164 Out-of-Feed Events and Gastric Ulcers in Finishing Pigs fed 40% air-Classified pea Starch Diets
Bibliographic record
Abstract
Abstract Air-classified pea starch (ACPS), a new feed ingredient, that is very fine and may contribute to bridging and the formation of gastric ulcers in pigs, especially if combined with extended feed outage event. The objective of this study was to determine the impact of a feed-out duration event in finishing pigs fed 40% ACPS diets, on gastric ulcers and animal growth parameters. A 28-d trial was performed utilizing 90 pigs with initial BW of 90.6±2.2 kg, housed in groups of 5 in a complete randomized design. A control group of pigs were also fed standard production diets without ACPS. A total of four treatments consisting of a control group (no ACPS) that had continuous access to standard feed, and an ACPS diet group exposed to 0h, 16h and 24h feed-out events. After d 28, 3 pigs/pen from the pigs fed ACPS diets were sent to a commercial abattoir and their stomach tissues harvested. Lesions in the pars oesophagea were scored on a scale of 0 to 4. Pigs fed the ACPS diets tended to have a higher BW (P < 0.09) compared to the control pigs by d 7. However, there was no difference on the overall BW (P>0.09). ADG was higher (P < 0.05) in pigs fed the ACPS diets in the initial 7 days than the control pigs. Overall ADFI in pigs fed ACPS diets were higher (P < 0.05) than the control pigs. The overall G:F was reduced in the ACPS-fed pigs. The 0h, 16h and 24h out of feed events produced 83%, 91% and 100% ulcers respectively. With the average ulcer scores being 1.8, 2.3 and 2.0 for the 0h, 16h and 24h, respectively. In conclusion, feeding 40% ACPS diets resulted in a high incidence of ulcers and 16h feed outage results in the highest severity.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".