Inclusion of Dried Black Soldier Fly Larvae in Free-Range Laying Hen Diets: Effects on Production Efficiency, Feed Safety, Blood Metabolites, and Hen Health
Bibliographic record
Abstract
Identifying alternative feedstuffs to replace conventional nutrient sources in poultry diets is crucial to supplying the growing demand for animal feed. A 17-week-long feeding experiment with three diets, including 0% (control), 10%, and 18% full-fat dried black soldier fly larvae (DBSFL), was conducted to evaluate the production efficiency and feed safety of using the larvae for partial (50%) and full (100%) substitutions of soybean meal and 90% replacement of soybean oil in free-range laying hen diets. Thirty hens (18–36 weeks old) were housed in two mobile poultry trailers per treatment level. The weight gain of hens, their feed intake, egg production, egg weights, feed conversion ratios, bird welfare parameters, hematology and blood metabolites, fecal microbiology, and digestive tract weights were examined. Control hens had higher weight gains, laid more and bigger eggs while consuming less feed, and had lower feed conversion ratios than 18% DBSFL hens. However, the production performances of 10% DBSFL hens were not significantly different from the control in many of the parameters considered (e.g., hen-day egg production or HDEP). In conclusion, partial replacement of soybean meal and oil with DBSFL in layer diets maintains production efficiency, feed safety, and hen health and welfare status.
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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 | 0.000 |
| 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".