Apparent Digestibility of Macronutrients and Fatty Acids from Microalgae (Schizochytrium sp.) Fed to Rainbow Trout (Oncorhynchus mykiss): A Potential Candidate for Fish Oil Substitution
Bibliographic record
Abstract
Aquaculture feed formulation has recently turned its focus to reduce the reliance on marine-derived resources and utilise alternative feedstuffs, as an approach to improve the environmental sustainability of the aquaculture sector. The fish oil market is highly volatile, and availability of this commodity is continuously decreasing for use in aquaculture. Currently, a growing number of commercial efforts producing microalgae are providing omega 3-rich oil for sustainable aquaculture feed. This study was focused to determine the nutrient digestibility of a marine microalga, Schizochytrium spp., which is rich in docosahexaenoic acid (DHA) and long-chain polyunsaturated fatty acids (LC-PUFA), as a novel dietary lipid source that could be utilized effectively by rainbow trout (Oncorhynchus mykiss). A whole-cell Schizochytrium spp. biomass was used in the digestibility experiment at two different temperatures, 8 °C and 15 °C. No significant differences were detected between the two temperatures for the apparent digestibility coefficients (ADCs) of the dry matter (94.3 ± 4.9%), total lipids (85.8 ± 0.0%), crude proteins (89.5 ± 1.8%), energy (83.1 ± 1.7%) and fatty acids (85.8 ± 7.5%). The ADCs of the nutrients, energy, DHA and other fatty acids showed that Schizochytrium spp. is a high-quality candidate for fish oil substitution and supplement of LC-PUFA in fish feed with vegetable oils.
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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 | 0.000 |
| 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 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".