Meta-analysis to predict the effects of temperature stress on meat quality of poultry
Bibliographic record
Abstract
Temperature stress (TS) is a significant issue in poultry production, which has implications for animal health and welfare, productivity, and industry profitability. Temperature stress, including both hot (heat stress) and cold conditions (cold stress), is associated with increased incidence of meat quality defects such as pale, soft, and exudative (PSE) and dark, firm, and dry (DFD) meat costing poultry industries millions of dollars annually. A meta-analysis was conducted to determine the effect of ambient TS on meat quality parameters of poultry. Forty-eight publications which met specific criteria for inclusion were identified through a systematic literature review. Temperature stress was defined by extracting 2 descriptors for each treatment mean from the chosen studies: (1) temperature imposed for the experimental treatments (°C) and duration of temperature exposure. Treatment duration was categorized for analysis into acute (≤24 h) or chronic (>24 h) treatments. Meat quality parameters considered were color (L*-a*-b* scheme), pH (initial and ultimate), drip loss, cooking loss, and shear force. Linear mixed model analysis, including study as a random effect, was used to determine the effect of treatment temperature and duration on meat quality. Model evaluation was conducted by performing a k-fold cross-validation to estimate test error, and via assessment of the root mean square prediction error (RMSPE), and concordance correlation coefficient (CCC). Across both acute and chronic durations, treatment temperature was found to have a significant effect on all studied meat quality parameters. As treatment temperature increased, meat demonstrated characteristics of PSE meat and, as temperature decreased, meat demonstrated characteristics of DFD meat. The interaction between treatment temperature and duration was significant for most traits, however, the relative impact of treatment duration on the studied traits was inconsistent. Acute TS had a larger effect than chronic TS on ultimate pH, and chronic stress had a more considerable impact on color traits (L* and a*). This meta-analysis quantifies the effect of ambient TS on poultry meat quality. However, quantitative effects were generally small, and therefore may or may not be of practical significance from a processing perspective.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.053 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".