The effects of cold pork loins on the pasteurization temperature in sous vide cooking
Bibliographic record
Abstract
Objective: Sous vide is a relatively new cooking method introduced in restaurants in British Columbia. Sous vide cooking involves placing vacuum sealed food inside a temperature controlled water bath or steam convection oven. Unlike conventional cooking, sous vide cooking involves cooking food at a lower temperature (usually < 65°C) with a longer cook time. The low temperature allows chefs to precisely control the changes within the food. Thus sous vide cooked dishes have consistent texture and color, with retained flavor, moistness and nutrients. With all the benefits, sous vide cooking does have some disadvantages. Lower cooking temperature may not be sufficient for bacterial count reduction, resulting in unsafe food. In addition, every validated sous vide menu requires chefs to precisely follow the cooking temperature and cook time. Any deviation can cause the food to not reach the required 6.5 log reduction in bacterial count. The purpose of this experiment was to determine the effect on the internal temperature of cooking-in-process pork loin packages when additional chilled pork loin packages with an internal temperature of 4°C are submerged into the water bath. Methods: Two groups of pork loin packages with data loggers inside (SmartButton) at approximately 4°C were introduced into a 60°C water bath at different intervals. The first group (6 packages) was immersed inside the water bath at time = 0 minute, while the second group (6 packages) was immersed inside the water bath at time = 10 minutes. Both groups were taken out when they were cooked for 31 minutes (at time = 31 minutes and 41 minutes respectively). Water bath temperature was recorded using SPER Scientific 8000024 data logger. Temperature data for pork loin packages was used to calculate the mean lethality achieved by each group. One sample t-test and two sample t-test were used for statistical analysis. Results: There was a more than 3 mean log lethality difference in group A and group B pork loins. Pork loins cooked sous vide style in group A achieved a mean lethality of 5.12 at 31 minutes (range 0.42 to 12.78) while group B pork loins achieved a mean lethality of 8.44 at 31 minutes (range 3.35 to 11.87). With the same cook time, group A had a statistically significantly lower mean lethality than group B pork loins with p value = 0.003. Although statistically inconclusive whether group A pork loins achieved a mean lethality of 6.5, group B pork loins did reach the recommended mean lethality of 6.5. Conclusion: The result indicated when new cold pork loin packages at 4°C are introduced into a cooking-in-process sous vide water bath at 60°C, the lethality of the original pork loin packages in the bath will be lowered if the cook time remains unchanged. However, it is inconclusive on whether the original pork loin packages will reach 6.5 lethality recommended by BCCDC. The new pork loin packages will reach 6.5 lethality if the original cook time is used.
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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 | 0.001 |
| 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 | 0.001 |
| 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".