Effect of protein and carbohydrate feed concentrations on the growth and composition of black soldier fly (Hermetia illucens) larvae
Bibliographic record
Abstract
Black soldier flies ( Hermetia illucens ) can be used for a wide range of applications, from screening their anti-microbial properties, entomophagy through to waste management. Although the use of black soldier flies for these purposes has been widely studied, mass-rearing black soldier flies is still in the preliminary phase. This study focussed on the nutritional composition of black soldier fly larvae over the course of their life history, and the impact of manipulating dietary protein and carbohydrate on the growth and composition (protein and fat) of the larvae. Larvae were collected every 24 h over the course of this life-stage to test for differences in composition. To test the effect of dietary protein and carbohydrate differences, larvae were fed 25 diets with varying concentrations of protein and carbohydrates. Overall, the composition of larvae changed very little over their life history, with the higher concentration of protein mostly observed in the earlier instars of the larvae. The pre-pupal stage reduced the fresh and dry weight of the larvae, whereas the ash concentration was very stable throughout their life history. Both dietary protein and dietary carbohydrate had a significant effect on the fresh and dry weight of the larvae, but dietary protein was a stronger indicator of larval fresh and dry weight than dietary carbohydrate. Larval composition was also influenced by the feed-type, with heavier larvae producing significantly more fat than the lighter ones.
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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 | 0.000 | 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".