Effect of solid-state fermentation on the functionality, digestibility, and volatile profiles of pulse protein isolates
Bibliographic record
Abstract
Fermentation, as a clean processing technique, induces structural and compositional modifications to plant proteins, improving their functionality and nutrition. However, the effect varies depending on the level of hydrolysis, the fermenting strain, and the specific substrate used. The present work examined the effect of solid-state fermentation (SSF) by Lactobacillus plantarum, Aspergillus niger and Aspergillus oryzae of several niche market pulse (chickpea, green lentil, and faba bean) protein isolates on their functional and nutritional properties. The pulse proteins were moderately hydrolyzed to different extents (degree of hydrolysis of 9%–15%) after 48 h of fermentation, enhancing surface charge and solubility while decreasing water holding capacity and emulsion stability. Protein digestibility was reduced for all pulses which was hypothesized to be due to an increase in phenolic content caused by fermentation. Among the strains, only A. niger outgrew the natural microbiota for all pulses. Variations relating to the property changes were observed among the inocula and pulses; however, no general trend could be concluded. Fermentation produced a large variety of favourable new volatile compounds in the protein isolates.
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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".