98 Effect of engineered biocarbon on rumen fermentation, nutrient digestibility, methane emissions, and rumen microbiota in beef heifers
Bibliographic record
Abstract
Abstract The objective of this study was to examine the effect of engineered biocarbon (EB) on rumen fermentation, apparent total tract digestibility, methane (CH4) emissions and the rumen and fecal microbiome of Angus × Hereford heifers fed a barley silage-based diet. The experiment was a replicated 4 × 4 Latin square using 8 ruminally cannulated heifers (565 ± 35 kg initial BW). The basal diet contained 60% barley silage, 35% barley grain and 5% mineral supplement with EB added at 0% (control), 0.5%, 1.0%, or 2.0% (DM basis). Each period was 28-d consisting of 14-d adaptation and 14-d of measurements. Samples for profiling of the microbiome in rumen liquid, solids and feces were collected on d-15 before feeding. Rumen samples for fermentation characterization were taken at 0, 3, 6, and 12-h post feeding. Total collection of urine and feces was conducted from d-18 to 22. Heifers were housed in open-circuit respiratory chambers on d-26 to 28 to estimate CH4 emissions. Ruminal pH was recorded at 1-min intervals during CH4 measurements using indwelling pH loggers. Data were analyzed with the fixed effects of dietary treatment and random effects of square, heifer within square and period. Dry matter intake was similar across treatments (P = 0.21). NH3-N concentration and protozoa counts responded quadratically (P = 0.01) to EB. Minimum pH was increased (P = 0.04), and variation of pH was decreased (P = 0.03) by 2.0% EB. Total tract digestibility, N balance and CH4 production were not affected (P ≥ 0.17) by EB. EB affected the relative abundance of Fibrobacter (P = 0.05), Spirochaetaes (P = 0.01), Verrucomicrobia (P = 0.02), Tenericutes (P = 0.01), and Elusimicrobia (P = 0.02). Results suggest that at the examined concentrations, EB was ineffective at decreasing enteric CH4 emissions, however it altered the rumen microbiome.
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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".