Effect of alternative rearing substrates and temperature on growth and development of the cricket Modicogryllus conspersus (Schaum)
Bibliographic record
Abstract
The increasing demand for animal protein in sub-Saharan Africa has led to insects being considered an alternative protein source for food and feed. In Uganda, chicken mash, containing fish meal as the protein source is commonly used to rear crickets. However, fishmeal is an expensive protein source that is also human food. This study therefore aimed at establishing an alternative preferred (consumed in the highest quantity) plant leaf diet for raising the Modicogryllus conspersus cricket, and the most suitable temperature for hatchability and egg development. The effect of (a) three diets (cassava leaves + cocoyam leaves + milk weed leaves; cassava leaves + pumpkin leaves + wandering Jew; and cassava leaves + lablab + Cinderella weed) on growth; and (b) incubation temperature (26, 28, 30, 32, and 34 °C) on egg hatchability and egg development time were studied. Cassava, pumpkin and milk weed leaves were the most ‘preferred’ of the tested plant leaves. Egg development time was longer at lower temperatures, ranging between 7-14 days across a 26-34 °C temperature range. The highest hatchability (95%) was observed at 28 °C, below and above which hatchability decreased. The maximum nymph weight (1.58 mg) at hatching was observed at 26 °C and decreased with increasing egg incubation temperature. The plant leaf diet containing leaves with highest protein content (pumpkin, wandering Jew and cassava) led to the highest growth and growth rate comparable to the control diet (broiler chick mash). Temperature had a significant effect on egg development time (P<0.001) and nymph weight at hatching (P<0.001) while the food type significantly influenced growth (P<0.001) and moulting time. The possibility of formulating a nutrient balanced, cost-effective, compound feed for cricket production should be investigated.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".