Influence of <i>Bacillus licheniformis</i> B4 fermentation on soybean meal nutritional value and early weaned pig growth performance
Bibliographic record
Abstract
AIM: This study aimed to examine B4's fermentation efficiency and the growth performance of newly weaned pigs fed B4 fermented soybean meal (B4-FSBM). METHOD AND RESULTS: Soybean meal (SBM) was inoculated with B4 and fermented at room temperature for 48 hours. Following fermentation, analysis was performed to examine anti-nutritional factor degradation efficiency. Fermentation broke down large molecular weight proteins, consistent with sizes of glycinin and β-conglycinin into smaller proteins. Crude protein significantly increased from 51.5% to 56.5%. Neutral detergent fiber (NDF) was reduced by 26.9% (P < 0.05), while the phytate phosphorus content was reduced by 59.16% (P < 0.05) in B4-FSBM. In the animal trial, 90 newly weaned piglets were divided into three groups, receiving either the negative control (NC; 25.4% SBM), positive control (PC; 25.4% SBM supplemented with 3000 mg/kg zinc oxide), or B4 (B4; 19% FSBM, 6.4% SBM). There was a temporary setback in growth performance for pigs fed B4-FSBM during the early weeks. However, their growth performance improved, and by the fourth week, their gain-to-feed ratio was significantly improved when compared to the control groups. Additionally, pigs fed B4-FSBM had increased (P < 0.05) crude protein digestibility compared to the NC for weeks 3 and 4. CONCLUSIONS: Fermentation of SBM with B4 improves feed efficiency and protein digestibility in weaned 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) | 0.001 | 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".