491 Production factors affecting the contribution of collagen to meat toughness
Bibliographic record
Abstract
The progression of mature collagen crosslink formation in bovine intramuscular connective tissue (IMCT) is affected by growth promotants use and cattle age. One-way analysis of variance of data from gluteus medius (GM) and semitendinosus (ST) muscles from 14 calf-fed (about 14 months) and 14 yearling-fed (about 20 months) steers, and 12 mature cows (> 3 years) of Charolais Red-Angus or Hereford-Aberdeen Angus genetics indicated collagen heat solubility was significantly (P < 0.05) reduced in both muscles from mature cows compared to calf- and yearling-fed steers, and that total collagen increased with cattle age in the GM only. Pyridinoline (Pyr) concentrations and densities increased in the IMCT of GM of steers to the same levels of those of cow IMCT by the yearling-fed stage while Ehrlich Chromogen (EC) concentration was lowest in cows regardless of muscle. Mean thermal denaturation temperatures (Tmax, °C) for IMCT were similar for calf- and yearling-fed steers regardless of muscle, but were significantly increased for both muscles from cows. Pearson correlations showed that GM WBSF was unrelated to collagen characteristics, but ST WBSF was negatively correlated to EC concentration (mol EC/g raw meat)(r = -0.41, P 0.01) and density (mol EC/mol collagen)(r = -0.32, P 0.05), and collagen solubility (%, r = -0.48, P 0.01), and positively correlated to IMCT Tmax (r = 0.63, P 0.0001) and enthalpy (kJ/mol)(r = 0.58, P 0.0001). Tmax was positively correlated to Pyr density (mol Pyr/mol collagen, r = 0.50 and 0.53, P 0.001, GM and ST, respectively) and negatively correlated to EC density (mol EC/mol collagen, r = -0.52 and -0.70, P 0.0001, GM and ST respectively). These results suggested that Pyr contributes to WBSF of high IMCT locomotory muscles such as the ST more than to that of postural muscles such as the GM.
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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".