Feed size and texture influence propionic and butyric acid concentrations and Escherichia coli populations in the pig gastrointestinal tract
Bibliographic record
Abstract
Natural approaches are now being considered to replace antimicrobials to reduce the risk of antimicrobial resistance development.This has put new emphasis on using diet to control bacterial infections in pigs, some of which having recently demonstrated a zoonotic disease potential.Moreover, dietary modifications can lead to a modulation of the bioregulation of volatile fatty acids (VFA).Our objective was to assess the effect of feed size and texture on intestinal VFA profiles and concentrations, E. coli populations, and on growth performance.Fattening pigs (n=840) received one of six different diets (mash feed 500, 750 and 1250 µm and pellet feed 500, 750 and 1250 µm).Weight gain of pigs was monitored for each diet formulation over the fattening period.At the slaughterhouse, caecal and colon contents from 165 pigs were sampled for enumeration of E. coli by quantitative PCR (qPCR) and for VFA quantification.Acetic, propionic, and butyric acids were quantified by capillary gas chromatography.The yccT gene was used to enumerate total E. coli.A decrease in feed conversion associated with pellet texture and/or 500 µm particle size was observed for each diet formulation (p<0,05).In addition, caecal (p=0,0271) and colon (p=0,0012) propionic acid concentrations were lower for pigs receiving pellet rather than mash feed.Similarly, caecal (p=0,0167) and colon (p=0,0008) butyric acid concentrations were also lower for pigs receiving pellet rather than mash feed.Moreover, caecal (p=0,0208) and colon (p=0,0006) butyric acid concentrations were higher for pigs receiving a feed with a 1250 µm rather than 500 µm particle size.For total E. coli enumeration, caecal (p=0,01) and colon (p=0,04) yccT gene copy numbers were higher for pigs receiving pellet rather than mash feed.Taken together, results showed that mash feed is associated with favourable intestinal changes (VFA levels) and with a reduction of E.coli in the pig.
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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) | 0.000 | 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) | 0.001 | 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".