Genetic selection to increase bone strength affects prevalence of keel bone damage and egg parameters in commercially housed laying hens
Bibliographic record
Abstract
The prevalence of keel bone damage as well as external egg parameters of 2 pure lines divergently selected for high (H) and low (L) bone strength were investigated in 2 aviary systems under commercial conditions. A standard LSL hybrid was used as a reference group. Birds were kept mixed per genetic line (77 hens of the H and L line and 201 or 206 hens of the LSL line, respectively, per pen) in 8 pens of 2 aviary systems differing in design. Keel bone status and body mass of 20 focal hens per line and pen were assessed at 17, 18, 23, 30, 36, 43, 52, and 63 wk of age. External egg parameters (i.e., egg mass, eggshell breaking strength, thickness, and mass) were measured using 10 eggs per line at both 38 and 57 wk of age. Body parameters (i.e. tarsus and third primary wing feather length to calculate index of wing loading) were recorded at 38 wk of age and mortality per genetic line throughout the laying cycle. Bone mineral density (BMD) of 15 keel bones per genetic line was measured after slaughter to confirm assignment of the experimental lines. We found a greater BMD in the H compared with the L and LSL lines. Fewer keel bone fractures and deviations, a poorer external egg quality, as well as a lower index of wing loading were found in the H compared with the L line. Mortality was lower and production parameters (e.g., laying performance) were higher in the LSL line compared with the 2 experimental lines. Aviary design affected prevalence of keel bone damage, body mass, and mortality. We conclude that selection of specific bone traits associated with bone strength as well as the related differences in body morphology (i.e., lower index of wing loading) have potential to reduce keel bone damage in commercial settings. Also, the housing environment (i.e., aviary design) may have additive effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".