Effects of Replacement of Fish Oil with Microbial Oil (Schizochytrium sp. T18) on Membrane Lipid Composition of Atlantic Salmon Parr Muscle and Liver Tissues
Bibliographic record
Abstract
A 16-week feeding trial was conducted to investigate effects of replacing dietary fish oil (FO) with docosahexaenoic acid (DHA)-rich microbial oil (MO) from Schizochytrium sp. (T18) on membrane lipid composition of Atlantic salmon parr liver and muscle tissues. Four nutritionally balanced diets were formulated with varying levels of FO, MO, and canola oil (CO), including a control diet with 20% FO, a secondary control diet with 10% FO and 10% CO, and two experimental diets that completely replaced FO with a low (5%) and high (10%) proportion of MO. No significant differences were observed in growth parameters (81–98 g; weight gain), total lipid class composition, and total sterol content among the dietary treatments. However, there were significant differences in the proportions of individual ꞷ3 and ꞷ6 fatty acids in both liver and muscle tissues, reflecting the different dietary treatments. Notably, the presence of low eicosapentaenoic acid (EPA) in the MO diets did not affect the growth performance of the fish, suggesting a lower requirement for EPA in the diet and a greater necessity for DHA. The results also showed that DHA was present in very high proportions in the cellular membrane, particularly in muscle tissue, with low levels of linoleic acid and alpha-linolenic acid. Overall, the findings suggest that MO derived from Schizochytrium sp. (T18) could be a potential substitute for FO in the diet of farmed Atlantic salmon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 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".