Effect of acute cold exposure, age, sex, and lairage on broiler breast meat quality
Bibliographic record
Abstract
The effect of acute cold exposure on bird physiology, muscle metabolites, and meat quality was assessed in 360 male and female broilers at 5 and 6 wk of age, exposed for 3 h to temperature ranges of -18 to -4°C and a control of +20°C, by using a simulated transport system followed by 0 or 2 h of lairage. Core body temperature (CBT) was recorded, and the microclimate temperature and RH surrounding individual birds were monitored. Birds were classified based on the temperature in their immediate surroundings. Exposure to temperatures below 0°C resulted in a decrease (P < 0.05) in blood glucose and an increase in live shrink. During the 3 h of exposure to -8°C or lower, CBT dropped substantially. Temperatures below -14°C caused lower glycolytic potential and lactate concentrations. Five-week-old birds showed darker and redder breast meat with higher ultimate pH (pH(u)), less cook loss, and higher processing cook yield at temperatures below -8°C compared with warmer temperatures and with 6-wk-old birds exposed to similar temperatures. No difference in meat quality was observed between the 2 ages at temperatures below -14°C. Males had a greater decrease in CBT and had breast meat with higher pH(u) compared with females. The 2-h lairage resulted in darker breast meat with higher pH(u) at exposure temperatures below -14°C and with higher water-binding capacity and processing cook yield at temperatures below -11°C. A high (>57%) incidence of dark, firm, and dry breast meat [pH >6.1 and L* (lightness) <46] was observed at temperatures below -14°C. A 2-h lairage resulted in an additional 20% increase in the incidence of dark, firm, and dry meat at temperatures below -8°C. Results of this study showed that older birds coped better with extreme cold conditions compared with younger birds. Furthermore, it would be beneficial to limit the length of lairage before processing after exposure to acute cold to improve bird welfare and reduce meat quality defects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".