Effect of pelleting on nutrients and energy digestibility in growing pigs fed corn-soybean meal-based diet or diet containing corn distillers dried grains with solubles (cDDGS), wheat middlings, and bakery meal
Bibliographic record
Abstract
This study was conducted to determine the effect of pelleting and diet type on the apparent ileal (AID) and total tract digestibility (ATTD) of nutrients and energy in growing pigs. Six pigs were cannulated at the ileum and were assigned to treatments following a crossover design. One diet was a control diet based on corn and soybean meal (CT). Part of it was replaced by corn distillers dried grains with solubles (cDDGS), wheat middlings, and bakery meal in the second diet (ByP). Diets were in mash (CT-MH and ByP-MH) or pelleted (CT-PT and ByP-PT) form. Results showed that pelleting increased digestibility in all diets with a distinct effect on the CT diet (interaction diet × pelleting, P < 0.05). Pelleting improved the AID of dry matter, crude protein, and energy by 17%, 27%, and 17% in the CT diet and by 10%, 9%, and 17% in the ByP diet (P < 0.01). The AID of amino acids followed the effect observed on crude protein (P < 0.01). Pelleting increased AID of total non-starch polysaccharides for the CT diet by 63% and 42% for the ByP diet (P < 0.01). The pelleting conditions improved the degradability of the compounds in the diets during digestion in 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".