Changes in tenderness and cathepsins activity during post mortem ageing of yak meat
Bibliographic record
Abstract
Tian, J.-C., Han, L., Yu, Q.-L., Shi, X.-X. and Wang, W.-T. 2013. Changes in tenderness and cathepsins activity during post mortem ageing of yak meat. Can. J. Anim. Sci. 93: 321–328. Very little research has been conducted on yak meat tenderization. In this study we investigated the changes in physical characteristics (e.g., pH, water-holding capacity, texture profile analysis, shear force) and cathepsins L, B and H activities in the tenderization process. These traits were quantified in longissimus dorsi muscle from 10 yaks during 192 h post mortem. Samples were aged at 4°C for 0, 12, 24, 36, 48, 72, 120, 168 and 192 h. pH decreased (P<0.05) from 6.84 to 5.54 in the first 72 h and did not change significantly during the next 120 h. Water-holding capacity showed an overall decreasing trend (P<0.05). Shear force decreased? (P<0.05) and myofibrillar fragmentation index increased? (P<0.05), and it was concluded that ageing can improve yak meat tenderness. Our results on texture profile analysis showed a decrease in hardness (P<0.05), springiness (P<0.05) and chewiness (P<0.05), reflected in a progressive softening during ageing (P<0.05). Cathepsins L, B and H activity showed an increased trend (P<0.05). In conclusion, our results show potential roles for cathepsins L, B and H in the tenderization process. This study provides further insights into the tenderization process of yak meat, which may ultimately be used for the advantageous manipulation of the process.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".