Cluster Analysis of Longidorus Species (Nematoda: Longidoridae), a New Approach in Species Identification


  • Weimin Ye
  • R. T. Robbins


hierarchical, cluster analysis, identification, longidorus, morphometrics


Hierarchical cluster analysis based on female morphometric character means including body length, distance from vulva opening to anterior end, head width, odontostyle length, esophagus length, body width, tail length, and tail width were used to examine the morphometric relationships and create dendrograms for (i) 62 populations belonging to 9 Longidorus species from Arkansas, (ii) 137 published Longidorus species, and (iii) 137 published Longidorus species plus 86 populations of 16 Longidorus species from Arkansas and various other locations by using JMP 4.02 software (SAS Institute, Cary, NC). Cluster analysis dendograms visually illustrated the grouping and morphometric relationships of the species and populations. It provided a computerized statistical approach to assist by helping to identify and distinguish species, by indicating morphometric relationships among species, and by assisting with new species diagnosis. The preliminary species identification can be accomplished by running cluster analysis for unknown species together with the data matrix of known published Longidorus species.