Effects of betaine, organic acids and inulin as single feed additives or in combination on bacterial populations in the gastrointestinal tract of weaned pigs
Bibliographic record
Abstract
A study was carried out to investigate whether blends of betaine, organic acids and inulin may improve their efficacy to modulate intestinal bacterial populations in weaned pigs compared with the single application of these additives. Moreover, potential postprandial diurnal variations in ileal bacterial numbers were determined in piglets fed the control diet. Twenty-four piglets in two consecutive experiments received a wheat-barley-soybean meal control diet (Con) or the Con diet supplemented with betaine (BET; 0.2%), an organic acid blend (AC; 0.4%) or inulin (IN; 0.2%) as single additives or in combination. Ileal bacterial numbers of total bacteria, lactobacilli, bifidobacteria (p < 0.05) and enterobacteria (p < 0.10) showed a postprandial diurnal variation, thus spot sampling of ileal digesta for the determination of bacterial numbers may not be representative. There were only small effects of BET, AC and IN on ileal and faecal bacterial populations. BET + AC increased total ileal bacterial numbers compared to the Con and AC treatments. BET reduced lactobacilli numbers in faeces, whereas BET + IN increased ileal numbers of bifidobacteria compared to AC and IN. There is evidence that BET, AC, IN and their combinations may affect proliferation of beneficial bacterial populations, although this has to be confirmed in further studies.
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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 | 0.001 |
| 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 | 0.001 | 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".