Validation of the heating treatment of Canadian swine loin smoked on an industrial scale
Bibliographic record
Abstract
Pork meat and its derivatives are widely consumed in the world, in addition to being highly nutritious. A subject of extreme importance for the consumer is food security, since the guarantee of safe food consumption is essential. One of the most used methods aiming at the conservation and elimination of microorganisms in the products is the thermal cooking processing. During the elaboration of meat products, this treatment aims not only to attribute the sensory properties characteristic of the product, but also to guarantee the safety. When safety is the focus, the time / temperature binomial is essential to ensure the destruction of all pathogenic microorganisms and most contaminants. To obtain this guarantee, it is necessary to validate this heat treatment, making it necessary to define the most resistant microorganisms in the process. Salmonella and Listeria are among the most reported microorganisms in the literature as responsible for food outbreaks, even causing deaths, being found in ready-to-eat foods; Enterococcus, on the other hand, is considered one of the microorganisms most resistant to thermal processing used in the meat products industry. Therefore, the work aimed to validate the thermal processing of Smoked Canadian Pork Loin on an industrial scale, using Salmonella spp, Listeria monocytogenes and Enterococcus faecalis as the target microorganism. First, the temperature of the cooking oven was evaluated in 12 points (considering the ends and the central points), obtaining the cold point located on the left side, lower height and middle depth. At this point, the product's cooking temperatures were collected to calculate the lethality according to the Bigelow model, where reductions higher than those mentioned in the legislation and researched literature were observed, with 14.215 cycles for Salmonella spp, 641 for Listeria monocytogenes and 71 for Enterococcus faecalis. Analyzes of centesimal composition, physical-chemical and microbiological properties were also carried out to meet the technical regulations, which were all within the recommended standards. In order to verify whether the time and temperature binomials could be modified, resulting in a reduction in cooking time and optimizing heat treatment, a simulation of thermal transfer was performed using mathematical equations. It can be observed that the temperature when it reaches 72 ºC with 120 minutes of cooking, simulates the same conditions of the complete cycle, which would have an internal temperature of up to 74 °C and a final time of 285 minutes, and with regard to the food safety of the product, it would be able for consumption. However, studies related to sensory analysis must be carried out to check whether the product has the same sensory characteristics when compared to the traditional process. Due to the mentioned aspects, the process of heat treatment of the Smoked Canadian Type Pork Loin in the industry, is fit and can be reproduced, as long as the conditions of each thermal processing are verified and respected.
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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 | 0.001 |
| 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".