Water lentil (duckweed) protein purification by chemical (HCl) and electrochemical (Electrodialysis with bipolar membranes) acidification: Composition, structure and functional properties vs commercial protein isolates
Bibliographic record
Abstract
Water lentils (duckweeds) are a potential source of sustainable protein, though their use in food formulation remains underexplored. This study aims to investigate the functional properties of water lentil protein concentrates (WLPCs) and their by-products, which were obtained through solubilization followed by chemical (HCl) and electrochemical (electrodialysis with bipolar membranes) purification in comparison to the initial water lentil powder (IP), egg white, soy, and whey protein commercial isolates. Both purification methods increased RubisCO content from 40 % in the IP to 80-85 % in the purified products, while structural analysis showed a shift from intermolecular to intramolecular β-sheets and α-helices, enhancing functionality. Regardless of the purification process, WLPCs and their by-products exhibited complementary functional properties, often matching or exceeding those of the IP and commercial protein isolates. These findings highlight that purified water lentil proteins are suitable for food formulation, but further investigations are necessary to evaluate their organoleptic properties.
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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) | 0.000 | 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".