Very fast chilling of beef carcasses
Bibliographic record
Abstract
To determine if very fast carcass chilling (VFC; approximately –1°C within 5 h postmortem) of beef carcasses could be achieved through blast chilling, 96 carcasses of an estimated Canada 1 grade were used. The right side of each carcass was assigned to blast chilling conditions of either –20°C (48 sides) or –35°C (48 sides) while the left side was assigned to control chilling conditions (2°C for 24 h; 96 sides). Wind speed in the blast chill tunnel was 2.32 m s–1. Within each blast chill temperature, 12 blast-chilled sides were removed from the tunnel at each of four times (3, 5, 7 or 10 h) and chilled for the remainder of the 24-h period at 2°C. VFC conditions were not achieved in the deep hip region under any chilling regime, but were reached in the longissimus thoracis (LT) by approximately 6.5 h under rigorous chilling regimes (7 or 10 h of blast chilling at –35°C). After 6 d aging, LT muscles from sides blast chilled at –35°C for 10 h were more tender (22.4 vs. 29.3 N cm–2: P = 0.004) than those from their respective control sides. When these shear forces were categorized into tender (≤ 19.4 N cm–2), probably tender (> 19.4 ≤ 27.2 N cm–2), probably tough (> 27.2 = 33.2 N cm–2) and tough (> 33.2 N cm–2) categories, there was a higher proportion of tender (25.0 vs. 0.0%) and probably tender (58.33 vs. 33.33%) shears in the –35° C blast-chilled sides than in the control sides (P =0.06). However, these differences disappeared with extended aging to 21 d. Hence, the VFC advantage would be a reduction in the necessary aging time to achieve an acceptable product. The extreme chilling regime also resulted in significant reductions in cooler shrink, a slower rate of pH decline, an increased perception of marbling, darker meat colour and increased drip losses at retail. Further study of the mechanism of VFC tenderization is warranted. Key words: Beef carcasses, rapid chilling, beef quality, tenderness
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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 | 0.001 |
| 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".