200 Effect of Long-term Feeding of Deoxynivalenol (DON) Contaminated Diets on Performance of Grower-finisher Pigs
Bibliographic record
Abstract
Abstract Previous studies examining the effects of deoxynivalenol (DON) intake in pigs have largely focused on young animals or have been over a short period of time. The objective of the present study was to determine the effects of long-term feeding of DON contaminated diets on growth performance of grower-finisher pigs. A total of 240 mixed-sex pigs (35.9 ± 1.1 kg) were group housed in 6 pigs/pen (n = 10/treatment) and were randomly assigned to 1 of 4 dietary treatments for 77 d. Diets consisted of a control diet (CON) containing no DON or a diet containing 1, 3, or 5 ppm DON (DON1, DON3, or DON5) achieved by adding DON-contaminated wheat and wheat screenings at the expense of clean wheat. In the grower period, DON5-fed pigs had reduced average daily gain (ADG) compared to CON, with DON1 and DON3-fed pigs being intermediate P < 0.05). There was no effect of dietary treatment on ADG in the finisher period (P > 0.05). Overall the entire study, DON3 and DON5-fed pigs had similar and reduced ADG (P < 0.05) compared to CON and DON1, which did not differ (P > 0.05). Feed intake was reduced in DON-fed pigs in the finisher period (3.12, 2.97, 2.96, and 2.88 ± 0.05; P< 0.05) and in DON3 and DON5-fed pigs overall (2.62, 2.55, 2.47, 2.47 ± 0.03; P < 0.05) compared to CON, with no overall effect observed in the grower period. There was no effect on feed efficiency in any period (P > 0.05). The decrease in performance resulted in reduced final body weight in DON3 and DON5-fed pigs, compared to CON, with DON1-fed pigs being intermediate (P > 0.05). Overall, the effects of DON-intake on performance were variable and generally occurred rapidly after initial exposure and appear to be largely due to the reduction in feed intake.
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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 | 0.001 | 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".