250 Effect of Dietary Zinc and Copper Supplements on Digestibility of Minerals in Growing Pigs
Bibliographic record
Abstract
Abstract Dietary zinc (Zn) and copper (Cu) supplementation can affect the digestion and absorption of nutrients in pigs, especially of minerals. This study aimed to evaluate the effect of dietary levels of Zn and Cu on their ileal (AID) and total tract (ATTD) digestibility and that of manganese (Mn), calcium (Ca), and phosphorus (P). Six crossbred pigs were surgically equipped with a single-T cannula in their distal ileum. In cross over design, pigs received one of a four corn-soybean meal diets supplemented by two levels of Zn (100 and 500 mg/kg as Zn oxide) and two levels of Cu (40 and 80 mg / kg as Cu sulfate) for each period (7d with 2d for ileal digesta and feces collection). In this study, high level of Zn increased Zn and Mn AID (P< 0.01) but decreased Ca AID (P< 0.05). The high level of Cu improved Cu AID but only when high level of Zn was used (Zn x Cu, P< 0.051). The ATTD of Zn, Cu, Mn, and P were greater in pigs receiving 500 mg/kg of Zn (P< 0.01). The high level of Cu also increased its ATTD (P< 0.01) but reduced that of Ca when low level of Zn was added (Zn x Cu, P< 0.01). The post-ileal digestibility showed a significant absorption of Cu, Mn and Ca (digestibility different from 0). The post-ileal digestibility of Cu, Mn and Ca was greater when high level of Zn was added (P< 0.05). This study confirmed that the AID and ATTD of Cu and Zn could be affected by the dietary level of Zn and Cu in growing pigs. This study also showed that high levels of Cu and Zn reduced ATTD and AID of Ca but increased P ATTD. This last result is contradictory and must be confirmed by the analysis of phytic P.
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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) | 0.000 | 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".