Current state of insect proteins: extraction technologies, bioactive peptides and allergenicity of edible insect proteins
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This review aims to provide an updated overview of edible insect proteins and the bioactivity of insect-derived peptides. The essential amino acid content of edible insects is compared with well-known protein sources to demonstrate that edible insects have the potential to cover the protein quality requirements for different groups of the population. Then the current methodologies for insect protein extraction are summarized including a comparison of the protein extraction yield and the final protein content of the resulting products for each method. Furthermore, in order to improve our understanding of insect proteins, their functional properties (such as solubility, foaming capacity, emulsifying, gelation, water holding capacity and oil holding capacity) are discussed. Bioactive peptides can be released according to various enzymatic hydrolysis protocols. In this context, the bioactive properties of insect peptides (antihypertensive, antidiabetic, antioxidant and anti-inflammatory properties) have been discussed. However, the allergens present in insect proteins are still a major concern and an unsolved issue for insect-based product consumption; thus, an analysis of cross reactivity and the different methods available to reduce allergenicity are proposed. Diverse studies of insect protein hydrolysates/peptides have been ultimately promoting the utilization of insect proteins for future perspectives and the emerging processing technologies to enhance the wider utilization of insect proteins for different purposes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it