Effect of Medicinal Plant By-products Supplementation to Total Mixed Ration on Growth Performance, Carcass Characteristics and Economic Efficacy in the Late Fattening Period of Hanwoo Steers
Bibliographic record
Abstract
This study was conducted to evaluate the effect of medicinal plant by-products (MPB) supplementation to a total mixed ration (TMR) on growth, carcass characteristics and economic efficacy in the late fattening period of Hanwoo steers. Twenty seven steers (body weight [BW], 573±57 kg) were assigned to 3 treatment groups so that each treatment based on BW contained 9 animals. All groups received ad libitum TMR throughout the feeding trial until slaughter (from 24 to 30 months of age) and treatments were as follows: control, 1,000 g/kg TMR; treatment 1 (T1), 970 g/kg TMR and 30 g/kg MPB; treatment 2 (T2), 950 g/kg TMR and 50 g/kg MPB. Initial and final BW were not different among treatments. Resultant data were analyzed using general linear models of SAS. Average daily gain and feed efficiency were higher (p<0.05) for T1 than control, but there was no difference between control and T2. Plasma albumin showed low-, intermediate- and high-level (p<0.05) for control, T1 and T2, whereas non-esterified fatty acid was high-, intermediate- and high-level (p<0.05) for control, T1 and T2, respectively. Carcass weight, carcass rate, backfat thickness and rib eye muscle area were not affected by MPB supplementation, whereas quality and yield grades were highest (p<0.05) for T1 and T2, respectively. Daily feed costs were decreased by 0.5% and 0.8% and carcass prices were increased by 18.1% and 7.6% for T1 and T2 compared to control, resulting from substituting TMR with 30 and 50 g/kg MPB, respectively. In conclusion, the substituting TMR by 30 g/kg MPB may be a potential feed supplement approach to improve economic efficacy in the late fattening period of Hanwoo steers.
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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".