Influence of Antimicrobial Agents on the Spoilage of a Meat-Based Entomophage Diet
Why this work is in the frame
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Bibliographic record
Abstract
The microbial decomposition of a meat-based entomophage diet presented in Parafilm packets was investigated. Considerable bacteria but not fungi were associated with components used to prepare the diet (i.e., hens’ eggs, liver, and ground beef). At the initial sampling time, there were no differences among diet treatments in the size of bacterial or fungal populations. Bacterial populations in diets not containing antibacterial agents rapidly increased and reached an asymptote by 24 h (≈1010 colony-forming units per gram). Bacterial populations also increased in diets containing antibacterial agents, but they were significantly smaller than in diets not containing antibacterial agents. The most prevalent bacteria isolated were Carnobacterium piscicola, Carnobacterium divergens, Lactobacillus curvatus, Lactobacillus sakei, Leuconostoc mesenteroides, and Enterococcus spp., regardless of the antibacterial treatment used. The proliferation of fungi was delayed relative to bacteria, but significant differences were observed among the diet treatments. Fungi were most inhibited by sorbic acid and propionic acid in the absence of antibacterial agents. The most common fungi isolated were the yeasts Candida zeylanoides, Torulaspora globosa, and Yarrowia lipolytica. The pH of diets not containing antibacterial agents decreased rapidly and was highly correlated with increases in bacteria but not fungi. The results of this study demonstrate that antimicrobial agents significantly inhibit spoilage microorganisms in a meat-based diet and that alternative management strategies to delay the decomposition of such diets presented in Parafilm packets should target lactic acid spoilage bacteria, particularly Carnobacterium and Lactobacillus species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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