Bacterial Monitoring of Drinking Water Sources Using Immunofluorescence technique, Image Processing Software and Web-based Data Visualisation
- Authors
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Paul Nicolae Ancuta
National Institute of Research and Development in Mechatronics and Measurement Technique
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Anca Atanasescu
National Institute of Research and Development in Mechatronics and Measurement Technique
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Sorin Sorea
National Institute of Research and Development in Mechatronics and Measurement Technique
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Danut Iulian Stanciu
National Institute of Research and Development in Mechatronics and Measurement Technique, Romania
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Irina Eugenia Lucaciu
National Research and Development Institute for Industrial Ecology
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Catalina Stoica
National Research and Development Institute for Industrial Ecology
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Mihai Nita-Lazar
National Research and Development Institute for Industrial Ecology
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Alina Roxana Banciu
National Research and Development Institute for Industrial Ecology
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- Abstract
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European organizations involved in updating water management regulations (WHO, OECD) insist in recent years on the need to improve methods for assessing and managing microbiological , physical and chemical safety of drinking water . Data obtained as a result of water quality monitoring should become a starting point for risk management actions.
The paper is mainly focused on presenting a highly efficient software application used to implement a more rapid microbiological method to detect pathogenic bacteria for human health, based on bacterial specific antibody-antigen interaction (Ag-Ab) , namely immunofluorescence technique , and microscopic digital image processing. Laboratory tests have proven that the proposed solution is reliable, stable and time-efficient for preventing microbiological contamination of drinking water.
This application software, the method and related instrumentation that the paper presents are parts of a demonstrative modular model which monitors water quality. The first module consists of instrumentation and software that serve a methodology applied to detect pathogenic bacteria in drinking water samples. The second module performs data transmission and storage in a relational database and enables real-time data visualization. - References
- Downloads
- Published
- 2019-06-28
- Issue
- Vol. 21 No. 2 (2019)
- Section
- Articles