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The structure and dynamics of microbial populations play a significant role during cheese manufacture and ripening. Therefore, fast and accurate methods for identification and characterization of the microbial populations are of fundamental importance to the cheese industry. In this study, we investigate the application of the automated ribosomal intergenic spacer analysis (ARISA) for the assessment of the microbial dynamics in cheeses differing in salt cation level and type. We developed a database of the observed and theoretical length of the 16S-23S intergenic spacer of common lactic acid bacteria (LAB) found in cheese and used the database to describe the structure and dynamics of microbial populations during ripening. Salt content and cation concentration did not significantly influence the overall bacteria structure, except that lower salt levels resulted in enhanced starter survival. Presence of nonstarter LAB was detected by ARISA and denaturing gradient gel electrophoresis (DGGE) after 3 months for all the cheeses analysed. ARISA used as fingerprinting method, proved to be a rapid and inexpensive technique for the discrimination of LAB in cheese and demonstrated higher resolution and performance in comparison with DGGE.Significance and Impact of the Study: Microbial communities play important roles during cheese making and ripening, hence rapid inexpensive methods to characterize this microbiota are of great interest to both academic and industrial scientists. The application of automated ribosomal intergenic spacer analysis (ARISA) was used to examine the microbial ecology of Cheddar cheese differing in salt level and type. ARISA is well suited to the analysis of the microbial ecology of cheese during ripening. Additionally, the results confirm that salt concentration influences starter culture survival in the cheese matrix, while significant differences were not observed in the nonstarter lactic acid bacteria.