Vegetable oil-based nanoemulsions for the preservation of muscle foods: A systematic review and meta-analysis
Why this work is in the frame
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Bibliographic record
Abstract
This systematic review and meta-analysis quantified the effects of various vegetable oil-based nanoemulsion (NE) formulations on muscle foods’ microbial and chemical quality by estimating the weighted overall response ratio (R*). Treatment of muscle foods with NE formulations reduced the growth rates of total mesophilic bacteria, total psychrophilic bacteria, lactic acid bacteria, and Enterobacteriaceae by 26.2% (R*=0.738), 19% (R*=0.810), 44.7% (R*=0.553), and 31.8% (R*=0.682) during the storage period, respectively. Moreover, the NE formulations retarded the increasing rates of volatile basic-nitrogen content, lipid and protein oxidation, and lipid hydrolysis by 41.4% (R*=0.586), 34% (R*=0.660), 55% (R*=0.450), and 37.1% (R*=0.629), respectively. The NE formulations prepared from safflower, olive, canola, and sunflower oil were more effective than the other vegetable oils to control microbial growth and slow down chemical changes in muscle foods. The combination of nanoemulsions (NEs) and essential oils (EOs) was more efficient than NEs to preserve muscle foods. Packaging NE-treated muscle foods under anaerobic conditions provided better control of microbial growth and chemical changes than packaging under aerobic conditions. Consequently, a combination of vegetable oil-based NEs and EOs followed by anaerobic packaging is the most effective treatment to improve the quality of muscle foods.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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