Estimation of genetic parameters for body areas in Nile tilapia measured by digital image analysis

Abstract

Digital image analysis is a practical, non‐invasive, and relatively low‐cost tool that may assist in the evaluation of body traits in Nile tilapia, being particularly useful for assessing difficult‐to‐measure variables, such as body areas. In this study, we aimed to estimate variance components and genetic parameters for body areas of Nile tilapia obtained by digital images. The data set comprised body weight (BW) records of 1,917 pond‐reared fish at 366 days of age. Of this total, 656 animals were photographed and subjected to image analysis of trunk area (TA), head area (HA), caudal fin area (CFA) and fillet area (FA). Heritabilities and genetic correlations were estimated through multiple‐trait models based on Bayesian inference. Heritability estimates for BW, TA, HA, CFA and FA were 0.25, 0.23, 0.26, 0.21 and 0.25, respectively. Genetic correlations between the traits were high and positive, ranging from 0.70 to 0.98. We highlight the genetic correlation between BW and TA (rG = 0.98) and FA (rG = 0.97). In view of the observed results, it can be concluded that trunk and fillet areas obtained by digital image analysis can lead to indirect genetic gains in weight and other body areas. In addition, the areas studied have potential as a selection criterion and may assist in studies on changes in the body shape in Nile tilapia.

Additive‐genetic relationships of growth and morphometrics to meat yield traits in Macrobrachium nipponense (De Haan, 1849)

“…The phenotypic and genetic correlations between AW and growth were found to be very high and positive in two sexes of M. nipponense . This is consistent among species such as economic crustaceans and fishes (Campos‐Montes et al, 2017; Da‐Silva‐Cardoso et al, 2021; Fraslin et al, 2018; Gjerde et al, 2012; Hung et al, 2013; Kause et al, 2007; Kocour et al, 2007; Lutz & Wolters, 1999; Navarro et al, 2009; Neira et al, 2004; N. H. Nguyen, Ponzoni, et al, 2010; Pérez‐Rostro & Ibarra, 2003; Rutten et al, 2005; Thodesen et al, 2012; Wang et al, 2020). In contrast, the strength and directionality of genetic correlations between growth/morphometrics and meat yield are not that consistent, depending on species, sex, and ontogenetic stage.…”

Heritability Estimates of Growth-Related Traits in Oriental River Prawns, Macrobrachium nipponense

“…Although genetic markers can be used to construct families, the cost would be prohibitively high for this study. Tus, the individual animal model used by some researchers such as Joshi et al [43] and Cardoso et al [45] was not appropriate for the data analysis in this study. In many aquaculture species, individual animal identifcation is a challenge, which was the case in the current study.…”

A breeding program for Nile tilapia in Brazil: Results from nine generations of selection to increase the growth rate in cages

“…Therefore, with the aim of increasing the benefit of our breeding programs and supplying the market demands, we are studying new traits to consider as selection criteria, as a selection index or for their potential for creating new lines. Reproductive potential, uniformity of harvest weight, feed efficiency, body shape and predicted fillet yield by two-and threedimensional image analysis (Cardoso et al, 2021), meat quality, skin quality for biological dressings use, behaviour, and welfare are the target traits for the present breeding program. In addition, studies exploring the genetic variation in sexual dimorphism may be important for the commercial value of the animals, in addition to the genotype and environmental interactions in different production systems (Araújo et al, 2020).…”