Socio-economic and environmental implications of replacing conventional poultry feed with insect-based feed in Kenya
Bibliographic record
Abstract
The growing scarcity of resources for feed production and environmental concerns highlight the unsustainability of conventional feed sources. Insect farming is considered as an alternative feed due to its low land and water requirements, its low ecological footprint , and circular economy contribution by converting biowaste into high-quality feed ingredients. While there is growing research on the technical feasibility and nutritional performance of insect-based feed, its potential beneifts are not quanitified. Using experimental and secondary data, we assess the potential socio-economic benefits of black soldier fly larvae meal (BSFLM) to the Kenyan poultry sector. We find that replacing 5–50% of the conventional feed sources (fishmeal, maize, and soya bean meal) by BSFLM can generate a potential economic benefit of 69–687 million USD (0.1–1% of the total GDP) and 16–159 million USD (0.02–0.24% of the GDP) if the entire poultry sector (the commercial poultry sector) adopts BSFLM. These could translate to reducing poverty by 0.32–3.19 million (0.07–0.74 million) people, increasing employment by 25,000–252,000 (3300–33,000) people, and recycling of 2–18 million (0.24–2 million) tonnes of biowaste. Further, our findings show that replacing the conventional feeds by 5–50% BSFLM in the commercial poultry sector would increase the availability of fish and maize that can feed 0.47–4.8 million people at the current per capita of fish and maize consumption in Kenya. Similarly, the foreign currency savings can increase by 1–10 million USD by reducing feed and inorganic fertilzer importation. These findings suggest that greater investment to promote BSFLM could boost economic, environmental and social sustainability.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".