Phenetic numerical taxonomy is one of the methods to study bacterial diversity. The genus Bacillus is a cosmopolitan bacterium that is abundant in nature. Some of its members can withstand iron (Fe). The objective of this study was to determine the diversity of iron-resistant Bacillus isolated from the ITS Eco Urban Farming using a numerical phenetic taxonomic approach. Isolation of bacteria through composite method and screening of iron resistant bacteria on nutrient agar containing Fe. Characterization of bacteria achieved by morphological, physiological, and biochemical tests. Dendrogram construction utilizing the MultiVariate Statistical Package (MVSP) and isolates grouping based on the Unweighted Pair Group Method with Arithmetic Average (UPGMA). Seven tested isolates were resistant to Fe up to 120 ppm. Based on the generic assignment using profile matching, five isolates belong to Bacillus, and the others are not. Dendrogram construction showed 2 clusters, namely Cluster A, consisting of UF4, UF6, UF8, and Cluster B built from UF1 and UF5. Between cluster A and cluster B, there is a similarity index (SSM) of 64%, which indicates that the members of Cluster A are different from the members of Cluster B.
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24 January 2023
THE 4TH INTERNATIONAL CONFERENCE ON LIFE SCIENCE AND TECHNOLOGY (ICoLiST)
31 August 2021
Malang, Indonesia
Research Article|
January 24 2023
The diversity of Bacillus resistant iron (Fe) isolated from ITS eco urban farming using phenetic numerical taxonomy approach
Sabila Fatimah;
Sabila Fatimah
Department of Biology, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember
, Surabaya 60111, Indonesia
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Enny Zulaika
Enny Zulaika
a)
Department of Biology, Faculty of Science and Data Analytics, Institut Teknologi Sepuluh Nopember
, Surabaya 60111, Indonesia
a)Corresponding author: [email protected]
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a)Corresponding author: [email protected]
AIP Conf. Proc. 2634, 020016 (2023)
Citation
Sabila Fatimah, Enny Zulaika; The diversity of Bacillus resistant iron (Fe) isolated from ITS eco urban farming using phenetic numerical taxonomy approach. AIP Conf. Proc. 24 January 2023; 2634 (1): 020016. https://doi.org/10.1063/5.0111310
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