Effects of novel protein extraction methods on structure-functional properties and protein quality of fava bean protein isolates: A comparative study
Bibliographic record
Abstract
The effects of deep eutectic solvent (DES)-based protein extraction on structural and functional properties of fava bean protein isolate (FBPI) were determined in comparison to conventional salt and alkaline extraction methods, and the commercial soybean protein isolate (CS-PI) as the standard protein. The protein content of fava bean isolates extracted from DES (DESE-FBPI), alkaline (ALKE-FBPI), and salt (SSE-FBPI) was observed to be similar (∼92 %). FTIR data indicated that all protein isolates had intermolecular β-sheets as protein aggregates, except in DESE-FBPI. Differences in the extraction methods reflected better solubility, foaming and emulsification properties, and gelling capacity by DESE-FBPI than the conventionally extracted counterparts. In terms of protein quality, significantly higher (p < 0.05) in-vitro-protein digestibility corrected amino acid score (IV-PDCAAS) was exhibited by DESE-FBPI (87.24 ± 0.70%) and SSE-FBPI (86.52 ± 0.83%) than the ALKE-FBPI (80.45 ± 0.08%). These results suggest that different extraction methods have a profound impact on protein functionality and quality.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".