The effects of thermal treatment on the bacterial community and quality characteristics of meatballs during storage
Bibliographic record
Abstract
Abstract Thermal treatment is a widely applied food processing technology in the meat industry due to its convenience. However, the interpretation of the changes in the bacterial community and quality properties in the thermal processed meat products have not been well established. Therefore, the effects of thermal treatment on the quality characteristics and bacterial communities in meatballs during storage at 4°C were investigated, which will provide a more comprehensive understanding of the influence of thermal treatment on the meat quality. Thermal treatment (121°C, 15 min) decreased the initial total viable bacterial counts by 2.1 log CFU/g and the diversity of the initial bacterial communities in meatballs. Compared with the thermal treatment group, a significantly more rapidly increasing trend of total volatile basic nitrogen and a decreasing trend of pH were observed in the control group. At the end of storage, the bacterial community was dominated by Streptococcus , Acinetobacter and Pseudomonas in the thermal treatment meatballs, whereas Pseudomonas , Pantoea , and Serratia . dominated the bacterial community of the control group. Besides, the predicted metabolic pathways revealed high levels of carbohydrate, amino acid, and lipid metabolism in the control group. This finding could contribute to a deep understanding of the influence of thermal treatment on the meat quality. Moreover, these results could provide a theoretical foundation for the development of alternative and novel nonthermal processing technologies for use in the meat industry.
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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 | 0.001 | 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".