Growth performance and nutrient digestibility of weaned pigs fed corn–barley–soybean meal-based diets supplemented with a multi-enzyme blend
Bibliographic record
Abstract
A study evaluated effects of supplementing a barley–corn–soybean meal-based diet with a multi-enzyme product on growth performance and nutrient digestibility of weaned pigs. A total of 122 pigs (initial body weight of 5.2 kg ± 0.98) were group-housed in 24 pens of 5–6 barrows or 6–7 gilts per pen. Pigs were fed two diets: basal diet without or with a multi-enzyme blend that supplied 4000 U of xylanase, 150 U of β-glucanase, 1000 U of amylase, and 500 U of protease per kilogram of diet. The diets were fed for 6 weeks in two phases: Phase 1 for the first 3 weeks and Phase 2 for the last 3 weeks. Growth performance was determined by phase, whereas apparent total tract digestibility of nutrients was determined at the end of the experiment. Multi-enzyme did not affect body weight gain, but improved ( P < 0.05) gain-to-feed ratio by 5.4% for the entire study period. Multi-enzyme increased ( P < 0.05) apparent total tract digestibility of gross energy, neutral detergent fiber, and acid detergent fiber by 2.7%, 20.7%, and 41.9%, respectively. In conclusion, the test multi-enzyme product can improve feed efficiency of weaned pigs, likely through improved digestibility of dietary fiber components.
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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 | 0.001 |
| 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".