Production of Protein Isolates from Chilean Granado Bean (Phaseolus vulgaris L.)
Bibliographic record
Abstract
The Chilean granado bean (Phaseolus vulgaris L.) contains nutritionally valuable proteins, and there was indication that the proteins can help in the prevention of diabetes. To further explore tis potential purified samples of the bean proteins is required. A membrane-based process was developed for the isolation of proteins from granado beans, adapted from methods reported earlier for mustard protein processing. The optimised process consists of alkaline protein extraction from granado bean flour at pH 10, ultrafiltration at concentration factor 4 and diafiltration with diavolume 4 followed by isoelectric protein precipitation at pH 4. The process starting with granado beans containing 28% protein, recovered 60.1% of the protein as precipitated protein isolate (PPI) and 7.2% as acid soluble protein isolates (SPI). The losses in the process system were approximately 26% of mass and 18.8% of nitrogen due to removal of non-protein nitrogen and small molecular weight components, likely carbohydrates. The protein contents of the PPI and SPI were ~92 % and ~ 62% on a moisture-free basis; the protein content of the SPI produced is considerably lower than typical isolates. This may be due to the co-recovery of high molecular weight carbohydrates. The water absorption capacity and nitrogen solubility index, of the PPI and SPI were measured and compared to other oilseed isolates. The PPI showed high water absorption (<400%). SPI dissolved completely – a nitrogen solubility index of 100%, while PPI had low nitrogen solubility near its isoelectric point. Both isolates had traits desirable for easy incorporation into food products.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".