Six edible insect oils extracted by ultrasound-assisted: Physicochemical characteristics, aroma patterns and antioxidant properties
Bibliographic record
Abstract
ABSTRACT Oils from six edible insect commercially available in China (Tenebrio molitor (T. molitor), Teleogryllus mitratus, Locusta migratoria manilensis, Cryptotympana atrata (C. atrata), Clanis bilineata tingtauica larvae (C. bilineata tingtauica) and Protaetia brevitarsis larvae (P. brevitarsis)) were extracted by ultrasound-assisted n-hexane and characterized by physicochemical characteristics, biological active compounds, fatty acid composition, volatile components and antioxidant activity. The oil extraction yield of T. molitor was higher than that of other insects, reaching 33.90%. Six edible insect oils had the similar fingerprints with outstanding bands at the wavenumber of 2920, 2850, 1460, and 720 cm -1 . The UFA content in the oil of C. atrata were the highest, reaching 82.51%. The PUFA/SFA indexes of the other five insect oils were all higher than 0.45, except for P. brevitarsis oil. Hydrocarbons were the main volatile substances in the six insect oils. The scavenging ability of the DPPH radical in the oils of C. atrata and C. bilineata tingtauica was notably higher, with IC 50 values of 19.20 mg/mL and 23.63 mg/mL, respectively. The results could be used for the development and use of new edible insect oils in foods to improve resource utilization.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".