Characterization of pea composites and feasibility of heat-modulated meat analogs production
Bibliographic record
Abstract
This study aimed to characterize pea composites' functionalities and investigate the feasibility of pea composites-based heat modulated meat analog (MA) production. Pea composites (concentrate, flour) were used as the main source of plant-proteins in preparation of MA. Techno-functional, sensorial, microstructural, chemical, and thermal characteristics of pea composites as well as the prepared MAs were investigated. Results showed that, protein content and particles size significantly ( p < 0.05) influenced the water holding capacity (0.94 g/g ± 0.03–1.17 g/g ± 0.08), oil holding capacity (1.08 g/g ± 0.02–1.32 g/g ± 0.04), foaming capacity (49.20 % ± 0.12–58.9 % ± 0.98), foam stability (63.15 % ± 0.21–71.82 % ± 0.68), emulsion stability (61.73 % ± 1.68–66.02 % ± 1.25), least gelation concentration (at pH 7: 8.02 % ± 0.91–18.02 % ± 0.21), and solubility (at pH 7:70.51 % ± 2.54–93.71 % ± 1.86) of studied pea composites; that subsequently influenced the formation of heat-modulated MAs. Color, stickiness, moldability, microstructure (surface plot, fractal dimension: 2.771 ± 0.006–2.884 ± 0.009, surface openings: 8.76 % ± 1.25 − 33.24 % ± 1.28), thermal (denaturization temperature:103.41 °C ± 3.87–161.20 °C ± 1.35, enthalpy: 1085.10 J/g ± 115.42–1322.71 J/g ± 185.65), and chemical attributes of MAs were associated with the protein content (25.30 % ± 0.98–60.30 % ± 1.87) and particle size (d 10 :2.30 μm ± 0.32–15.02 μm ± 1.35; d 50 :6.30 μm ± 1.02–59.01 μm ± 2.35; d 90 :15.11 μm ± 2.34–137.01 μm ± 15.21) of pea composites. MA formulated with pea flour showed better moldability and acceptability in comparison to pea concentrates. This study exposed the use of pea flour as a feasible option to produce heat modulated meat analogs. • Protein content and particle size impacts techno-functional traits of pea composites. • Types of pea composite impacts the attributes of formulated meat analog (MA). • Pea flour is a promising ingredient to produce heat-modulated MA. • Lower protein content and larger particle resulted compact microstructure in MA.
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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".