Individual growth monitoring of European sea bass larvae by image analysis and microsatellite genotyping

De Verdal Hugues, Vandeputte Marc, Pepey Elodie, Vidal Marie-Odile, Chatain Béatrice. 2014. Individual growth monitoring of European sea bass larvae by image analysis and microsatellite genotyping. Aquaculture, 434 : 470-476.

https://doi.org/10.1016/j.aquaculture.2014.09.012

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Quartile : Q1, Sujet : FISHERIES / Quartile : Q2, Sujet : MARINE & FRESHWATER BIOLOGY

Résumé : The aims of the present study were to develop non-lethal methods to identify individual fish larvae and post-larvae before tagging and accurately follow their growth characteristics. European sea bass (Dicentrarchus labrax) was used as a model species at four different ages ranging from 71 to 100 days post fertilization (dpf). Two different methods were tested for non-lethal tissue sampling from each larva for DNA analysis: 1) using a sterile absorbent paper to sample mucus and/or epithelial cells by rubbing the fish skin and 2) fin-clip of the bottom part of the caudal fin. Whatever the age of the larvae, the genotyping rate (at 12 microsatellite markers) was low with the use of sterile absorbent paper but relatively high with fin-clip sampling at 80 and 87 dpf (on average 17 and 63% of the loci genotyped for sterile paper and fin clips, respectively). Several measurements were performed on digital pictures of sea bass larvae to model body weight. Using area, perimeter, length, height and volume, it was possible to estimate body weight with a coefficient of determination r2 = 0.98 on very small larvae (body weight ranging from 20.0 to 419.3 mg). The present results suggested that individual monitoring of the growth of European sea bass larvae can be achieved by combining image analysis and microsatellite genotyping as early as 87 dpf or 236 mg mean body weight.

Mots-clés Agrovoc : larve de poisson, Dicentrarchus labrax, identification, testage non destructif, croissance, poids corporel, surface, génotype, analyse d'image, microsatellite, marqueur génétique, modèle de simulation