Abstract:The morphological variations and discriminant methods of Channa argus (♂)，C.maculata (♀) and their hybrid were studied using traditional morphometrics and the truss network analysis.Body color of C.argus,C.maculata and their hybrid were observed.The results showed significant differences between C.argus and C.maculata from stripe at top of head,side and base of caudal fin,and the hybrid resembled C.maculata from body color.Among eleven meristic characters,the numbers of soft ray of pelvic fin were consistent in these three species,and the numbers of soft ray of pectoral fin deviated from its male parent’s species.The other meristic characters were within the range of its parent’s,the average hybrid index was calculated to be 53.45.The chi-square analysis of meristic characters showed that:there were significant differences(P<0.05) or greater significant differences(P<0.01) between C.argus and C.maculata except the number of pectoral fin rays; greater significant differences(P<0.01) between C.argus and the hybrid except the number of tail fin rays,gill rakers,lateral line scales and scales below lateral line; and significant differences(P<0.05) or greater significant differences(P<0.01) between C.maculata and the hybrid except the number of tail fin rays and gill rakers.Among meristic characters,the number of dorsal fin rays,lateral line scales and scales above lateral line can be used as preliminary indicators to determine the three species.Among ten measurable characters,the average hybrid index was calculated to be 73.90,indicating the measurable character inclined to its male parent’s species (C.argus).Cluster analysis,discriminant analysis and principal component analysis were applied to the measurable character data and the truss network data.The results indicated that the hybrid resembled C.argus from body shape,and there were greater morphological differences among C.argus,C.maculata and their hybrid.Differences between them involved the entire body.Three species could be distinguished by using the 3 formulae established with discriminant analysis which the discrimination accuracy was 100.0%.