PSX-B-8 Effect of supplementing red osier dogwood extract on in vitro gas production, feed digestibility and fermentation characteristics of high-forage diet
Bibliographic record
Abstract
Abstract Red osier dogwood (ROD) is native shrub plant in Canada and rich in bioactive compounds. The objective of this study was to evaluate the effects of ROD extract supplementation in a high-forage (HF) diet on gas production (GP), dry matter (DM) disappearance (DMD) and fermentation characteristics in batch cultures with varying media pH. The study was a completely randomized design with 4 levels of ROD extract (0, 1, 3 and 5% of substrate) × 2 media pH (5.8 and 6.5) factorial arrangement. The study was conducted in three replicate experiments. Substrate contained 60% barley silage and 40% barley concentrate (DM basis). Inoculum was obtained from 2 ruminally fistulated beef heifers offered the HF diet. Substrate (0.5 g DM) ground (1 mm) was incubated for 48 h in a culture bottle. Data were analyzed using Mixed procedure of SAS with fixed effects of treatments and random effect of experiment. There was no interaction between media pH and level of ROD on GP, DMD and fermentation characteristics. Increased media pH (5.8 vs. 6.5) increased (P < 0.01) GP (averaged 164 vs. 275 ml/g substrate), DMD (50.6 vs. 60.6%), and total VFA production (63 vs. 71 mM). Increasing ROD extract levels did not affect GP but linearly (P = 0.05) decreased DMD from 62.1 to 58.9% at pH 6.5. Although total VFA production was not affected, increasing ROD extract linearly (P < 0.01) increased the proportion of acetate (47.9 to 49.7%) and propionate (20.5 to 22.3%) at pH 5.8; whereas at pH 6.5, acetate to propionate ratio quadratically (P = 0.04) changed to be lower with 3% ROD extract (2.08) than other treatments (2.21). These results indicated that supplementation of HF diet with ROD extract may improve fibre digestion at low media pH, and improve fermentation efficiency at high media pH.
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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".