Effects of dietary fishmeal substitution with corn gluten meal and poultry meal on growth rate and flesh characteristics of Chinook salmon (Oncorhynchus tshawytscha)
Bibliographic record
Abstract
Abstract There is considerable interest in developing diets that maintain growth performance and market appeal for salmon aquaculture while relying less on fishmeal as a major ingredient. Here, we compared growth rate, survival, fat content, tissue colouration and carotenoid levels (astaxanthin) in Chinook salmon (Oncorhynchus tshawytscha) fed two diets. The first diet was a typical commercial salmon diet with 59% fishmeal content, while the second diet reduced the fishmeal content to 15% (75% reduction) and substituted 28% corn gluten meal and 16% poultry meal. Over an approximately 14-month growth period, we found no significant difference between fish fed the high fishmeal or low fishmeal diet in either growth rate or survival. Individuals fed the low fishmeal diet did have 25% higher total body fat percentage than those fed the high fishmeal diet. Individuals fed the low fishmeal diet also had flesh that was significantly less red than fish fed the high fishmeal diet. Carotenoid analysis confirmed that the change in tissue colour was the result of reduced astaxanthin levels in salmon fed the low fishmeal diet. Due to the importance of red tissue colour for the market appeal of salmon, the corn gluten and poultry meal diet is not viable for salmon aquaculture in its present formulation, but our results suggest further modifications to the diet that could mitigate this effect.
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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 | 0.001 |
| 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".