Effect of timing of postweaning xylanase supplementation on growth performance, nutrient digestibility, and fecal microbial composition in weanling pigs
Bibliographic record
Abstract
Effect of timing of xylanase supplementation to weanling pigs and its effect on growth performance, nutrient digestibility, and fecal microbiota was investigated. A total of 128 weanling pigs [(Hampshire × Duroc) × (Yorkshire × Landrace); 6.2 ± 0.6 kg body weight (BW); weaning age: 21 d] were assigned to four treatments, with eight replicate pens and four pigs per pen. Treatments were a combination of two dietary treatments (without or with xylanase) in two periods; (period 1, days 0–14) and period 2 (days 14–42): xylanase–xylanase, xylanase–control, control–xylanase, and control–control. Fecal microbiota diversity and apparent total tract digestibility (ATTD) were determined. From days 0–14, pigs had lower (P < 0.01) BW, average daily gain (ADG), and feed efficiency when xylanase was included in the diets. The final BW (P < 0.05) and overall ADG (P < 0.02) at day 42 were greater when xylanase was supplemented from day 14 compared with supplementation from day 0. The apparent ileal digestibility and ATTD of dry matter, gross energy, nitrogen, and phosphorus were increased (P < 0.05) by xylanase. Xylanase significantly decreased (P < 0.05) the relative abundance of Veillonella spp. and tended (P = 0.08) to decrease the relative abundance of Megasphaera spp. in period 2 compared with the non-supplemented group.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".