Effect of temperature and <scp>pH</scp> on postmortem color development of porcine M. longissimus dorsi and M. semimembranosus
Bibliographic record
Abstract
BACKGROUND: Purchasing pork that is boned within 1 h postmortem and not aged is customary in China, and final pork color would not be fully realized. The relationship between early postmortem, pre-rigor meat color and 24 h postmortem, post-rigor pork color was investigated and related to the rate of pH and temperature decline within the longissimus dorsi (LD) and the semimembranosus (SM) muscles of pork carcasses. Muscle color, pH and temperature were measured at 45 min and at 3, 9, 15 and 24 h postmortem in carcasses of F₂ White Duroc and Chinese Erhualian pigs. RESULTS: Pork color at 45 min postmortem was not indicative of that at 24 h postmortem in LD and SM, although muscle pH values and temperature at 45 min postmortem were significantly correlated with the LD and SM ultimate color. High muscle pH was associated with decreased L*, whereas high muscle temperature increased L*. Muscle pH and temperature had little effect on a* and b* in LD and color evolution in SM. CONCLUSIONS: Results indicated that meat color inspected shortly after slaughter does not reflect post-rigor meat quality.
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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".