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Pigmentation of Pacific White Shrimp, <i>Litopenaeus vannamei,</i> by Dietary Astaxanthin Extracted from <i>Haematococcus pluvialis</i>

2011· article· en· W1994144450 on OpenAlexaff
Zhi Yong Ju, Dong‐Fang Deng, Warren G. Dominy, Ian Forster

Bibliographic record

VenueJournal of the World Aquaculture Society · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsFisheries and Oceans Canada
FundersMerckU.S. Department of Agriculture
KeywordsHaematococcus pluvialisShrimpLitopenaeusAstaxanthinBiologyFood scienceCarotenoidShellfishFisheryAnimal scienceFish <Actinopterygii>Aquatic animal

Abstract

fetched live from OpenAlex

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 &lt; 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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.808

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.021
GPT teacher head0.219
Teacher spread0.198 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations75
Published2011
Admission routes1
Has abstractyes

Explore more

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