Impact of combined xylanase and β-glucanase enzymes on digesta transit time, short-chain fatty acids, and caecal thermal profile of broilers fed corn–soy-based diets
Bibliographic record
Abstract
A study was conducted to evaluate the effects of including a xylanase + β-glucanase enzyme product in corn–soy-based diets on performance, caecal short-chain fatty acids and thermal profile, ileal digestibility, and intestinal kinetics of broiler chickens. A total of 744 male day-old chicks were randomly allotted to 24 floor pens and distributed in a 2 × 2 factorial arrangement with low or standard energy level × without or with 100 g of the enzyme per ton of feed. Enzyme supplementation improved bodyweight gain from 1 to 21 d (P < 0.05). An increased caecal concentration of acetic acid was observed when the enzyme was added to the low-energy diet (P < 0.05). The pH of the caecal content was reduced (P < 0.01), and the caecal temperature was increased by low-energy diets (P < 0.05). The apparent ileal digestibility of energy was improved by the enzyme (P < 0.01). The addition of the enzyme increased the mean retention time in the distal ileum (P < 0.05). In summary, the addition of a xylanase + β-glucanase enzyme product in corn-based diets increases the retention time of digesta in the distal ileum and the caecal acetic acid concentration, improves ileal digestibility of energy and performance from 1 to 21 d in broiler chickens fed corn–soy-based diets.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".