Multivariate analysis using morphometric and ultrasound information for selection of tilapia (Oreochromis niloticus) breeders

Abstract

This study evaluated morphometric and ultrasound information of tilapia (O. niloticus) breeders through multivariate analysis. We applied correlation, clustering, and principal component analysis to a dataset composed of information from 222 male and female breeders of the improved GIFT strain. The body weight, objective of the breeding program, showed a high positive correlation with most of the morphometric parameters. The formation of clusters indicated characteristics responsible for muscle composition and carcass weight. Some characteristics showed a high correlation, such as body weight and fillet weight (0.98 and 0.94 for females and males, respectively), and a high contribution to the explanation of data variability; of the total characteristics evaluated for females, two explained 75% data variability and four explained 72% for males. We concluded that it is possible to reduce the number of characteristics measured, as well as use information of average daily weight gain and body weight to select female and male breeders, respectively, to drive genetic gains favoring more productive generations