Effects of pre-slaughter administration of oral calcium gel to beef cattle on tenderness
Bibliographic record
Abstract
The effects of pre-harvest administration of oral calcium gel to beef cattle on longissimus pH, calpain activity, and tenderness were examined. Thirty steers (539 kg) were randomly assigned to one of the following treatments: control (CON, n = 15) and calcium gel administered (CA, n = 15). At 3 to 6 h prior to slaughter, the calcium gel steers were dosed via a rumen tube with calcium propionate (150 g of calcium and 630 g propionate) and propylene glycol (600 g) in a liquid suspension. Calcium gel administration prior to slaughter increased (P < 0.05) m-calpain and m-calpain activity (caseinolytic activity per gram of muscle) with no change (P >0.05) in calpastatin activity. Total mineral (%) and calcium (mg g–1) contents of the longissimus muscle were greater (P <0.05) for CA than CON. Steaks from CA steers had Warner-Bratzler shear force (WBS) values lower (P < 0.05) than CON after4 and 7 d of aging. No differences (P > 0.05) were noted in WBS values at days 2, 14, or 28 of aging between the treatments. Sensory panel ratings were higher (P < 0.05) for tenderness of CA steaks than CON after aging for 7 d, and juiciness and flavor ratings were similar (P > 0.05). Pre-harvest calcium gel administration elevated longissimus muscle calcium content, increased calpain activity, and accelerated postmortem aging to improve tenderness. Key words: Beef, calcium, tenderness, calpain
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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) | 0.001 | 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".