76 Effects of replacing monensin and tylosin in finishing cattle diets with essential oils and/or benzoic acid on growth performance and carcass characteristics
Bibliographic record
Abstract
Abstract This study examined the effects of replacing monensin and tylosin with essential oils and/or benzoic acid in finishing cattle diets on growth performance, feed efficiency, and carcass characteristics. Crossbred steers (n = 68; BW = 539 ± 4 kg) were blocked by starting weight into three blocks and were assigned to 1 of 5 finishing diets: no additional supplement (CON), monensin/tylosin (M/T), essential oils (EO), benzoic acid (BA), or a combination of essential oils and benzoic acid (COMBO). Steers were housed with two dietary treatments represented in seven pens, while an eighth pen only housed steers fed the CON diet. Individual animal feed intake was collected using an Insentec feeding system, so steer was the experimental unit for all analyses. Data were analyzed using a randomized complete block design with fixed effect of treatment and random effect of block. Final weight, average daily gain, and dry matter intake were similar (P > 0.12) among treatments. Gain to feed ratio differed (P = 0.05) among treatments, specifically steers fed the M/T diet had greater G:F compared with steers fed CON, EO, and COMBO diets. For carcass characteristics, there were no significant treatment differences in hot carcass weight (P = 0.19), dressing percentage (P = 0.62), ribeye area (P = 0.49), fat thickness (P = 0.84), calculated yield grade (P = 0.91), marbling score (P = 0.07), and yield grade (P = 0.43). Quality grade differed (P = 0.05) among treatments, with steers fed the EO diet having a lower quality grade than all other dietary treatments. Overall, steers supplemented with essential oils and(or) benzoic acid had similar gain, feed intake, and carcass parameters as steers fed CON, while steers fed M/T had slightly improved feed efficiency compared to all other treatments.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".