Adsorption of Soy Protein Isolate in Oil‐in‐Water Emulsions: Difference Between Native and Spray Dried Isolate
Bibliographic record
Abstract
Abstract The purpose of this study was to determine the differences in the emulsifying properties of isolated soy protein prepared in the pilot plant (heated and spray dried) or in the laboratory (unheated and freeze‐dried), from the same soy flakes. When the thermal transitions were measured by micro‐calorimetry, the protein isolated in the pilot plant showed a very broad thermal transition, while the native isolate showed two distinct transition peaks, attributed to β‐conglycinin and glycinin denaturation. Electrophoretic analysis and protein assay of the soluble protein in the fractions revealed a significantly smaller amount of protein recovered in the centrifugal supernatant for the isolated soy protein prepared in the pilot plant than for the native protein. A larger amount of ions was recovered in the pilot plant isolate. However, the thermal treatment of the solutions increased the recovery of the pilot plant isolate proteins in the centrifugal supernatant, with an opposite effect for the native soy protein. A significantly larger amount of pilot plant isolated protein was needed to prepare emulsions with the same characteristics of those prepared with native soy protein. The emulsions prepared with pilot plant isolates showed much lower susceptibility to heating than those prepared with native protein.
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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".