The effects of rearing density on growth, survival, and starvation resistance of the house cricket Acheta domesticus
Bibliographic record
Abstract
Alternative food sources have become an important focus of research due to increased food demand coupled with reductions in traditional food productivity. In particular, substitutes for protein sources have been of increasing interest due to the unsustainability of traditional protein sources. Insects have been identified as a sustainable alternative to traditional protein sources, as they are easy to produce and contain essential proteins, fats, and minerals. However, mass-rearing insects requires similar considerations as farming traditional protein sources. To increase productively, growth and survival must be maximized at the highest possible densities while minimizing disease and food requirements. Here, we use the house cricket Acheta domesticus, a highly cultivated insect species, to investigate optimal densities for mass rearing at 14 days of age (4th instar). Nymphs were separated into density groups of 0.09, 0.19, 0.47, and 0.93 cricket/cm2 and monitored for growth and survival. Multiple regression revealed sex (p < 0.0001), density (p < 0.0001), and sex*density interaction (p = 0.0345) as predictors of growth rate. Survival to maturation was significantly reduced in both 0.47 (31%) and 0.93 (45%) cricket/cm2 groups compared to the controls. A second experiment was then conducted to investigate the starvation resistance of adult crickets reared from 14 days of age at 0.09, 0.19, 0.93, and 1.86 cricket/cm2. A second multiple regression analysis revealed only density (p < 0.0001) and to a lesser extent sex (p = 0.0005) to be predictors of starvation resistance. These results indicate that mass-rearing house crickets is most optimal at densities < 0.93 cricket/cm2, where impacts on survival and starvation are minimal. Although these results have implications for cricket mass rearing, research on other endpoints, including reproduction and the synergistic effects of other environmental factors, such as temperature and humidity, should be conducted.
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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".