Temperature-dependence of life history in an edible cricket: Implications for optimising mass-rearing
Bibliographic record
Abstract
• Rearing temperature (20–38 °C) had substantial effects on life history traits in an edible cricket. • Growth, development and reproduction defined a range of temperatures suitable for mass-rearing (30–36 °C). • Yield estimates revealed times and temperatures that maximize yield for harvest. • The data are a first-step towards optimizing and evaluating industrial mass-rearing practices. Optimisation of life history and organismal performance underlies success in insect mass-rearing. Rearing schedules, resource use and production yield depend on many aspects of insect fitness and performance within and across generations, such as growth, development, longevity, and fecundity, which are all temperature dependent. Despite this general understanding, we often lack species-specific information needed to make informed decisions about manipulating rearing temperatures to optimise insect growth and development. Here, we characterise the effects of rearing temperature on nymph to adult development and lifespan (20 – 38 °C), and reproductive output (30 – 38 °C) in a farmed cricket ( Gryllodes sigillatus ). Crickets grew larger and reached adulthood sooner at higher developmental temperatures at the expense of longevity. Reproductive output was similar across a range of temperatures but decreased at 38 °C. Therefore, while temperature control is necessary to maximise production rates, temperature is unlikely to affect production yield in a fixed harvest cycle provided it is maintained within the narrow range enabling both fast growth and stable reproduction (32 – 36 °C). Our study provides a fundamental basis for further optimisation of insect rearing operations and a deeper understanding of the thermal biology of this commonly farmed species.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".