Protein matrix interactions and adaptogenic bioactive release in high-protein cracker systems enriched with Rhodiola rosea and Eleutherococcus senticosus
Bibliographic record
Abstract
Bioactive compounds like phenylpropanoids and phenylethanoids, found in adaptogenic roots Rhodiola rosea (RR) and Eleutherococcus senticosus (ES), are commonly used in supplements. Crackers made with pulse protein isolates represent a vehicle to deliver these compounds. This study investigated interactions of RR and ES root powders with protein isolates (pea (PPI), faba bean (FBPI), lentil (LPI) and lupin (LuPI)) and their impact on dough and cracker physicochemical properties. In addition, in vitro bioaccessibility was studied. Root powders significantly increased dough consistency, with RR promoted protein aggregation. In the crackers, a reduced lightness and increased yellowness was shown, particularly with RR. FBPI_control crackers were the hardest and stiffest, while root addition generally softened texture. FTIR revealed that secondary structure changes influenced in vitro bioaccessibility, with β-sheets and protein aggregates limiting and random coil enhancing release of bioactives. Combining adaptogenic roots with pulse proteins is a promising strategy for producing functional high-protein crackers. • ES and RR roots modified the dough consistency and protein aggregation behavior. • Protein secondary structure (β-type protein aggregates) modulated cracker hardness. • α-Helix restricted the release of eleutheroside B and E and tyrosol. • Protein source modified the release of bioactive compounds and the bioaccessibility.
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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".