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Record W2500304524 · doi:10.1111/jwas.12310

Cod Larviculture Using High‐density Rotifer Production with Different Enrichments

2016· article· en· W2500304524 on OpenAlexaff
Rémy Haché, Sébastien Plante, Benjamin S. Forward, Fabrice Pernet

Bibliographic record

VenueJournal of the World Aquaculture Society · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsResearch and Productivity CouncilVancouver Coastal Health
Fundersnot available
KeywordsRotiferBiologyEicosapentaenoic acidDocosahexaenoic acidFood scienceTemperature gradient gel electrophoresisLarvaArachidonic acidAquacultureIchthyoplanktonFatty acidZoologyAnimal sciencePolyunsaturated fatty acidBiochemistryFisheryEcologyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract High‐density ( HD ) rotifer culture systems have been recently commercialized, but are not commonly used by the aquaculture industry. The aim of this study was to determine if HD systems could be used in cod hatcheries. An enrichment strategy using the commercial products, ArteMac and Protein Selco Plus (Com), was compared with the manufacturer's suggested enrichment, using Pavlova‐ DHA (Pav). The Pav enrichment increased the eicosapentaenoic acid ( EPA ) levels in rotifers, but reduced the docosahexaenoic acid ( DHA ) and 22:5n‐6 (n‐ 6DPA , docosapentaenoic acid) levels. Larvae EPA levels in both polar and neutral lipids were relatively stable in the larvae fed with Com‐rotifers; while they were higher in early stages, they were progressively reduced through ontogeny in the Pav‐rotifers fed‐larvae. DHA levels in polar lipids decreased in larvae, particularly when fed with HD ‐Pav rotifers. In all larvae, arachidonic acid ( ARA ) levels increased in the polar and neutral lipids, regardless of treatments. In both lipid fractions, the levels of ARA were quite stable in time, but still higher in larvae fed with Com‐rotifers. Bacterial load was lower in larvae fed with Pav‐rotifers. Denaturing gradient gel electrophoresis ( DGGE ) bacterial profiles of larvae and rotifers were all similar. This study shows the potential of using HD systems to produce rotifers, but highlights the necessity of adjusting the nutritional composition of rotifers prior to being fed to larvae.

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 score0.622
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

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

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 head0.013
GPT teacher head0.214
Teacher spread0.201 · 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

Citations4
Published2016
Admission routes1
Has abstractyes

Explore more

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