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Morphological predictors of slaughter yields using 3D digitizer and their use in a common carp breeding program

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F20%3A43900843" target="_blank" >RIV/60076658:12520/20:43900843 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.1016/j.aquaculture.2020.734993" target="_blank" >https://doi.org/10.1016/j.aquaculture.2020.734993</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1016/j.aquaculture.2020.734993" target="_blank" >10.1016/j.aquaculture.2020.734993</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Morphological predictors of slaughter yields using 3D digitizer and their use in a common carp breeding program

  • Original language description

    Slaughter yields are traits of high interest especially for fish species sold in processed form like headless carcass or fillets, as well as with regard to increasing consumer preference for easy-to-prepare fish products. However, slaughter yields cannot be measured on live fish and thus their genetic improvement through mass selection is impossible. The usual alternatives are sib selection and/or indirect selection on correlated traits or morphological predictors of slaughter yields. In the present study, we assessed the possibility of using a combination of 3D digitized landmarks and ultrasound measurements in genetic improvement of slaughter yields in common carp. DNA pedigreed market-size carp (n = 1553 fish) were produced from a partial factorial design of 20 dams and 40 sires. Morphological predictors were recorded in real-time using a 3D digitizer and ultrasound tomography, and combined by multiple linear regression to predict slaughter yields. The 3D model-predicted headless carcass and fillet yields explained 59% and 50%, respectively, of the total phenotypic variation in slaughter yields. Genetic parameters of model-predicted yields and of the best individual predictor (3D-P-2- ratio between abdominal fillet thickness E8 and external 3D ventral height) were similar or slightly lower when compared to previous 2D-based predictors (Prchal et al., 2018a, 2018b, 2018c). This was also the case for the expected genetic gain using indirect selection on the same simple predictor for fillet yield improvement (0.48% fillet units for 3D vs. 0.52% for 2D). 3D model-predicted yields and especially simple predictors thus have a solid potential for genetic improvement of slaughter yields in common carp. While they are not better than 2D predictors, they are much more convenient and faster to collect in the field, as they do not imply post-processing of images. These practical aspects should be taken into account in the future carp breeding program.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    40103 - Fishery

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Aquaculture

  • ISSN

    0044-8486

  • e-ISSN

  • Volume of the periodical

    520

  • Issue of the periodical within the volume

    neuveden

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    9

  • Pages from-to

  • UT code for WoS article

    000515498200081

  • EID of the result in the Scopus database

    2-s2.0-85078178643