Body weight gain and nutrient utilization in starter pigs that are liquid-fed high-moisture corn-based diets supplemented with phytase
Bibliographic record
Abstract
A total of 384 starter pigs were used to examine the application of exogenous phytase in high-moisture corn (HMC)-based liquid diets. Pigs were randomly assigned to 24 pens in six blocks. Pens were randomly assigned one of four HMC-based diets formulated to vary in total phosphorus (P) content (Low, Medium and High), with phytase added to only the Low P diet (Phy). Body weight gain and feed intake were monitored until body weight exceeded 20 kg. Apparent total tract digestibility of crude protein and P were measured on day 21 (Phase II) and day 42 (Phase III). At the end of the trial, two pigs from each pen were sacrificed for analysis of carcass composition and evaluation of metacarpals. Pigs fed the Phy treatment had increased digestibility of crude protein (P < 0.05) and P (P = 0.062) in Phase III, and increased metacarpal breaking strength (P < 0.01) and P content (P < 0.05). Average daily gain, feed intake, and carcass composition were not affected by treatment (P > 0.05). In conclusion, performance of starter pigs fed liquid HMC-based diets was maintained at dietary P levels below established requirements, but addition of phytase improved bone strength and mineralization. This study provides evidence for the effectiveness of phytase, and that P requirement for maximum rate of weight gain in pigs is not sufficient for maximum skeletal development.Key words: High-moisture corn, liquid feed, phosphorus, phytase, starter pigs
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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 | 0.000 | 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".