Individual-level Dietary Manipulation for Optimizing Mass Rearing of the Edible Cricket Gryllodes sigillatus
Bibliographic record
Abstract
Insects, a sustainable and nutritious alternative protein source, are one potential solution to mitigating food insecurity.North America and Europe are currently experiencing the rapid development of the insects as food and feed industry, with some companies focused on farming crickets for human food and agricultural feed.Increasing yield is a primary goal of agricultural research.Yield is a measurement of product harvested per unit area, and cricket farms struggle with how best to do this at a scale of billions of crickets required for a farming environment without the costs of additional labour.I argue that yield can be thought of as a function of survival and body size at and development time to adulthood.In this thesis, I have used a multifaceted approach to explore how diet can manipulate growth, development time to adulthood, and survival of Gryllodes sigillatus.My findings revealed that a 15% dietary supplementation with royal jelly elicited a sex-specific increase in mass; females fed the royal jelly diet were 30% heavier, and this effect was driven by significantly longer abdomens containing 67% more eggs compared to those fed the basal diet.I also demonstrate that manipulation of protein and carbohydrate availability can optimize growth and development of G. sigillatus; yield was maximized on a 3P:1C diet, as crickets fed this diet were most likely to develop into adults and grew maximum mass and body size.Similarly, I show that the physical attributes of diet can also exert strong influences on life history; crickets fed a large particle size diet grew larger and heavier faster compared to crickets fed a small particle size diet, and crickets also demonstrated a preference for medium and large size diet throughout development.Finally, I present the first recorded results detailing the pest-beneficial interactions between dermestids and farmed crickets; crickets experienced delayed growth early in life after living with dermestids, but crickets can tolerate living with, and consuming, dermestid larvae.Overall, my findings suggest iii that dietary supplementation, macronutrient ratio, diet particle size, and pest interactions all contribute to variation in cricket life history traits important to production yield.
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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 | 0.001 |
| 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".