Revalorization of the Cooking Water (Aquafaba) from Soybean Varieties Generated as a By-Product of Food Manufacturing in Korea
Bibliographic record
Abstract
Concerns regarding sustainability have prompted the search of value in the by-products of food manufacturing. Such is the case of the cooking water (CW) of chickpeas, which has shown its potential as a vegan egg white replacement. This study aimed to characterize and compare the CW from three novel legumes (black soybeans, BSB; yellow soybeans, YSB; and small black beans, SBB) obtained from the processing of Korean soybean foods, and the widely used CW from chickpeas (CH), with regard to total polyphenol, total carbohydrate, and protein contents, and further compare their foaming and emulsifying abilities and stabilities. Compositional analysis revealed that all the studied legumes possessed higher values than CH for all parameters. Furthermore, the CW from these legumes exhibited enhanced functional properties, particularly foaming capacity and stability. Taken together, our results suggest that the CW from BSB, YSB, and SBB, sourced from the manufacturing of legume food products, has the potential of being revalorized as a plant-based functional ingredient for vegan product development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".