Drying technologies for edible insects and their derived ingredients
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
Edible insects and their ingredients are considered as a novel, sustainable and high-quality nutritional source for their potential use as food and feed. However, they are highly oxidizable and potentially unsafe. Dehydration of insects removes moisture and extends their shelf life. Moreover, it is considered as a prerequisite and/or pretreatment for some extraction technologies for ingredient production. Drying technologies (sun drying, smoke drying, roasting, freeze drying and oven drying) have been used to dry insects, both at a laboratory and industrial level. Different drying pretreatments (thermal blanching, microwave-assisted drying and pulsed electric field) have been explored to improve the final quality of the insect products, extending their shelf life and reducing total energy consumption. Therefore, this article aimed to review the current research available in edible insect drying processing technologies, addressing their effectiveness and their influence over different quality parameters such as protein/lipid extraction efficiency, sensory characteristics of the final products, microbiological safety, shelf life and their impact on bioactive compounds.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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