. All the experiments showed significant differences in the population of E. coli O157:H7 in the presence or absence of LAB. During storage, E. coli O157:H7 number declined for all experiments and approached undetectable levels at the end of storage. The sensitivity of E. coli O157:H7 to acidity and lowered temperature was noticed during storage. Practical Applications Escherichia coli O157:H7 has emerged as a major foodborne pathogen and has been implicated in several outbreaks involving milk and dairy products. The results of the present study indicate that E. coli cannot tolerate the acidity and storage temperature. Applying quality control systems in the processing line will ensure that the E.coli will not survive in the commercially prepared fruit yogurt.
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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) | 0.002 | 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".