Comparison of Conventional and Sustainable Lipid Extraction Methods for the Production of Oil and Protein Isolate from Edible Insect Meal
Bibliographic record
Abstract
Edible insects represent an interesting alternative source of protein for human consumption but the main hurdle facing the edible insect sector is low consumer acceptance. However, increased acceptance is anticipated when insects are incorporated as a processed ingredient, such as protein-rich powder, rather than presented whole. To produce edible insect fractions with high protein content, a defatting step is necessary. This study investigated the effects of six defatting methods (conventional solvents, three-phase partitioning, and supercritical CO2) on lipid extraction yield, fatty profiles, and protein extraction and purification of house cricket (Acheta domesticus) and mealworm (Tenebrio molitor) meals. Ethanol increased the lipid extraction yield (22.7%–28.8%), irrespective of the insect meal used or the extraction method applied. Supercritical CO2 gave similar lipid extraction yields as conventional methods for Tenebrio molitor (T. molitor) (22.1%) but was less efficient for Acheta domesticus (A. domesticus) (11.9%). The protein extraction yield ranged from 12.4% to 38.9% for A. domesticus, and from 11.9% to 39.3% for T. molitor, whereas purification rates ranged from 58.3% to 78.5% for A. domesticus and from 48.7% to 75.4% for T. molitor.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".