The importance of fish culture has been increasing since 1990’s. The steady growth of fish culture helps to ensure a stable supply of fish for human consumption. However, when compared with capture fisheries, production from fish culture is greatly influenced by fish diseases. Outbreaks of fish diseases have caused great economic loss to fish culture. Research has been conducted to understand and reduce the occurrence of fish diseases in fish culture. In Hong Kong, bacterial infection is the most common cause of fish diseases. This project is therefore directed to isolate and identify the causative bacterial pathogen of some fish disease cases with the aim of setting up a local fish disease database for assisting the identification of diseases and improving the understanding of fish diseases in fish farms in Hong Kong. In this project, seven fish disease cases caused by bacteria were investigated with the AFCD officials in Hong Kong. Nine fish disease bacterial pathogens were isolated and identified using different methods (including commercial biochemical test kits, automated system and DNA sequencing). The bacteria identified included Aeromonas hydrophila, Lactococcus garvieae, Streptococcus agalactiae, Streptococcus dysgalactiae, Streptococcus iniae, Vibrio vulnificus and Aeromonas salmonicida. Sensitivity tests to 10 common antibiotics conducted for the identified bacteria showed that spectinomycin is the most broad spectrum antibiotics. In addition, a long-term physical storage of bacterial stock with glycerol and glass beads was established for further research of the identified bacteria. For efficient data analysis, an electronic database using Microsoft Access to hold the identification results and case history of each isolated bacteria was developed. Different data entry forms and reports were also constructed to facilitate easy data entry and data access for users. The three bacteria identification methods were compared for their efficiency and accuracy. Some limitations encountered in this project including time constraints and low accuracy of some biochemical identification tests were discussed and recommendations to overcome these limitations and improvements to the constructed database were made. / published_or_final_version / Environmental Management / Master / Master of Science in Environmental Management
| Identifer | oai:union.ndltd.org:HKU/oai:hub.hku.hk:10722/207649 |
| Date | January 2014 |
| Creators | Leung, Ka-ming, 梁家銘 |
| Publisher | The University of Hong Kong (Pokfulam, Hong Kong) |
| Source Sets | Hong Kong University Theses |
| Language | English |
| Detected Language | English |
| Type | PG_Thesis |
| Rights | Creative Commons: Attribution 3.0 Hong Kong License, The author retains all proprietary rights, (such as patent rights) and the right to use in future works. |
| Relation | HKU Theses Online (HKUTO) |
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