Biochemical identification and numerical taxonomy of Aeromonas spp. isolated from food samples in Turkey

Abstract

Numerical taxonomy was used to analyze phenotypic data obtained from 126 new isolates of Aeromonas strains taken from red meat, raw chicken, minced meat, and fish samples. Each strain was tested for 86 characters but only the final data including 63 characters were analysed using the S(SM) and the UPGMA clustering algorithm. At S(SM) of >= 83%, the strains clustered into 10 aggregate groups consisting of 7 major (5 and up strains) and 3 minor (2-4 strains), and 5 single member clusters, each of which was identified as A. hydrophila, A. caviae, and A. sobria, respectively. It was proved that the food isolates showed a relative phenotypical distance and the groups of strains that had atypical profiles were compared with the type species by the present identification schemes. It was clearly seen that the phenetic approach was a necessary tool to delimitate and identify the Aeromonas species. Numerical taxonomy of Aeromonas strains isolated from different sources revealed the presence of potentially pathogenic Aeromonas spp., especially in food.