Influence of the processing on composition, protein structure and techno-functional properties of mealworm protein concentrates produced by isoelectric precipitation and ultrafiltration/diafiltration
Bibliographic record
Abstract
Edible insects represent a great alternative protein source but food neophobia remains the main barrier to consumption. However, the incorporation of insects as protein-rich ingredients, such as protein concentrates, could increase acceptance. In this study, two methods, isoelectric precipitation and ultrafiltration-diafiltration, were applied to produce mealworm protein concentrates, which were compared in terms of composition, protein structure and techno-functional properties. The results showed that the protein content of the isoelectric precipitation concentrate was higher than ultrafiltration-diafiltration (80 versus 72%) but ash (1.91 versus 3.82%) and soluble sugar (1.43 versus 8.22%) contents were lower. Moreover, the protein structure was affected by the processing method, where the ultrafiltration-diafiltration concentrate exhibited a higher surface hydrophobicity (493.5 versus 106.78 a.u) and a lower denaturation temperature (161.32 versus 181.44 °C). Finally, the ultrafiltration-diafiltration concentrate exhibited higher solubility (87 versus 41%) and emulsifying properties at pH 7 compared to the concentrate obtained by isoelectric precipitation.
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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 | 0.001 | 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".