PSIII-A-18 The Effects of Feeding Finishing Cattle Benzoic Acid and/or Live Active Yeast (Saccharomyces Cerevisiae) on Meat Quality
Bibliographic record
Abstract
Abstract In a randomized complete block design, 59 Angus-cross finishing steers were used to evaluate the effects of benzoic acid, active dry Saccharomyces cerevisiae, or a combination of both when supplemented in a high-grain finishing diet on meat quality and sensory evaluation of longissimus steaks. Steers were fed a high-moisture corn-based finishing diet for 106 d containing: no supplementation (CON), 0.5% benzoic acid (ACD), 3 g/head/d active dry S. cerevisiae (YST), or both (0.5% benzoic acid and 3 g/head/d S. cerevisiae (AY)). Cattle were humanely slaughtered at a commercial facility where 54 rib sections (CON; n=15, ACD; n=14, YST; n=15, and AY; n=11) were retrieved and used for evaluation of meat quality and trained sensory parameters. Statistical analysis was completed using PROC GLIMMIX of SAS. Longissimus pH, proximate composition, shear force, and cooking loss did not differ between treatments (P ≥ 0.10). Although no differences in lipid oxidation was detected at the beginning of the retail display (d 0), lipid oxidation levels were greater (P = 0.02) in CON vs. AY steaks following 12 days of retail display. Some colour parameters differed (P ≤ 0.04) among treatments on days 11 (L*) and 12 (a*, L*, and discolouration) of the retail display. Although dietary treatment did not impact fatty acid profiles for longissimus muscle, n-6:n-3 polyunsaturated fatty acids ratios were greater in CON and YST than in ACD longissimus (P = 0.007). Steaks from Combination (AY) supplemented steers were chewier than steaks from steers only supplemented with benzoic acid, while juiciness, tenderness, and flavour were not impacted by supplementation. These results suggest that supplementation with benzoic acid and(or) yeast does not have a substantial impact on meat quality or sensory traits.
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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) | 0.003 | 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".