Spotted Wolffish Broodstock Management and Egg Production: Retrospective, Current Status, and Research Priorities
Bibliographic record
Abstract
) eggs hatched in Norway in the mid-1990s as this species was considered by Norwegian authorities to be a top candidate species for cold-water aquaculture in the North Atlantic regions. Previous research conducted in Norway (since 1992) and Canada (since 2000), focused on identifying key biological parameters for spotted wolffish cultivation which led, respectively, to the rapid establishment of a full commercial production line in northern Norway, while Québec (Canada) is witnessing its first privately driven initiative to establish commercial production of spotted wolffish on its territory. The control of reproduction can be viewed as a major requirement to achieve the development of performant strains using genetic selection tools and/or all-year-round production to bring about maximal productivity and synchronization among a given captive population. Although the basic reproduction aspects are more understood and controlled there are still some challenges remaining involving broodstock and upscaling of operations that limit the achievement of a standardized production at the commercial level. Quality of gametes is still considered a major constraint and it can be affected by multiple factors including nutrition, environmental conditions, handling practices, and welfare status. Internal insemination/fertilization and the protracted incubation period are challenging as well as the establishment of a health monitoring program to secure large-scale operations. The profound progress achieved in the control of reproduction, sperm handling, and cryopreservation methods for this species is presented and discussed. In this review, we also go into detail over the full range of up-to-date cultivation practices involving broodstock and identify areas that could benefit from additional research efforts (i.e., broodstock nutrition, health and welfare, scaling-up egg and larval production, genetics, and development of selective breeding programs).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".