Research Article

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus)

Published: August 19, 2016
Genet. Mol. Res. 15(3): gmr8285 DOI: 10.4238/gmr.15038285

Abstract

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X1), body width (X5), distance from first dorsal fin origin to anal fin origin (X10), snout length (X16), eye diameter (X17), eye cross (X18), and slanting distance from snout tip to first dorsal fin origin (X19) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X1 + 7.728X5 + 1.973X10 - 7.024X16 - 4.400X17 - 3.338X18 + 2.138X19, with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X1), body width (X5), distance from first dorsal fin origin to anal fin origin (X10), snout length (X16), eye diameter (X17), eye cross (X18), and slanting distance from snout tip to first dorsal fin origin (X19) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X1 + 7.728X5 + 1.973X10 - 7.024X16 - 4.400X17 - 3.338X18 + 2.138X19, with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.