PSIII-33 Nutritive value of soybean products fed to growing pigs without or with multi-enzyme.
Bibliographic record
Abstract
Indigestible fiber-protein-phytate complexes reduce feeding value of soy products. We investigated effects of multi-enzyme supplement (MES) on standardized ileal digestibility (SID) of AA and DE content in expeller soybean meal (ESBM) and roasted full fat soybean seed (FFSB) fed to growing pigs. The ESBM was a commercial product and FFSB was roasted at 118–120°C for 75 min in a local farm. The CP was 42.8 and 33.4% DM in ESBM and FFSB, respectively and corresponding values for crude fat were 11.8 and 17.4% DM. Semi-purified diets with 50% of either ESBM or FFSB as sole source of AA were prepared without or with MES supplying phytase, protease, xylanase, β-glucanase at 1,500, 5,625, 270 and 70 U/kg of feed, respectively. Diets had TiO2 indigestible marker and ratio of cornstarch to sucrose and corn oil was identical to our published N-free diet to calculate DE by difference method. Eight ileal-cannulated barrows (BW = 22.1 ± 0.61 kg) were fed 4 diets in a replicated 4 × 4 Latin square design (n=8). Period lasted for 9 d; 5-d for acclimation, 2-d for fecal and 2-d for ileal digesta samples collection. Fixed effects of soy product, MES and two-way interactions were evaluated. There was no (P>0.05) interaction or MES effect on AID and SID of CP and AAs, except AID and SID of Phe (P<0.05). ESBM had higher (P<0.05) AID and SID of CP and AAs than FFSB. There was no (P>0.05) interaction or MES effect on apparent total tract digestibility (ATTD) except on CF (P<0.05), and MES effect on Ash and CP. ESBM had higher (P<0.05) ATTD of DM, Ash, CF, GE, CP, while FFSB had only higher (P<0.05) ATTD of NDF. In conclusion, MES had no effect on AID and SID of AA. ESBM had higher AID, SID and ATTD than FFSB.
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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 | 0.000 |
| 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".