In pursuit of a better broiler: carcass traits and muscle myopathies in conventional and slower-growing strains of broiler chickens
Bibliographic record
Abstract
Selection for accelerated growth rate and high breast yield in broiler chickens have been associated with an increase in myopathies, including wooden breast (WB) and white striping (WS). To investigate effects of growth rate on carcass traits and incidence of myopathies, 14 strains were evaluated, encompassing 2 conventional (CONV; strains B and C: ADG0-48 > 60 g/d) and 12 slower-growing (SL) strains. The latter were categorized based on growth rate: FAST (strains F, G, I and M; ADG0-62=53–55 g/d), MOD (strains E, H, O and S; ADG0-62=50-51 g/d), and SLOW (strains D, J, K and N; ADG0-62<50 g/d). In a randomized incomplete block design, 7,216 mixed-sex birds were equally allocated into 164 pens (44 birds/pen; 30 kg/m2), with each strain represented in 8 to 12 pens over 2 to 3 production cycles. From each pen, 4 males and 4 females were processed at 2 Target Weights (TWs) based on their expected time to reach 2.1 kg BW (TW 1: 34 d for CONV; 48 d for SL strains) and 3.2 kg BW (TW 2: 48 d for CONV; 62 d for SL strains). Weights and yields for the carcass, breast, drumsticks, thighs, and wings were obtained; breast fillets were assessed to determine the presence and severity of WB and WS. At both TWs, breast yield was higher as growth rate increased (P < 0.001), with CONV having greater breast yield than other categories. Strain F had the greatest breast yield at both TWs (P < 0.001) within the FAST category. At TW 2, CONV had the greatest incidence of WB and WS (P < 0.001). However, within FAST, strain F had the greatest incidence of myopathies (P < 0.001) at both TWs, exhibiting values as high or as greater than CONV birds. The incidence of WB and WS in strains with differing growth rates but high breast meat yield suggests that the latter may play a major role in the occurrence of these myopathies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".