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Development of a dairy cattle drinking water quality index (DCWQI) based on fuzzy inference systems
Affiliation:1. Department of Environmental Health Engineering, School of Public Health, Tehran university of Medical Sciences, Enghelab St., Tehran, Iran;2. Young Researchers Club, Medical Branch, Islamic Azad University, Tehran, Iran;3. National Institute of Health Research, Tehran University of Medical Sciences, Tehran, Iran;4. Department of Animal and Poultry Health and Nutrition, Faculty of Veterinary Medicine, University of Tehran, Enghelab St., Tehran, Iran;5. Research Center for Science and Technology in Medicine (RCSTIM), Tehran University of Medical Sciences, Keshavarz Boulevard, Tehran, Iran;6. Department of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran;1. Department of Environmental Health Engineering, School of Health, Khoy University of Medical Sciences, Khoy, Iran;2. Social Determinants of Health Research Center, Yasuj University of Medical Sciences, Yasuj, Iran;3. Department of Environmental Health Engineering, Faculty of Health, Yasuj University of Medical Sciences, Yasuj, Iran;4. The Chang School of Continuing Education, Ryerson University, Toronto, Ontario, Canada;5. Department of Environmental Health Engineering, Student Research Committee, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran;1. Sino-Canada Energy and Environmental Research Center, North China Electric Power University, Beijing 102206, China;2. School of Environment, Beijing Normal University, Beijing 100875, China;3. Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, Sask. S4S 7H9, Canada;4. School of Environmental Science and Engineering, Sun Yat-Sen University, Guangzhou 510275, Guangdong, China;1. Norwegian Veterinary Institute, Department of Health Surveillance, P. O. Box 750, 0106 Oslo, Norway;2. Faculty of Land and Food Systems, University of British Columbia, 2357 Main Mall, Vancouver, BC V6T 1Z4, Canada;1. School of Earth Sciences, Swami Ramanand Teerth Marathwada University, Nanded, Maharashtra 431606, India;2. Clearwater Group, 229 Tewksbury Avenue, Pt. Richmond, CA 94801, USA;3. Department of Mechanical Engineering, Shri Guru Gobind Singhji Institute of Engineering and Technology, Nanded 431 606, India;1. Department of Earth Sciences, University of Tabriz, Tabriz, Iran;2. Department of Bioresource Engineering, McGill University, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada;3. Department of Applied Geology, Kharazmi University, Tehran, Iran
Abstract:The critical role of water quality for all animals, and especially dairy cattle, the dairy products of which are consumed by humans, raises the need for an index which represents well the quality of water consumed by dairy cattle. Noting the high subjectivity and inappropriate classifications that traditional methods apply to development an index, we aimed to develop a better index that measures the quality of drinking water supplied to dairy cattle (DCWQI1) based on fuzzy logic. Using fuzzy logic enabled us to capture experts’ knowledge and to simulate the human's way of thinking in the design of the index. Our approach avoided the shortcomings of the previous models. We selected 20 parameters that available literature determined were critical to assessing the quality of water for dairy cattle to drink due mainly to their potential impacts both on dairy cattle and human health. These parameters were: dissolved oxygen (DO), biochemical oxygen demand (BOD), pH, temperature, total dissolved solids (TDS), turbidity, fecal coliform, heterotrophic plate count, hardness, alkalinity, arsenic, lead, mercury, nickel, cadmium, chromium, total phosphorous, H2S, nitrate, and fluoride. We used trapezoidal membership functions and the final ruleset consisted of 550 rules. Mamdani inference system captured experts’ knowledge and experience; center-of-gravity method was used to defuzzify the results. To evaluate the index performance, we conducted a case study of Karun River employing the water quality data from six sampling stations along the river over the period of 2007–2010 and compared the results to those from the National Sanitation Foundation (NSF) water quality index (WQI). Our study found that the water quality of Karun River lies in the low to medium range (annual mean index values of 38–55). In addition, the values from the fuzzy DCWQI were generally lower than the values from the NSF WQI, mainly because the DCWQI included heavy metals in its index, while the NSF WQI did not. Results of the present study suggest that DCWQI can be considered as a comprehensive tool for assessing the quality of water for dairy cattle drinking purposes and can be reliably used for that objective.
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