Analysis of<i>Salmonella</i>and enterococci isolated from rendered animal products
Bibliographic record
Abstract
The objectives of this study were to determine the current status of bacterial contamination in rendered animal products and to analyze Salmonella and enterococci isolates from the samples. One hundred and fifty samples were provided by various rendering companies across the United States, including the following meal types: feather, meat, meat and bone, meat and bone from poultry, poultry, and blood meals. The average pH of the meals ranged from 6.16 to 7.36, and the moisture content ranged from 1.9% to 11.5%. The total bacterial counts were in the range of 1.7 to 6.68 log10 CFU/g, with the highest in blood meal and the lowest in meat meal. Enterococcus species were detected in 81.3% of the samples and accounted for up to 54% of the total bacterial counts in some samples. Both blood meal and feather meal were more contaminated (P < 0.05) with enterococci than other meal types, although all blood meals were from a single company. Salmonella was detected in 8.7% of the samples. Escherichia coli was not detected in any of the samples, but coliforms were detected in four samples. Among enterococci isolates, three were vancomycin resistant. Thirteen serotypes of Salmonella displayed 16 pulsed-field gel electrophoresis patterns. Pulsed-field gel electrophoresis analysis has indicated that Salmonella contamination was not persistent in the plant environment over time. The D-values for the Salmonella isolates at 55, 60, and 65 degrees C were in the ranges of 9.27-9.99, 2.07-2.28, and 0.35-0.40 min, respectively. These results suggest that the presence of Salmonella in the finished products may be due to postprocessing contamination. This study has also revealed that the rendering industry has microbiologically improved its products since earlier studies were conducted.
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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 | 0.000 |
| 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 | 0.001 | 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 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".