An organic acid blend can modulate swine intestinal fermentation and reduce microbial proteolysis
Bibliographic record
Abstract
The increased use of slow-release organic acids in swine nutrition has prompted more research to assess their possible role in modulating the intestinal microflora as an alternative to antibiotics. Three diets for growing pigs containing 0 (L-NDF), 100 (M-NDF), and 200 g kg-1 (H-NDF) dried sugar beet pulp (SBP) were pre-digested to simulate ileal digestion, and used as substrate in an in vitro cecal fermentation study. The inoculum was collected from pigs immediately after slaughter. Diets tested were L-NDF, M-NDF, and H-NDF with or without the addition of an organic acid blend providing phosphoric, citric, fumaric, and malic acid at 1.53, 0.78, 2.59, and 1.12 mmol L-1, respectively. Cecal microbial growth was monitored using the cumulative gas production technique. Fermentation fluid was analyzed for ammonia and volatile fatty acids concentrations. The maximum rate of gas production was higher when H-NDF rather than L-NDF or M-NDF (+ 18%; P < 0.05) was fed; such a high rate of growth (+ 14%; P < 0.05) was also achieved when the acid blend was added to L-NDF. After 24 h, the acid blend reduced ammonia, isoacids, and acetic acid concentrations in fermentation fluid regardless of the type of diet (P < 0.05). Organic acids stimulated bacterial fermentation when added to a low-fiber diet and were able to reduce ammonia in all diets tested. Key words: Swine, cecum, fiber, organic acids, ammonia, volatile fatty acid
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".