The Use of Malic and Acetic Acids in Washing Solution to Control <i>Salmonella</i> spp. on Chicken Breast
Bibliographic record
Abstract
Abstract Salmonella is a persisting contaminant in poultry products that may pose a potential risk to consumers. Thus, developing decontamination strategies to eliminate or reduce this pathogen in chicken is crucial. The objective of the current study was to investigate the antimicrobial activity of malic acid (MA) and acetic acid (AA) or their combination against Salmonella on chicken breast at 4 °C for 10 days. The effect of storage temperature (4 and 21 °C) on Salmonella inactivation was also investigated for up to 21 days. Five serovars of Salmonella were inoculated in a model Mueller‐Hinton (MH) broth system to a level of about 7 log 10 CFU/mL and the broth was treated with 5 mg/mL of each of MA, AA or their combination. AA was more effective than MA in the model system at 21 °C, where it resulted in total elimination of Salmonella , but MA was more effective in eliminating Salmonella at 4 °C. However, the combined MA and AA solutions were more effective than either MA or AA alone. When applying washing solutions containing 5 mg/mL of either of MA, AA, or their combination to chicken breast inoculated with about 5 log 10 CFU/g, the MA+AA washing solution was the most effective. It resulted in complete elimination of Salmonella from chicken breast and rendered a significant reduction in mesophilic aerobic bacteria and lactic acid bacteria numbers. Practical Application This study indicates that the use of a washing solution containing MA and AA could improve the safety and extend the shelf life of raw chicken by substantially reducing Salmonella and contaminating microflora on the product.
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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) | 0.001 | 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) | 0.001 | 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".