Effects of <i>Quillaja</i> saponin supplementation on growth performance, nutrient digestibility, fecal microbiota, and fecal gas emission in growing pigs
Bibliographic record
Abstract
The purpose of this study was to evaluate the effects of dietary supplementation of Quillaja saponin (QS) on growth performance, nutrient digestibility, fecal microbiota, and fecal gas emission in growing pigs. A total of 50 crossbred growing pigs [(Yorkshire × Landrace) × Duroc] with an initial body weight of 23.83 ± 1.95 kg were randomly assigned to one of two treatments for a 56 d trial with five replicate pens per treatment and five pigs (two barrows and three gilts) per pen. Dietary treatments including control diet and control diet supplemented with 200 mg·kg−1 QS. The average daily gain was significantly increased during days 0–56, whereas the fecal ammonia emission on day 56 and fecal coliform bacteria counts on day 28 were significantly decreased in pigs fed with QS-containing diet. However, dietary supplementation of QS had no significant effects on apparent total tract digestibility. In conclusion, dietary supplementation of 200 mg·kg−1 QS had beneficial effects on growth performance, fecal microbiota, and fecal gas emission in growing pigs. Considering the carry-over effects, the adaption period should be at least 28 d when supplementing 200 mg·kg−1 QS to the diet of growing pigs for improving the growth performance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 | 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".