Extraction of Proteins and Pasting and Antioxidant Properties of Soybean Hulls
Bibliographic record
Abstract
Soybean hulls are a by-product from soybean processing for oil and meal production which comprise approximately 8% of the whole seed. This study investigated water holding capacities and pasting properties, and first reported the phenolic contents and antioxidant activities from soybean hulls which are important to our long-term health. In addition, the conditions for extracting proteins from soybean hulls including optimum pH, as well as homogenizing and separation methods for extraction, were also studied. Higher protein content in extracts and recoveries was obtained with extraction at pH 9. Using sieve separation may be an effective way to extract proteins from hulls for industrial applications. The precipitated protein content increased from 51.52% to 59.29% after purification by washing with water once; however, after two washes, no further improvement was shown. The extracted proteins can be used for food applications. The ground hull powders (10% protein), dried supernatant (14% protein) and sediments (7-8% proteins) along with valuable fibers should be good food ingredients for several food categories. This research explored the great potential of converting the low value by-products into value-added functional food uses along with the benefit of reducing food and agricultural wastes.
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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".