Alain Vergnet, Sylvain Bonhommeau, Michel Renovell, Serge Bernard, Mohamed Belhaj, Achraf Lamlih, Vincent Kerzérho, Mohan Julien, Eloïse Detrez, Hugues de Verdal, Fathi Ben Ali, Fabien Soulier, Tristan Rouyer, Smart Integrated Electronic Systems (SmartIES), Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier (LIRMM), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UR226, Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), and ANR-16-CONV-0004,DIGITAG,Institut Convergences en Agriculture Numérique(2016)
International audience; Fish oocyte development monitoring is a mandatory operation when studying breeding in captivity as well as in the wild. In aquaculture, it is required to determine the best fertilization time. In the wild, it helps to detect spawning grounds, the distribution of fish species and the interaction between animals and their environment. In both settings, the conventional technique for developmental stage identification consists of handling the fish for oocyte sampling and sample observation using a binocular zoom head. Such an operation is difficult for the operator as well as for the fish. There is a need for repeated anesthesia and oocyte sampling, and it relies on operator expertise to identify the developmental stage. In this context, this publication proposes, for the first time, to study the potential of bioimpedance measurement as an alternative in fish breeding studies. We have set up an experiment combining the in vitro bioimpedance measurement of sampled oocytes with the conventional estimation technique for 69 sampled collected on farmed European sea bass. The statistical analysis has demonstrated that three of the four main developmental stages can be identified using bioimpedance measurement. The integrability of the bioimpedance technique with its implantable sensor makes this potential alternative approach very promising. Thanks to this sensor it could be possible, for the first time ever, to monitor in vivo the oocyte developmental stage in captivity as well as in the wild.