Summary: The character state data for clusters defined at the 83% simple matching coefficient () similarity level in a previous phenetic classification were used to construct a probabilistic identification matrix for species. The 24 phena included consisted of 10 clusters containing from 2 to 17 strains and 14 single-member clusters. Characters most diagnostic for the clusters were selected from the 185 used in the classification, using previously developed computer programs for determination of character separation indices (CHARSEP) and selection of group diagnostic properties (DIACHAR). The resulting matrix consisted of 41 characters x 24 phena, and identification scores, provided by a program for the identification of unknowns against an identification matrix (MATIDEN), were used for its evaluation. Cluster overlap, calculated by a program for determination of overlap between groups in a matrix (OVERMAT), was generally very small, and the best identification scores possible for most typical examples of each group (MOSTTYP program) were very satisfactory. Input of test data for randomly selected cluster representatives resulted in correct identifications with good scores for the three coefficients provided by the MATIDEN program.


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