Abstract:

Effects of 17 morphometric traits on body weight of Megalobrama amblycephala were analyzed, using correlation analysis and path analysis. The total of 240 individuals were chosen for body length, head length, head depth, head width, caudal peduncle length, caudal peduncle width, pre-dorsal-length, pre-orbital-length, post-orbital-length, length of dorsal fin, length of anal fin, pre-pelvic-distance, pre-anal-distance, distance between the nostrils and left eye diameter measurements. Results of correlation analysis showed that there were significantly correlations between most of morphometric traits and body weight (P < 0.01). According to the regression coefficient test, 6 morphometric traits were excluded from the optimal multiple linear regression equation, y = -1226.370 + 14.749P1 + 46.953P2 + 29.983P3 + 10.082P4 - 52.755P5 + 27.823P6 + 21.749P7 + 10.444P8 - 29.445P9 + 53.868P10 (P < 0.05). Path analysis results indicated that the body depth and total length could well predict body weight, since their path coefficients were largest, 0.326 and 0.272, respectively. The power of regression equation of body weight on total length was close to 3, indicating the body weight of M. amblycephala grows isometrically with its total length and body depth., Effects of 17 morphometric traits on body weight of Megalobrama amblycephala were analyzed, using correlation analysis and path analysis. The total of 240 individuals were chosen for body length, head length, head depth, head width, caudal peduncle length, caudal peduncle width, pre-dorsal-length, pre-orbital-length, post-orbital-length, length of dorsal fin, length of anal fin, pre-pelvic-distance, pre-anal-distance, distance between the nostrils and left eye diameter measurements. Results of correlation analysis showed that there were significantly correlations between most of morphometric traits and body weight (P < 0.01). According to the regression coefficient test, 6 morphometric traits were excluded from the optimal multiple linear regression equation, y = -1226.370 + 14.749P1 + 46.953P2 + 29.983P3 + 10.082P4 - 52.755P5 + 27.823P6 + 21.749P7 + 10.444P8 - 29.445P9 + 53.868P10 (P < 0.05). Path analysis results indicated that the body depth and total length could well predict body weight, since their path coefficients were largest, 0.326 and 0.272, respectively. The power of regression equation of body weight on total length was close to 3, indicating the body weight of M. amblycephala grows isometrically with its total length and body depth.