In vitro digestibility, peptide profile, and bioactivities of water lentil (duckweed) protein compared to commercial protein isolates
Bibliographic record
Abstract
Water lentils (duckweeds) are a promising protein source, however their digestibility and potential to release bioactive peptides remain underexplored. This study investigated, for the first time, the in vitro digestibility of proteins from water lentil protein concentrates (WLPCs) and their associated by-products obtained through chemical or electrochemical purification, in comparison with the initial native water lentil powder (IP) and commercial protein isolates (egg white, whey, and soy), using the INFOGEST protocol. Following the intestinal phase of the digestion, WLPCs exhibited moderate digestibility, likely due to protein denaturation during extraction, whereas the bioaccessible fraction (∼38 %) of IP showed high digestibility. Peptide profiling further revealed that IP produced a more diverse peptide pool than WLPCs and their by-products. Regarding bioactivity, intestinal digestate supernatants from IP, whey and soy protein isolate showed the strongest ACE inhibition, while WLPCs exhibited the highest DPP-IV inhibition. These findings indicate that water lentil protein purification does not necessarily improve digestibility, but they confirm the potential of water lentil proteins as a valuable source of bioactive peptides.
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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".