MUSCLE FIBER TYPE AND THE OCCURRENCE OF PALE, SOFT, EXUDATIVE PORK
Bibliographic record
Abstract
ABSTRACT Pale, soft, exudative (PSE) pork is a problem in the meat industry. Previous studies have shown that PSE pork results from accelerated postmortem muscle metabolism, perhaps related to a preponderance of type 2b muscle fibers. The present study further elucidates the role of fiber type complement in PSE pork. Immunocytochemical and histochemical techniques were used to characterize fibers as type 1, 2a, 2×or 2b in PSE and normal longissimus muscle. The number, size and percent of total muscle cross‐sectional area of each fiber type were determined. No significant differences in size, number or percent of total area of any fiber type were found between PSE and normal pork. This suggests that the relative abundance of any given fiber type is not wholly responsible for the occurrence of PSE pork. Consistent with PSE water loss, however, the fibers from PSE pork were on average significantly smaller than those from normal pork. PRACTICAL APPLICATIONS Pale, soft and exudative (PSE) meat continues to be a major problem for the pork industry. The present study provides important insights into the role of muscle fiber type in this condition. Unlike many previous studies, we examine the presence of all four primary fiber types (1, 2a, 2× and 2b) in normal and PSE pork. We determine that the relative abundance of any given fiber type cannot be entirely responsible for the occurrence of PSE pork. Also the smaller average size of fibers from PSE pork is consistent with water loss from the tissue, and has the potential to be used as an additional criterion for identifying PSE pork.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".