Deterioration of water quality mainly due to high total ammonia nitrogen (TAN) and nitrite will affect the productivity of shrimp culture. In this study, three indigenous strains assigned as VCM5, VCM8 and VCM12 were evaluated for their ability to degrade TAN and nitrite. These strains were inoculated into shrimp aquaculture wastewater to enhance the degradation of TAN and nitrite. All the strains reduced TAN and nitrite level from the shrimp aquaculture wastewater significantly (p<0.05). Strain VCM5 (GenBank accession number KJ700465) and VCM8 (GenBank accession number KJ700464) showed 99.71% sequence similarity with the 16S rRNA gene type species Bacillus vietnamensis 15-1T (ABO99708) and strain VCM12 (GenBank accession number KJ700463) showed 99.05% sequence similarity with 16S rRNA gene sequence type species Gordonia bronchialis DSM43247T (CP001802).
Life science ontologies play an important role in Semantic Web. Given the diversity in fish species and the associated wealth of information, it is imperative to develop an ontology capable of linking and integrating this information in an automated fashion. As such, we introduce the Fish Ontology (FO), an automated classification architecture of existing fish taxa which provides taxonomic information on unknown fish based on metadata restrictions. It is designed to support knowledge discovery, provide semantic annotation of fish and fisheries resources, data integration, and information retrieval. Automated classification for unknown specimens is a unique feature that currently does not appear to exist in other known ontologies. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1,830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users.