Pigmentation of Pacific White Shrimp, <i>Litopenaeus vannamei,</i> by Dietary Astaxanthin Extracted from <i>Haematococcus pluvialis</i>
Bibliographic record
Abstract
This study investigated the effectiveness of dietary supplementation of astaxanthin (Ax) from the Haematococcus pluvialis on growth, survival, and pigmentation in Pacific white shrimp. Ten test diets were processed to contain five levels of Ax (25, 50, 75, 100, and 150 mg/kg as fed basis) by adding the natural or synthetic Ax to a basal diet containing no Ax. Each diet and a commercial shrimp feed were fed to four replicate tanks of shrimp (12 shrimp/tank) for 8 wk. Neither the natural nor synthetic Ax affected shrimp growth or survival. After cooking, shrimp fed the diets containing the natural Ax exhibited a strong red color, compared to the light pink color of shrimp fed the remaining diets. Colorimetric readings and Ax content in cooked shrimp demonstrated that the natural esterified Ax had greater pigmentation efficiency than synthetic free Ax (P < 0.05). The Ax contents in shrimp tail muscle demonstrated significant correlation with the levels of dietary Ax. The supplementation level of the natural Ax for optimum pigmentation efficiency is in a range of 75–100 mg/kg diet. The Ax product used in this study contained only a small amount (ca. 5.0%) of other carotenoids, indicating that the high pigmentation efficiency was mainly due to algal esterified Ax.
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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) | 0.001 | 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".