Impact of diet type and xylanase supplementation on the ileal digestibility of nutrients, and growth performance in growing-finishing pigs
Bibliographic record
Abstract
In the experiment, six pigs fitted with a T-cannula at the distal ileum were fed six diets in a 6 × 6 Latin square design. Treatments were corn-soybean meal diet (CS), diet containing wheat by-products (WBP), and diet containing corn distillers dried grains with solubles and canola meal (DDCM) without or with xylanase (X) supplementation (CS-X, WBP-X, and DDCM-X). The WBP and DDCM diets had higher apparent ileal digestibility (AID) of lipids and acid detergent fiber (ADF) (P < 0.05) than CS diets. A xylanase × diet interaction was observed for the AID of neutral detergent fiber (NDF) (P < 0.05) showing larger impact of xylanase in WBP than in the other diets. Using similar dietary treatments except for CS-X, growth and body composition of the sixty males (83.0 kg) at the end of the 28-day growing phase showed that pig fed the CS diet had greater average daily feed intake (ADFI) (P = 0.004) and average daily gain (ADG) (P = 0.014) for period 0–14 d but not from 15–28 d. Overall performance (0–28 d) showed higher ADFI (9.5%; P = 0.015) in CS but no difference was observed for ADG and gain to feed ratio (G:F). These results showed that diets containing a high proportion of by-products can give equivalent performance to a CS diet and that adding xylanase for this short period had limited effects.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 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".