COMPARISON OF EXCISION, SWABBING AND RINSING SAMPLING METHODS TO DETERMINE THE MICROBIOLOGICAL QUALITY OF BROILER CARCASSES
Bibliographic record
Abstract
ABSTRACT Skin excision, swabbing with cotton wool and whole carcass rinse are three common sampling methods of poultry carcasses. The objective of this study was to compare the three different sampling methods for enumeration and monitoring of bacteria on broiler carcasses. Total viable counts, Pseudomonas spp., lactic acid bacteria, Brochothrix thermosphacta and Enterobacteriaceae recovered by each sampling method were enumerated using the pour plate technique. Rinsing and excision recovered a similar level (P > 0.05) of the total viable counts, whereas swabbing yielded a lower level (P < 0.05). For Pseudomonas spp., lactic acid bacteria and B. thermosphacta, rinsing recovered the highest counts, followed by excision and finally the swabbing. There was no significant difference (P > 0.05) to detect Enterobacteriaceae by the three methods. Polymerase chain reaction–denaturing gradient gel electrophoresis (PCR‐DGGE) was used to monitor bacterial constituents. Compared with rinsing, the dice coefficient was 69.2% for excision and 32.3% for swabbing. The results revealed that great differences existed among the sensitivity of microorganism detection by the three methods, rinsing > excision > swabbing. Considering the bacterial recovery and DGGE profile, rinsing seems to be the preferable sampling method for enumeration and monitoring of bacteria on broiler carcasses whereas swabbing is poor. PRACTICAL APPLICATIONS This work compared the efficiency of three sampling methods (excision, swabbing and rinsing) to evaluate bacteria on broilers using culture‐dependent and culture‐independent methods. The results indicate that whole carcass rinse would be a preferable sampling method to monitor the bacteria on broiler carcasses, especially using the culture‐independent method.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".