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Genetic and phenotypic evaluation of harvest traits from a comprehensive commercial Atlantic salmon, Salmo salar L., broodstock program

2019· article· en· W2908416655 on OpenAlexaff
Amber F. Garber, Fatemeh Amini, Salvador A. Gezan, Bruce Swift, S.E. Hodkinson, J. T. R. Nickerson, Christopher J. Bridger

Bibliographic record

VenueAquaculture · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsHuntsman Marine Science Centre
Fundersnot available
KeywordsBiologySalmoPhenotypic traitHeritabilityBroodstockTraitQuantitative trait locusGenetic correlationSelective breedingZoologyPhenotypeGenetic variationGeneticsAquacultureFisheryGeneFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Twenty-two harvest carcass quantity and fillet quality traits, including nine calculated traits, were evaluated on 1496 North American origin farmed Atlantic salmon (mean weight ~5.5 kg) belonging to 81 families. Narrow-sense heritabilities along with a description of the variability of the traits, effects of sex and maturity status, and genetic and phenotypic correlations between the traits are presented and discussed. In addition, these traits are comprehensively compared to published results, when available, on Atlantic salmon and other fish species. All recorded carcass quantity traits were heritable (h2 = 0.30–0.48), indicating additive genetic control that can be exploited towards improvement, and their genetic and phenotypic correlations with one another are discussed. Quality traits related to melanin discoloration, gaping and marbling were less heritable (h2 = 0.04–0.15), but were at a reduced level overall in the group of salmon sampled. These secondary traits are considered useful as tracking traits to ensure their frequency does not increase over time due to genetic practices or to environmental factors that affect fish production. Fillet color was discussed from both visual and instrumental evaluation (h2 ≥ 0.42), including the negative and/or positive genetic and phenotypic correlations of varying degrees, making this trait difficult to incorporate into a selection index. Fillet color (all phenotypic measures) also lacked genetic and phenotypic correlations to fillet weight and other weight associated traits indicating that improvement in growth does not result in any changes in color. Calculated traits are presented related to yield, as these are often the most commonly discussed with commercial fish producers, resulting in moderate heritabilities (h2 = 0.14–0.27). Finally, implications of these harvest evaluation results to manage a commercial Atlantic salmon broodstock program are also discussed in detail.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.849
Threshold uncertainty score0.601

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)0.0010.000

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 head0.029
GPT teacher head0.259
Teacher spread0.230 · 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 designObservational
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

Citations25
Published2019
Admission routes1
Has abstractyes

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