Development of an economic prediction tool for hatchery residue valorisation systems through fermentation and black soldier fly bioconversion in Quebec
Bibliographic record
Abstract
Abstract Hatchery residue valorisation through fermentation and black soldier fly larval bioconversion offers a promising alternative to conventional management. However, assessing the technical and economic feasibility of such systems is essential before implementation. While financial planning tools already exist, they require adaptation to specific production models, scales, and regional contexts. This study aimed to develop a feasibility assessment tool designed for a Quebec-based valorisation system. The tool incorporates two production models: centralised (110 tonnes per week (tpw)) and decentralised (10, 15, or 25 tpw), while evaluating the use of two fermentation co-products (dry or liquid whey permeate), two integration levels for reproduction (in-house or external supply of neonates), and two packaging options (bulk or retail). In total, 32 theoretical production scenarios were analysed. Infrastructure and equipment requirements were derived from supplier quotations and a pre-engineering report for black soldier fly processing facilities. The tool estimates operational costs, including labour, inputs, energy, and maintenance, as well as financial considerations such as loan repayments for capital expenditures. Revenues from the sale of dried larvae (pet food market) and composted frass (organic fertiliser) are included, enabling the calculation of annual profits based on the production model and site capacity. Although secondary processing scenarios are excluded, the tool provides a comprehensive overview of the costs associated with implementing and operating such a system. It considers regional factors, including the availability of inputs and the challenges posed by Quebec’s northern climate, making it a relevant tool for producers exploring alternative ways of managing hatchery residues.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".