Genetic parameter estimations of new traits of morphological quality on gilthead seabream (Sparus aurata) by using IMAFISH_ML software
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AuthorsLeón-Bernabeu, S. (Sergi); Shin, H.S. (Hyun Suk); Lorenzo-Felipe, A. (Alvaro); García-Pérez, C. (Cathaysa); Berbel, C. (Concepción); Elalfy, I.S. (Islam Said); Armero, E. (Eva); Pérez-Sánchez, J. (Jaume); Arizcun-Arizcun, M. (Marta); Zamorano, M.J. (Maria Jesús); Manchado, M. (Manuel); Afonso, J.M. (Juan Manuel)
Non-invasive Technology (NiT)
In this study, a total of 18 novel productive traits, three related to carcass [cNiT] and fifteen related to morphometric [mNiT]), were measured in gilthead seabream (Sparus aurata) using Non-invasive Technologies (NiT) as implemented in IMAFISH_ML (MatLab script). Their potential to be used in industrial breeding programs were evaluated in 2348 offspring reared under different production systems (estuarine ponds, oceanic cage, inland tank) at harvest. All animals were photographed, and digitally measured and main genetic parameters were estimated. Heritability for growth traits was medium (0.25–0.37) whereas for NiT traits medium-high (0.24–0.61). In general, genetic correlations between mNiT, cNiT and growth and traits were high and positive. Image analysis artifacts such as fin unfold or shades, that may interfere in the precision of some digital measurements, were discarded as a major bias factor since heritability of NiT traits after correcting them were no significantly ...
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