SUMMARY: The character state data obtained for clusters defined at the 77-5% similarity level in the phenetic numerical classification described by Williams (1983) were used to construct a probabilistic identification matrix. The 23 phena included were the major clusters (19 2 and ) and one minor cluster (). The characters most diagnostic for these clusters were selected using Sneath's CHARSEP and DIACHAR programs. The resulting matrix consisted of 41 characters × 23 phena.

Identification scores, determined by Sneath's MATIDEN program were used to evaluate the matrix. Theoretical assessment was achieved by determination of the cluster overlap (OVERMAT), the identification scores for the Hypothetical Medium Organism of each cluster (MOSTTYP), and the scores for randomly selected cluster representatives using the classification data of Williams . (1983). The matrix was evaluated practically by the independent re-determination of the characters for the same cluster representatives, which-also provided a measure of test error. Finally it was used to identify unknown isolates from a range of habitats.

The results showed that the matrix was theoretically sound. Test error was within acceptable limits and did not distort identifications. Of the unknown isolates, 80% were clearly identified with a cluster. It is suggested that the matrix could form the basis for a more objective identification and grouping of the large number of species which have been described.


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