Control of biogas production process by enzymatic and fluorescent image analysis
The process of methanogenesis, which is in the essence of the widely distributed technologies for biogas production, is slow, has multiple steps and occurs under anaerobic conditions. These factors make the control and the management of the anaerobic digestion difficult and impose the testing and im...
Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2018-03-01
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Series: | Biotechnology & Biotechnological Equipment |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/13102818.2018.1425637 |
Summary: | The process of methanogenesis, which is in the essence of the widely distributed technologies for biogas production, is slow, has multiple steps and occurs under anaerobic conditions. These factors make the control and the management of the anaerobic digestion difficult and impose the testing and implementation of new indicators for control which are fast and focused on the activity and functioning of the methanogenic community in addition to the traditionally used technological parameters. In this study, the biogas production process in wastewater treatment plant ‘Kubratovo’ was analysed in two different seasonal situations and a correlation was made between the studied parameters for control. The complex methodological arsenal included the activities of aerobic and anaerobic dehydrogenase, fluorescent image analysis and key chemical and technological indicators. The correlation analysis showed that the fluorescent image analysis parameters (number/mean size of clusters; fluorescence intensity; area) had the strongest relationship with the biogas production. Based on these results, we propose a fluorescent indicative system for control of the biogas production technologies. It is a fast tool for assessment the effectiveness of the process of anaerobic digestion. Its focus on the activity and functioning of the biological system could contribute to the optimization of the whole performance of these technologies and could serve as a prediction tool for potential problems in the future. |
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ISSN: | 1310-2818 1314-3530 |