Comparative impact of conventional and alternative gut health management programs on growth performance and breast meat quality in broiler chickens raised in commercial and research settings
Bibliographic record
Abstract
Consumer and regulatory pressure continue to drive the poultry industry to reduce the use of antibiotics due to concerns surrounding antimicrobial resistance in human medicine. Consequently, gut health management programs have been developed to facilitate production of chicken with less reliance on antimicrobials. The objective of this study was to evaluate whether conventional and alternative gut health programs paired with antibiotic removal were impacting growth performance and breast meat quality in broiler chickens reared under commercial (study 1) and research (study 2) settings. A total of 1,159,908 broilers were reared on one of 3 gut health management programs: 1) conventional (CON), where some medically important antibiotics (MIA) are allowed, 2) raised without MIA (RWMIA), and 3) raised without antibiotics (RWA). Studies showed no statistical differences for body weight, feed intake, feed conversion ratio (FCR), or total mortalities among birds reared on the three programs. In commercial settings, total condemnations were significantly lower in birds reared on the CON program compared to birds reared without MIA. Breast weight (g/100 g BW) was lower in birds on the RWA program under commercial conditions, however the same effect was not observed under research conditions. The RWMIA program had the highest breast weight in both studies and demonstrated the lowest incidence of breast meat myopathies in research settings. These results suggest that growth performance was similar among programs and that the strategies employed in the absence of antibiotics are effective in maintaining overall performance. Differences in breast meat attributes among programs warrants further study.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".