Effects on growth performance, feed efficiency, and health of weanling pigs fed fermented liquid whey inoculated with lactic acid bacteria that inhibit Escherichia coli in vitro
Bibliographic record
Abstract
Objectives: To determine the fermentation dynamics of liquid whey-dextrose (FLWD) inoculated with lactic acid bacteria (LAB) and whether feeding FLWD inoculated with LAB and added to a basal dry diet without antibiotics affects growth, feed efficiency, and health of weanling pigs. Materials and methods: One hundred and forty newly weaned pigs were assigned to five dietary treatments (four pens of seven pigs per treatment). Three FLWD preparations inoculated with either human- or pig-origin LAB strains were added to a basal dry feed. The fourth FLWD preparation contained no LAB. The fifth diet was the basal dry feed containing 0.1% lincomycin (control). LAB strains were mixed with FLWD prior to fermentation. Dry matter (DM), pH, and LAB counts of diets were measured daily during the 5-day fermentation period and the first 2 days of storage. Growth performance was recorded and rectal swabs were collected weekly. Fecal consistency was evaluated daily. Results: The pH and DM of fermented feed decreased and total LAB increased over time. Average daily gain and feed intake were highest in controls. Prevalence and severity of diarrhea were greater in pigs consuming LAB-inoculated diets than in control pigs. Mortality did not differ among treatment groups. Fewer hemolytic Escherichia coli were recovered from pigs fed FLWD. Implications: Fermented liquid feeds do not consistently promote better growth performance and health in weanling pigs. Use of LAB in starter feed may inhibit enteric E coli; however, further studies are needed to determine whether specific strains of LAB may prevent postweaning diarrhea.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".