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Volume 7, Number 2, June 2018

The anaerobically digestion and agricultural application of organic wastes was conducted using food wastes and cow dung. Twenty kilograms each of the feed stocks was added into two 30 liters-capacity batch digesters. The anaerobic digestion was carried out within a temperature range of 25 – 31O C for a retention time of 51days. The results showed a cumulative gas yield of 5.0 bars for food waste and no gas production for cow dung within the retention time. Bacteria such as Escherichia coli, Staphylococcus aureus, Pseudomonas aeruginosa, Proteus vulgaris and Clostridium sp were isolated. Fungi isolated included Aspergillus niger, Aspergillus nidulan, Trichophyton rubrum and Epidermophyton flocossum. The non-dispersive infrared (NDIR) analysis of the biogas produced confirmed that the gas consisted of CH4, CO2 and H2. Statistical analysis revealed there was no significant correlation between temperature and biogas produced from the organic wastes (r= 0.177, p = 0.483).The organic wastes from the biogas production process stimulated maize growth when compared to control (soil without organic waste) and indicated maximum height. The study therefore reveals that food waste as potential substrates for biogas production has a moderate bio-fertilizer potential for improving plant growth and yield when added to soil.

Key Words
waste; biogas; digestion; methane (CH4); carbon dioxide (CO2)

Leh-Togi Zobeashia S. Suanu: National Biotechnology Development Agency, Lugbe, Abuja, Nigeria

Aransiola S. Abiodun: Bioresources Development Centre, National Biotechnology Development Agency,
KM 5 Ogbomoso/Iresapa Road, Onipaanu, Ogbomoso, Nigeria

Ijah U. J. Josiah and Abioye O. Peter: Department of Microbiology, Federal University of Technology, PMB 65, Minna, Nigeria

Water quality monitoring network needs periodic evaluations based on environmental demands and financial constraints. We used a genetic algorithm to optimize the existing water quality monitoring stations on the Sefid-Rud River, which is located in the North of Iran. Our objective was to optimize the existing stations for drinking and irrigation purposes, separately. The technique includes two stages called data preparation and the optimization. On the data preparation stage, first the basin was divided into four sections and each section was consisted of some stations. Then, the score of each station was computed using the data provided by the water Research Institute of the Ministry of energy. After that, we applied a weighting method by providing questionnaires to ask the experts to define the significance of each parameter. In the next step, according to the scores, stations were prioritized cumulatively. Finally, the genetic algorithm was applied to identify the best combination. The results indicated that out of 21 existing monitoring stations, 14 stations should remain in the network for both irrigation and drinking purposes. The results also had a good compliance with the previous studies which used dynamic programming as the optimization technique.

Key Words
genetic algorithm; network design; optimization, sampling site; water quality monitoring

Gholamreza Asadollahfardi, Nima Heidarzadeh,
Atabak Mosalli and Ali Sekhavati: Civil Engineering Department, Faculty of Engineering, Kharazmi University, Tehran, Iran

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