Optimizing wet isolation conditions and characterizing functionality of protein isolates from air-classified starch-rich pulse flours
Bibliographic record
Abstract
Starch-rich pulse flours are an underutilized, low-value by-product from air classification of pulses. They contain 8 %–20 % proteins with substantial untapped potential. This research aimed to optimize the alkaline extraction/isoelectric precipitation method to produce protein isolates from air-classified starch-rich faba bean and pea flours and to examine their techno-functional characteristics in comparison with commercial pea protein isolate (CPPI). The alkaline extraction was performed over a range of pH (8.5, 9.5, 10.5, and 11.0) and temperatures (25, 30, 40, and 50 °C). Higher pH and temperature increased the yields but reduced the purity of the protein isolates. Fourier transform infrared (FTIR) spectroscopy further revealed that the milder extraction conditions better preserved β-sheet and β-turn structures and led to smaller percentages of unordered α-helices in both faba bean (FPI) and pea protein isolates (PPI). FPI and PPI extracted under yield-optimized condition (designated as FPI-C yield and PPI-C yield ) exhibited greater denaturation, surface charge, and hydrophobicity than the counterparts from purity-optimized condition (designated as FPI-C purity and PPI-C purity ). Consequently, FPI-C yield and PPI-C yield showed reduced water solubility, increased oil-absorption capacity (OAC), and enhanced emulsion stability and foaming capacity as compared to respective FPI-C purity and PPI-C purity samples. This study revealed that the alkaline extraction conditions influenced not only the purity and yield but also the surface and functional properties of generated protein isolates. • Higher pH and temp. increased yields but lowered purity of pulse protein isolates • FTIR revealed mild extraction conditions better preserved β-sheets and β-turns • Pulse protein isolates from mild extraction were less denatured and less hydrophobic • Extraction conditions determined functional properties of pulse protein isolates • Structure-function relationships of pulse protein isolates were discussed
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".