Evaluation of Using Fermented Okara (Soybean By‐Product) as a Feed Ingredient in Commercial Pig Production
Bibliographic record
Abstract
Okara is an insoluble soybean byproduct, and much of it is discarded due to its high perishability. This study investigated the efficacy of fully replacing fermented soybean meal in a control diet (PC) with fermented okara at an equal crude protein level (EC) or at an equal amount level (EQ) on growth performance and meat quality in 315 pigs, starting from weaners to finishers. Results indicated that EC and EQ groups led to significantly (p < 0.05) improved growth performance primarily during the grower and finisher stages. Both EC and EQ groups had significantly (p < 0.05) increased duodenal villus height. Moreover, EC group had significantly (p < 0.05) elevated concentration of acetic acid and reduced branched-chain fatty acids (iso-butyric acid and 2-methylbutyric acid) when compared to PC. There was an increase in volatile fatty acid-producing bacteria at the genus level, such as Prevotella, Lactobacillus, Megasphaera and Streptococcus in EC group. More importantly, no adverse effects on meat quality were observed in pigs fed with fermented okara. Taken together, utilization of fermented okara as an alternative protein source for animals not only improves performance and gut health, but also facilities a recycling economy to promote sustainable agriculture practices.
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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 | 0.001 | 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 | 0.001 | 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".