Simulated transport of well- and poor-feathered brown-strain end-of-cycle hens and the impact on stress physiology, behavior, and meat quality
Bibliographic record
Abstract
Transportation of poultry is stressful, especially for end-of-cycle hens (EOCH) experiencing metabolic stress. The aim of this study was to evaluate the effects of simulated transport on well- and poor-feathered brown-strain EOCH. The study (5 × 3 × 2 factorial arrangement) consisted of 5 temperature and relative humidity (RH) combinations applied directly at crate level (−10°C uncontrolled RH [−10], +21°C 30%RH [21/30], +21°C 80%RH [21/80], +30°C 30%RH [30/30], or +30°C 80%RH [30/80]), 3 durations (4, 8, or 12 h), and 2 feather covers (well [WF] or poor [PF]). Hens (n = 540) from 3 commercial farms were housed for a 3- to 5-d adaptation period, then feed was withdrawn before treatment exposure (crate density 54.5 kg/m2). Data collected included chamber conditions, feather condition score, behavior, blood physiology, core body temperature, mortality, and meat quality. Data were analyzed (randomized complete block design) using ANOVA; significance declared at P ≤ 0.05. Time spent performing thermoregulatory behaviors increased for hot (30/30 and 30/80) and cold (−10) treatments. Mortality only occurred in hens exposed to −10 and increased with longer duration. Cold exposure impacted meat quality, resulting in higher thigh pH and lower L∗ (lightness) and b∗ (yellowness). Prolonged exposure duration resulted in dehydration, indicated by blood physiology (hematocrit and hemoglobin) and live shrink. PF hens struggled with thermoregulation in −10, while WF hens struggled in 30/30 and 30/80. These results demonstrate that EOCH exposed at crate level to hot (+30) conditions experience thermal stress, while hens exposed to cold (−10) are unable to cope, compromising welfare and meat quality.
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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 | 0.002 |
| 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".