Performance of growing-finishing pigs fed barley-based diets supplemented with normal or high-fat oat
Bibliographic record
Abstract
The objective of this study was to compare a high-fat oat recently developed at the University of Saskatchewan with regular oat as energy sources for use in diets fed to growing-finishing pigs. Seventy crossbred pigs (Pig Improvement Canada Ltd, Acme, AB) weighing an average of 27.5 ± 2.6 kg were assigned on the basis of sex, weight and litter to one of five dietary treatments in a factorial design experiment. The main effects tested included oat type (normal and high fat), level of oat inclusion (0, 25 and 50%) and sex of pig (barrows and gilts). Digestibility coefficients for dry matter (P = 0.002), crude protein (P = 0.001) and gross energy (P = 0.004) were significantly higher for pigs fed high-fat oat compared with normal oat. Pigs fed the high-fat oat also gained weight significantly faster (P = 0.01) and with increased efficiency (P = 0.01) compared with pigs fed diets containing normal oat. Oat level did not affect pig performance (P > 0.05). Neither type of oat nor level of inclusion had any significant (P > 0.05) effects on any carcass trait including dressing percent, carcass value index, lean yield, loin fat or loin lean. In conclusion, feeding diets containing a recently developed high-fat oat to pigs improved growth rate and efficiency of feed conversion compared with feeding diets containing normal-fat oat. Nutrient digestibility also improved with no negative effects on carcass quality. High-fat oat is an attractive alternative to normal oat as an energy source for growing-finishing pigs and can be fed at higher levels than are currently recommended for normal oat without hindering pig performance. Key words: Swine, high-fat oat, digestibility, growth, carcass composition
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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 | 0.000 | 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".