A dietary spray‐dried plasma feeding programme improves growth performance and reduces faecal bacterial shedding of nursery pigs challenged with enterotoxigenic <i>Escherichia coli</i> K88
Bibliographic record
Abstract
Abstract This study aimed to assess the effects of different spray‐dried plasma (SDP) feeding programmes to pigs on performance, intestinal histomorphology and faecal bacterial shedding after an Escherichia coli K88 challenge. A total of 96 piglets (5.77 ± 0.01 kg) were weaned at 21 days of age (Day 0) and challenged with 3 ml of 1 × 1010 CFU of E. coli K88 in total 3.0 × 1010 CFU/animal on Days 0, 2 and 4. Pigs were fed nursery diets containing 0.0%, 3.0%, 6.0% or 9.0% SDP from weaning to 35 days of age; 0.0%, 1.5%, 3.0% or 4.5% SDP from 36 to 49 days; and the same control diet (without SDP), for the last 10 days of the experiment (50−59 days of age). Performance was measured from 35 to 59 days of age and faecal bacterial shedding and intestinal histomorphometry were evaluated at Days 28 and 49 of age respectively. From 21 to 35 days of age, there was a linear effect for body weight (BW) and average daily gain (ADG), a trend of linear effect for average daily feed intake (ADFI) and a quadratic effect for feed:gain ratio (FG). From 21 to 49 days, the 9.0:4.5% and 6.0:3.0% SDP feeding programmes improved BW, ADG and FG when compared to the other treatments. At 59 days of age, BW and ADG were increased by the two highest SDP feeding programmes. The 9.0:4.5% SDP feeding programme increased ADFI from 21 to 59 days of age, with 6.0:3.0% being intermediate and the other two treatments being lowest. The CFU counts of E. coli/g of faeces decreased linearly with increasing addition of SDP. These results indicate that an extended inclusion of increased SDP levels in post‐weaning diets can improve growth potential and decrease bacterial shedding induced by E. coli K88.
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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) | 0.001 | 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 | 0.001 |
| 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".