Soft Perches in an Aviary System Reduce Incidence of Keel Bone Damage in Laying Hens
Bibliographic record
Abstract
Keel bone fractures and deviations are one of the major welfare and health issues in commercial laying hens. In non-cage housing systems like aviaries, falls and collisions with perches and other parts of the housing system are assumed to be one of the main causes for the high incidence of keel bone damage. The objectives of this study were to investigate the effectiveness of a soft perch material to reduce keel bone fractures and deviations in white (Dekalb White) and brown laying hens (ISA Brown) kept in an aviary system under commercial conditions. In half of 20 pens, all hard, metal perches were covered with a soft polyurethane material. Palpation of 20 hens per pen was conducted at 18, 21, 23, 30, 38, 44 and 64 weeks of age. Production data including egg laying rate, floor eggs, mortality and feed consumption were collected over the whole laying period. Feather condition and body mass was assessed twice per laying period. The results revealed that pens with soft perches had a reduced number of keel bone fractures and deviations. Also, an interaction between hybrid and age indicated that the ISA hybrid had more fractured keel bones and fewer non-damaged keel bones compared with the DW hybrid at 18 weeks of age, a response that was reversed at the end of the experiment. This is the first study providing evidence for the effectiveness of a soft perch material within a commercial setting. Due to its compressible material soft perches are likely to absorb kinetic energy occurring during collisions and increase the spread of pressure on the keel bone during perching, providing a mechanism to reduce keel bone fractures and deviations, respectively. In combination with genetic selection for more resilient bones and new housing design, perch material is a promising tool to reduce keel bone damage in commercial systems.
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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 | 0.000 |
| 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) | 0.001 | 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".