314 Steer Production Performance and Enteric gas Emissions Associated with Free-Choice Mineral Supplement Infused with Varying Levels of Garlic Powder
Bibliographic record
Abstract
Abstract The addition of phytogenics such as garlic powder into beef mineral supplements is motivated by the potential for increased mineral intake and associated insectifugal outcomes. This 3-yr study compared feed and mineral intake and performance in crossbred beef steers that received free-choice mineral supplements infused with or without garlic powder (5% inclusion). The study design was a randomized complete block design where each steer (n=180) was randomly assigned to either a 5%GP or 0%GP treatment group, balancing for breed composition and initial body weight. Different garlic brands (5%GPLO, 5%GPSE, and 5%GPWL) were also assessed during the third year of study. Individual feed and mineral supplement intakes were monitored using automatic feeding units from different bunks ad libitum. Enteric gas fluxes (CH4, CO2, O2, and H2) were also measured with an automated head-chamber emission monitoring system. Over 3 yr, there was no difference (P > 0.05) in dry matter intake, average daily gain, and gain to feed ratio between 5%GP and 0%GP groups, but supplement intake was greater (P < 0.05) for 5%GP (206 gd-1) compared with 0%GP (152 gd-1) treatment. Comparing all brands in third year showed differences in mineral consumption where 5%GPLO (223 gd-1) had greatest (P < 0.0001) supplement intake, but there was no difference (P > 0.05) among 5%GPSE (133 gd-1), 5%GPWL (103 gd-1) and 0%GP (145 gd-1). Enteric gas fluxes did not differ between 5%GPLO and 0%GP for CH4 (129 gd-1, 119 gd-1; P = 0.69), CO2 (7912 gd-1, 7351 gd-1; P = 0.31), O2 (5394 gd-1, 4816 gd-1; P = 0.15) and H2 (0.84 gd-1, 0.67 gd-1; P = 0.42). Results suggest that infusing garlic at 5% increased supplement intake in feedlot cattle but had no effect on growth or enteric gas fluxes. Differences in the brands evaluated here may be related to the shelf/storage age of the products and the bioactive compound profiles.
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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 | 0.000 |
| 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".