Optimization of a hatchery residue fermentation process for potential recovery by black soldier fly larvae
Bibliographic record
Abstract
The conventional management of hatchery residues (HR) poses environmental issues and health risks for handlers. This study evaluates the potential of fermentation to reduce pathogens and odors in HR, enabling them to be recovered into feed using black soldier fly. This saprophagous edible insect is valued for its ability to efficiently bioconvert organic residues into high-quality biomass. Due to the low carbohydrate content of HR, whey permeate was added at lactose inclusion levels of 0, 5, 15, 25, and 35% (dry basis) to optimize fermentation. Using a commercial ferment starter culture (0.3%, wet basis), HR were fermented under semi-anaerobic conditions for two weeks. Fermentation metrics, including pH, microbiological loads (total aerobic mesophilic, presumptive lactic acid bacteria, coliforms, Escherichia coli), volatile fatty acids, and volatile organic compounds, were monitored at days 0, 3, 7, and 14. Optimal stabilization was achieved with lactose inclusion of 15 to 35% after 7 days, which reduced pH (<5.3), increased lactic (87.82 mg/g) and acetic (20.28 mg/g) acid production, and decreased coliform and Escherichia coli counts below detection limit (1.7 log cfu/g). The production of compounds associated with unpleasant odors was also limited. The use of a ferment did not result in a greater reduction of coliform counts, the initial loads of lactic acid bacteria (> 7 log cfu/g) being sufficient to initiate spontaneous fermentation. However, ferment was found to be efficient in heated HR. These findings demonstrate the effectiveness of fermentation for stabilizing HR, highlighting its potential for integration into insect bioconversion systems.
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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 | 0.001 |
| 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".