Aquafaba from Korean Soybean II: Physicochemical Properties and Composition Characterized by NMR Analysis
Bibliographic record
Abstract
Aquafaba (AQ) emulsification properties are determined by genetics and seed processing conditions. The physicochemical properties and hydration rates of chickpea (CDC Leader) as a control with proven emulsifying properties were recently reported. Here, we identify correlations between soybean (Backtae, Seoritae, and Jwinunikong) physical, chemical, and hydration properties as well as AQ yield from seed and functional (emulsion and foaming) properties. In addition, a total of 20 compounds were identified by NMR including alcohols (isopropanol, ethanol, methanol), organic acids (lactic acid, acetic acid, succinic acid, citric acid, and malic acid), sugars (glucose, galactose, arabinose, sucrose, raffinose, stachyose), essential nutrients (choline, phosphocholine), amino acids (alanine, glutamine), and polyphenols (resveratrol, glycitin). The process used in this study utilizes a soaking step to hydrate the seed of the selected Korean soybean cultivars. The product, AQ, is an oil emulsifier and foaming agent, which is suitable for use as an egg substitute with improved emulsion/foam formation properties when compared with a chickpea-based AQ.
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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".