New Perspectives in Fisheries: The Use of Insects in Aquaculture
Bibliographic record
Abstract
In the face of climate change and variability and the need to enhance aquaculture production sustainability, production and utilization of novel feed resources for aquaculture while maintaining or contributing to environmental sustainability is critical. Insects have been shown to produce critical biomass suitable for animal feed with minimal environmental footprints. The insect biomass has been shown to be of high nutritional quality and therefore can be used as feed for fish. Fish feed formulations have been successfully done and incorporated diets for various fish species with very positive results. The incorporation of the insect meals in aquafeeds has also been shown to reduce the cost of fish feeds and improve the overall profitability of fish farming enterprises. In this chapter, the utilization of insect meals in the formulation of aquafeeds and the effect on the performance of fish is presented. This includes the replacement of fishmeal as the main animal protein source in fish feeds and the nutritional quality of insect meals as important sources of proteins for green, profitable, and sustainable aquaculture. It is certain that in the near future, large-scale insect farming and processing to produce insect meals as an ingredient of fish feeds will have positive impact on the sustainability and profitability of aquaculture.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 0.008 |
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".