Extended ageing time and temperature effects on quality of sub-primal cuts of boxed beef
Bibliographic record
Abstract
Most of the information indicating ageing improves tenderness has been collected on the loin and rib-eye muscles over relatively short ageing times, assuming that all muscles will react similarly. In the present study, the effect of extended ageing times on instrumental texture (56 d) and sensory characteristics (42 d) of six different beef sub-primals [striploin (SL), inside round (IR), outside round (OR), eye of round (ER), blade eye (BE) and chuck tender (CT)] was studied. The effects of two ageing temperatures (1 and 5°C) were also compared. In general, ageing increased tenderness (P < 0.05) of SL, BE, ER and CT sub-primals, although BE shear force increased after 42 d of ageing. On the other hand, ageing had no effect on IR tenderness (P > 0.05) and resulted in a decrease in tenderness of OR (P < 0.05) until day 35, with a later increase after 42 d of ageing. Increasing ageing temperature (5°C) had limited effect on tenderness, but ageing time and temperature increases led to lower flavour and higher off-flavour intensity (P < 0.05) of the studied sub-primals. These results suggest that cut-specific maximum ageing times and rigid adherence to temperature maximums would be of benefit to optimize post-slaughter processes and meat quality.Key words: Beef, ageing, tenderness, muscle
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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".