Investigating factors affecting the incidence of tibial dyschondroplasia in meat-type poultry: A meta-analysis
Bibliographic record
Abstract
Tibial Dyschondroplasia (TD) is the accumulation of growth plate cartilage in the proximal end of the tibiotarsus bone and has persisted as a major skeletal disorder in the poultry industry, continuing to negatively impact both profitability and animal welfare. Studies have reported potential effects of genetic selection, nutrition, and body weight on TD incidence, but these relationships vary between studies. Therefore, the objective of this study was to conduct a meta-analysis, to identify factors contributing to TD incidence, with 41 publications meeting the inclusion criteria. It was predicted that variables such as body weight (kg), sex, species, age (weeks), dietary calcium to phosphorus ratio (Ca:P), feed conversion ratio (FCR), and the decade of publication would have an impact on the incidence of TD. Linear mixed models were used to assess the effect of independent variables to predict TD incidence while including study as a random effect. Results indicated that increased body weight (0.13 ± 0.028; P < 0.0001) was associated with a higher TD incidence. TD incidence varied by species (P < 0.0001), with a greater effect observed in turkeys (0.16 ± 0.027; P < 0.0001) compared to broilers (0.10 ± 0.140; P = 0.475). In broilers, TD incidence decreased with age (P < 0.0001), with a slightly steeper decline in females (-0.28 ± 0.066; P < 0.0001) compared to males. The decade of study (70s-80 s, 90 s, and 2000s-2020s) was associated with TD incidence (P = 0.041), with incidence at its lowest in the 2000s-2020s (0.19 ± 0.044; P < 0.0001), and highest in the 70s-80s (0.37 ± 0.052; P = 0.028). An increase in the Ca:P ratio corresponded to a larger decline in TD incidence in broilers (-0.99 ± 0.158; P < 0.0001) compared to turkeys (-0.57 ± 0.217; P = 0.011). However, improved FCR (-1.37 ± 0.345; P < 0.0001) was correlated with increased TD incidence. To conclude, this meta-analysis identified factors related to TD incidence and emphasized the need for tailored management strategies to mitigate impact.
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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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.042 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".