Function of yeast extract in greater wax moth farming: does yeast extract always improve the development and reproduction of insects?
Bibliographic record
Abstract
TheGalleria mellonella L. (Lepidoptera: Pyralidae) has great nutritional potential for humans and animals and is currently used as a model organism in many biological studies, despite its damage to the apicultural industry and wild honeybee colonies. Yeast extract that promotes insect development and reproduction by containing many necessary nutrients has always been an important yet expensive ingredient in the majority of artificial diets forG. mellonella. To better understand the influence of yeast extract content onG. mellonella mass-rearing, the life table parameters fromG. mellonella mass-reared on increasing amounts of yeast (0% in control, 2, 4, 6, 7, and 9% of the total diet, respectively) under laboratory conditions were analysed according to age-stage, two-sex life table theory. Harvest rate and recruitment cost to produce 10,000 pupae were also assessed to help identify an economically sustainable rearing system. The intrinsic rate of increase (r) and finite rate of increase (λ) varied among diets. Highest values found in theG. mellonella population reared on a 9% yeast extract diet did not differ significantly from those of diets consisting of 4, 6, and 7% yeast extract, whereas these parameters were lowest in yeast-free artificial diets. The cheapest daily cost of rearing a population was 3,966.57 CNY (Chinese Yuan), and the heaviest pupal weight for both females and males (398.10±9.26 and 316.00±7.92 mg, respectively) were found with an artificial diet of 4% yeast extract. This study demonstrates that excessive dietary yeast extract is not always beneficial toG. mellonella. The most effective yeast extract percentage inG. mellonella mass-rearing diets is about 4% based on life table parameters, computer projection, and harvesting costs.
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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".