Influence of Extrusion Mixing on Preparing Lipid Complexed Pea Starch for Functional Foods
Bibliographic record
Abstract
The present work examines the ability to reactively modify pea starch by lipid complexing in a twin‐screw extruder in order to produce a functional food product. The study considers the influence of moisture content, lipid type (myristic acid, palmitic acid) and content, in tests with differing screw designs to reduce enzymatic digestion. The modified starch was characterized for its physicochemical properties (bound lipid content, pasting properties, and Englyst digestion profiles). With near complete conversion at all tested lipid concentrations, differences found in enzyme resistance and pasting properties for the extruded samples were attributed to differences in the mixing environment. The lipid complexed pea starches under optimized conditions achieved a significant but moderate increase in either resistant starch (from 7.8% to 20%) or slowly digestible starch (from 12% to 23%) content compared to their native counterparts; however, the sought nutritional fractions (slowly digestible and resistant) could only be improved simultaneously with palmitic acid. The highest resistant fraction produced in the study corresponded to the higher shear environment tested and for complexes prepared at the highest lipid content.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".