Edible insects as an alternative protein source: Nutritional composition and global consumption patterns
Bibliographic record
Abstract
• Insect consumption varies across (sub)tropical and temperate regions of the world. • Edible insects are mostly from the orders Coleoptera, Hemiptera and Lepidoptera. • Powder functionality and protein quality differs among edible insect species. • Food safety (allergen) concerns affect insect consumption and food applications. Insects are emerging as a viable alternative protein source due to shifting global consumption patterns and environmental concerns associated with meat production. Despite their nutritional benefits, insects from the orders Coleoptera, Hemiptera, and Lepidoptera are yet to be widely accepted as dietary ingredients globally. This review examines regions of the world where insects are traditionally consumed and the current trends in global consumption patterns. It presents the complex and essential nutrients inherent in the different edible insect orders, potential insect-derived products, their role in ensuring food security as well as food safety concerns. Historically, tropical and some temperate regions of Asia, Africa, North America (including Mexico), South America, and Oceania have incorporated insects into their diets. Edible insects are rich in complex and essential nutrients, including chitin, high quality amino acids, vitamins, minerals, fatty acids, phenolic compounds and flavonoids. Chitin, a dietary fibre in edible insects, offers antimicrobial, cholesterol-lowering properties and serves as an excipient in medicinal compounds. However, the varying amino acid profile of different insect species pose challenges in meeting the human dietary requirements. Nonetheless, innovative insect-derived food products such as meat substitutes and composite baked products are gaining acceptance, thereby positioning edible insects as a sustainable alternative protein source in diets.
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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 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".