FN Archimer Export Format
PT J
TI Morphological predictors of slaughter yields using 3D digitizer and their use in a common carp breeding program
BT 
AF Prchal, Martin
   Kocour, Martin
   Vandeputte, Marc
   Kause, Antti
   Vergnet, Alain
   Zhao, Jinfeng
   Gela, David
   Kašpar, Vojtěch
   Genestout, Lucie
   Bestin, Anastasia
   Haffray, Pierrick
   Bugeon, Jérôme
AS 1:1;2:1;3:2;4:4;5:3;6:1;7:1;8:1;9:5;10:6;11:6;12:7;
FF 1:;2:;3:;4:;5:PDG-RBE-MARBEC-LSEA;6:;7:;8:;9:;10:;11:;12:;
C1 University of South Bohemia in České Budějovice, Faculty of Fisheries and Protection of Waters, South Bohemian Research Center of Aquaculture and Biodiversity of Hydrocenoses, Zátiší 728/II, 389 25 Vodňany, Czech Republic
   INRAE, GABI,, AgroParisTech, Université Paris-Saclay, 78350 Jouy-en-Josas, France
   Ifremer, Chemin de Maguelone, F-34250 Palavas-les-Flots, France
   Natural Resources Institute Finland (Luke), Biometrical Genetics, Myllytie 1, FI-31600 Jokioinen, Finland
   LABOGENA-DNA, 78350 Jouy-en-Josas, France
   SYSAAF, LPGP/INRA, Campus de Beaulieu, F-35042 Rennes, France
   INRAE, LPGP, 35000 Rennes, France
C2 UNIV SOUTH BOHEMIA, CZECH REPUBLIC
   INRAE, FRANCE
   IFREMER, FRANCE
   NAT RESOURCES INST FINLAND LUKE, FINLAND
   LABOGENA-DNA, FRANCE
   SYSAAF, FRANCE
   INRAE, FRANCE
SI PALAVAS
SE PDG-RBE-MARBEC-LSEA
IN WOS Ifremer UPR
   copubli-france
   copubli-p187
   copubli-europe
IF 4.242
TC 7
UR https://archimer.ifremer.fr/doc/00604/71625/70070.pdf
LA English
DT Article
DE ;Fillet yields;3D predictors;Genetic parameters;Indirect selection;Breeding program
AB 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_P2 – 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. 
PY 2020
PD APR
SO Aquaculture
SN 0044-8486
PU Elsevier BV
VL 520
UT 000515498200081
DI 10.1016/j.aquaculture.2020.734993
ID 71625
ER

EF