252 Apparent ileal and total tract digestibility of corn DDGS steeped without or with fiber degrading enzymes and fed to growing pigs
Bibliographic record
Abstract
Corn dried distiller's grains with solubles (DDGS) are high in gross energy but their use in pig diets is limited due to high fiber concentration. Steeping fiber rich ingredients with fiber degrading enzymes (FDE) may improve their feeding value. We evaluated apparent ileal (AID) and total tract (ATTD) of CP, crude fat, and fiber in DDGS steeped without or with 2 commercially available FDE (A and B). FDE-A supplied 5,500 U of xylanase and 1,050 U of β-glucanase per kg of feed, and FDE-B supplied 1,200 U of xylanase, 150 U of β-glucanase, 500 U of cellulose, and 5,000 U of protease per kg of feed. A mixture of 350 g of DDGS, additives (none for control), and 1.5 l of water was placed in sterile containers and incubated at 40°C with agitation every 40 min for 24 h. For feeding, respective DGGS was mixed with a base at a ratio of 65:35 to provide 20% CP. The base contained corn starch, minerals, vitamins, and 0.2% TiO2 as indigestible marker. Six ileal-cannulated pigs (20 kg BW) were fed the 3 diets in a replicated 3 × 3 Latin square design to give 6 replicates per diet. Pigs were fed at 2.8 × maintenance energy and had free access to water. In each period, pigs were adjusted to diets for 5 d followed by 2 d for grab fecal and 2 d, 8 h continuous collection of ileal digesta. Treatments had no effects (P > 0.05) on AID of CP, fiber, and crude fat (Table 252). DDGS steeped with FDE-A had lower (P = 0.005) ATTD of NDF than control but higher (P = 0.001) ATTD of crude fat compared to the control or DDGS steeped with FDE-B. In conclusion, under conditions of the study, steeping DDGS with fiber degrading enzymes had no effects on fiber (NDF and ADF) digestibility in growing pigs. AID and ATTD (%) of components in corn DDGS steeped without or with FDE
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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) | 0.001 | 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".