Evidence map›Paper›PMID 34306010›Full record

ArticleFrontiers in genetics2021

Genomic Prediction for Whole Weight, Body Shape, Meat Yield, and Color Traits in the Portuguese Oyster

Sang V Vu, Wayne Knibb, Cedric Gondro, Sankar Subramanian, Ngoc T H Nguyen, Mobashwer Alam, Michael Dove, Arthur R Gilmour, In Van Vu, Salma Bhyan and 4 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Sang V VuGeneCology Research Centre, University of the Sunshine Coast, Sippy Downs, QLD, Australia.
Wayne KnibbGeneCology Research Centre, University of the Sunshine Coast, Sippy Downs, QLD, Australia.
Cedric GondroDepartment of Animal Science, College of Agriculture and Natural Resources, Michigan State University, East Lansing, MI, United States.
Sankar SubramanianGeneCology Research Centre, University of the Sunshine Coast, Sippy Downs, QLD, Australia.
Ngoc T H NguyenNorthern National Broodstock Center for Mariculture, Research Institute for Aquaculture Number 1, Hai Phong, Vietnam.
Mobashwer AlamQueensland Alliance for Agriculture and Food Innovation, The University of Queensland, Saint Lucia, QLD, Australia.
Michael DoveNSW Department of Primary Industries, Port Stephens Fisheries Institute, Taylors Beach, NSW, Australia.
Arthur R GilmourConsultant, Orange, NSW, Australia.
In Van VuNorthern National Broodstock Center for Mariculture, Research Institute for Aquaculture Number 1, Hai Phong, Vietnam.
Salma BhyanGeneCology Research Centre, University of the Sunshine Coast, Sippy Downs, QLD, Australia.
Rick TearleSchool of Animal and Veterinary Science, The University of Adelaide, Adelaide, SA, Australia.
Le Duy KhuongFaculty of Environment, Ha Long University, Uong Bi, Vietnam.
Tuan Son LeResearch Institute for Marine Fisheries, Ngo Quyen, Hai Phong, Vietnam.
Wayne O'ConnorGeneCology Research Centre, University of the Sunshine Coast, Sippy Downs, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genetic improvement for quality traits, especially color and meat yield, has been limited in aquaculture because the assessment of these traits requires that the animals be slaughtered first. Genotyping technologies do, however, provide an opportunity to improve the selection efficiency for these traits. The main purpose of this study is to assess the potential for using genomic information to improve meat yield (soft tissue weight and condition index), body shape (cup and fan ratios), color (shell and mantle), and whole weight traits at harvest in the Portuguese oyster,

Indexed as

genetic improvementgenetic parametersgenomic selectionhigh density SNP markersprediction accuracy

Identifiers

PMID34306010
PMCPMC8298027

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.