Formulation and Evaluation of a Nutritionally Enriched Plant Protein-Based Matrix Using Low Temperature Extrusion Cooking—Air Drying Technology
Bibliographic record
Abstract
Extrusion cooking is broadly used in the food industry due to its easiness and simplicity. In this study a twin-screw extruder is applied at 150 rpm and 24-28 °C for the production of a nutritionally enriched extruded matrix, where hypo-allergenic rice protein (RP) and pea protein (PP) were used in the entrapment of natural antioxidant blueberry powder. The higher-moisture-content extrusion (40% MC) used with protein mixture (75 PP:25 RP) reduced the output temperature from 61.97 °C to 55 °C, the expansion ratio from 1.26 to 1, and the rehydration ratio from 78.70% to 31.90%, when compared with low-moisture-content extrusion used with RP samples (25% MC). Combining RP and PP showed also an enhancement in the textural properties of the extruded samples where firmness and toughness increased to 1503 (g) and 1822 (g.s), respectively, and preserved the anthocyanin content and antioxidant activity during extrusion processing and subsequent finish air drying. Moreover, the addition of maltodextrin in low concentration (5%) enhanced the antioxidant activity and anthocyanin retention (by 98.59% in mixture samples after extrusion and 92.13% after drying) and improved the appearance and sensory properties of the extruded matrices including firmness, toughness, and the color of the added blueberry powder.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".