Efficiency of Rearing the African Palm Weevil (Rhynchophorus phoenicis) in Different Substrates as Arsenal for Addressing Malnutrition in Children
Bibliographic record
Abstract
Background: Rhynchophorus phoenicis is arguably one of the most sought-after edible insects in the tropics. It is widely distributed in Africa and is a major pest of palm trees in Africa, Southern Asia, and South America. Globally, the population has been predicted to surpass 9 billion by 2050, leading to food insecurity. Objective: This research investigated rearing the edible insect (Rhynchophorus phoenicis) in different substrates under laboratory conditions to address problems associated with the weevils' availability for solving malnutrition issues in children when consumed. Methods: Ten (10) adult palm weevils were reared in different substrates (coconut husk, sugarcane, pawpaw, and a combination of all the substrates) under laboratory conditions with palm fiber as the control and arranged in triplicates to assess their emergence and survival. Data on larvae emergence, survival, and pupation were obtained within four (4) to eight (8) weeks post-emergence. Results: The rearing experiments showed that larvae emergence and survival (184.08±19.7), pupation rate (53.25±7.0), and adult emergence (12.92±1.8) were highest in coconut husk and least in pawpaw substrate. There was also a significant difference between the larvae emergence and survival, pupation, and adult emergence in the various substrates compared to the control (p<0.05). Implication: The study demonstrated the feasibility of mass-rearing African palm weevil (Rhynchophorus phoenicis) larvae, which, if incorporated into children's diets, will be immensely significant in solving nutritional deficiencies and problems associated with malnutrition.
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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) | 0.001 | 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 | 0.000 |
| 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".