111 Fermentation of Soybean Meal Using a Novel Bacillus Subtilis Isolate to Improve Nutritive Value in Growing Pigs.
Bibliographic record
Abstract
Soybean meal (SBM) fed to pigs contains a variety of antinutritional factors that impair the digestion of protein and utilization of nutrients. In the current study, a commercial SBM was subjected to solid state fermentation (SBM: water, 1:1; inoculum, 1%; temperature, 22-25°C) using a novel Bacillus subtilis CP-9 expressing high level of cellulase, xylanase and protease activities. Protein profile of the SBM after 48 h fermentation showed degradation of high molecular weight proteins including antigenic proteins into small-size peptides on sodium dodecyl sulfate polyacrylamide gel electrophoresis. To examine if fermentation altered the nutritive value of SBM, eight barrows (40 ± 2 kg BW) fitted with terminal ileal T-cannula were used. Two semi-purified corn starch–based diets were formulated with unfermented (UF) and fermented (F) SBM as the sole source of AA (min 18% CP, as-fed basis). Pigs were allocated in a two-period cross over design (n = 8) and were fed at 2.8 × maintenance energy requirement. Each period was 9 d; 5 d for adaptation, d 6 and 7 for grab fecal collection and d 8 and 9 for 8 h continuous ileal digesta collection. The diet was considered fixed effect whereas pig and period were considered random effects in statistical analysis. Pigs fed F-SBM had higher (P<0.05) apparent ileal digestibility (AID) of CP (82.7 vs. 79.6%) and ash (46.3 vs. 43.0%) compared with pigs fed UF-SBM. There was no treatment effects (P> 0.10) on AID of NDF and ATTD of acid detergent fiber (ADF), neutral detergent fiber (NDF) and gross energy (GE). In conclusion, fermentation of SBM by a novel Bacillus subtilis CP-9 increased ileal utilization of crude protein and minerals suggesting improved nutritive value 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 | 0.000 |
| 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) | 0.000 | 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".