Antimicrobial Efficacy of Peroxyacetic Acid Spray for Beef Carcasses and Cuts at Beef Processing Plants
Bibliographic record
Abstract
ABSTRACT The objective of this study was to assess the antimicrobial efficacy of peroxyacetic acid (PAA) for beef in processing facilities. Inactivation of a wildtype Escherichia coli strain by up to 400 ppm PAA in solutions with different organic loads was determined. The microbial efficacy of PAA was assessed at two commercial beef plants for carcasses and cuts during routine production. The wild type E. coli strain was reduced by >7 log CFU upon exposing to PAA for 15 s at >100 and 200 ppm in low and high organic load solutions, respectively. PAA spray significantly reduced coliforms and E. coli by 1.7–2.0 log units on carcasses artificially inoculated with fecal slurry at one plant, and reduced aerobes and coliforms by 1.7 and 1.0 log units on naturally contaminated carcasses at the other plant. The reduction by PAA spray of aerobes (p < 0.05) on artificially inoculated carcasses was <0.5 log. Significant and consistent reduction of aerobes and coliforms on cuts by PAA was observed for fat surface at both beef plants, but not for lean cut surface. However, fewer cuts sprayed with PAA were positive for E. coli, regardless of cut type, compared with those that were not sprayed. Taken together, PAA can be effective for reducing microbial contamination of beef carcasses and cuts in commercial practice.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".