Abstract

The development of image analysis systems has facilitated progress and diversification of morphological methods and expands the potential for using morphometry as a tool for fisheries management. This study aims to elucidate morphological structure of Thinlip mullet Liza ramada from Samandag and Arsuz Coasts in Northeastern Mediterranean using BioMorph software. The morphometric data set were generated from each sampled individual images, and the obtained morphometric landmarks on fish image were subjected to multivariate analyses to elucidate population differentiation. In discriminant function analysis, overall random assignment of individuals into their original population was 95% that 86.4% and 100% of cross-validated grouped individuals of Arsuz and Samandag populations were classified into their original population, respectively. In Principal component analysis, 19 principal components were produced of which first and second PCs explained 77 and 5 % of the variation. Examination of the contribution of each morphometric character to the first and second PCs indicated that the observed differences were mainly from the dorsal and height measurements, demonstrating these characters to be important in the description of the population specifications.