Evaluating alternatives to zinc oxide and antibiotics in nursery pig diets
Bibliographic record
Abstract
Producers aspire to reduce the use of antibiotics and ZnO in swine diets to limit antimicrobial resistance and negative environment impact. This 35-d study was conducted using 360 weanling pigs (DNA 200×400; 5.4±0.07 kg BW) to evaluate the effects of substituting medium chain fatty acids (MCFA) for carbadox and ZnO. Pens were allotted in a completely randomized design with 6 pigs/pen and 10 pens/treatment. The treatment diets: 1) control; 2) 3,000 ppm ZnO in Phase 1 and 1,500 ppm ZnO in Phase 2; 3) 50 g/ton carbadox; 4) 1% C6:C8:C10; 5) 1% Feed Energy R2 (Feed Energy Corp., Des Moines, IA); 6) 1% FORMI GML (ADDCON, Bitterfeld-Wolfen, Germany). Treatment diets were fed for 19 d, with a common diet fed from d 19 to 35 (Phase 3). In Phase 1 (d 0 to 7) ADG and ADFI had a significant difference (P<0.05) between ZnO, C6:C8:C10, and R2. Phase 2 (d 8 to 19) observed a significant difference (P<0.05) in ADG with ZnO and FORMI GML having greater ADG than other treatments. Phase 3 (d 20 to 35) had no significant difference in any response (P<0.05). Overall (d 0 to 35) pigs fed ZnO or carbadox had greater (P<0.05) ADG than those fed the control or R2 diets, pigs fed the C6:C8:C10 blend or FORMI had similar (P>0.05) ADG as those fed carbadox. During the common period, pigs fed ZnO continued to have greater (P<0.05) ADG than those fed R2, with other treatments being intermediate. There was no overall impact on G:F (P = 0.320). The results of this study suggest that although the MCFA did not improve weanling pig growth over ZnO and Carbadox, 1% FORMI GML may be a promising alternative. Thus, additional research regarding MCFA is warranted to effectively replace ZnO or antibiotics in pork production.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".