Oleogelation using pulse protein-stabilized foams and their potential as a baking ingredient
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
fat by the US Food and Drug Administration and Health Canada. Lately, the use of hydrocolloids such as animal proteins and modified cellulose for oleogel preparation has gained more attention. However, plant proteins have never been explored for the development of oleogels. The present study explored the use of freeze-dried foams prepared using protein concentrates and isolates of pea and faba bean with xanthan gum at different pH values for oil adsorption and subsequent oleogelation. Compared to protein isolate stabilized foams, protein concentrate-stabilized foams displayed (i) higher oil binding capacity (OBC) due to a higher number of smaller pore size; and (ii) lower storage modulus and firmness due to the higher oil content. At all pH values, there was no significant difference between the OBC of different protein isolates, but among the concentrates, pea displayed higher OBC than faba bean at pH 5 and faba bean displayed higher OBC than pea at pH 9. Results showed that such oleogels could be used as a shortening alternative. Cakes prepared using the pea protein-based oleogel at pH 9 displayed a similar specific volume as that of shortening-based cake, although with higher hardness and chewiness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it