Manure Valorization Using Black Soldier Fly Larvae: A Review of Current Systems, Production Characteristics, Utilized Feed Substrates, and Bioconversion and Nitrogen Conversion Efficiencies
Bibliographic record
Abstract
The growing demand for animal products leads to mounting environmental impacts from the livestock sector. In light of the desired transition from linear to circular nutrient flows and an increasing number of formal commitments toward reducing environmental impacts from livestock production, manure valorization using insects (particularly black soldier fly larvae; BSFL) gains increasing importance. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, this paper identified 75 BSFL production systems utilizing various types of manure as feed substrates. The review highlights considerable differences in system design regarding the different production steps and their specific characteristics. These differences lead to a wide spectrum of rearing performances, which were measured by a suite of indicators, including dry matter reduction (DMR), waste reduction index (WRI), feed conversion efficiency (FCE), bioconversion rate (BCR), and nitrogen reduction. The results further show that, to date, most manure-valorizing BSFL production systems operate at the micro-scale level. However, specific reduction targets for manure-related emissions will likely necessitate large-scale systems at the farm or industrial level, and further research should thus focus on the comprehensive assessment of potential environmental benefits of manure valorization using BSFL.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".