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Int. J. Environ. Res. Public Health 2010, 7(5), 1970-1983; doi:10.3390/ijerph7051970

The Case for Visual Analytics of Arsenic Concentrations in Foods

1,* , 2,* , 2
1 Department of Environmental Sciences, University of South Africa, PO Box 392, Pretoria 003, South Africa 2 Center for Bioinformatics & Computational Biology, Department of Biology, Jackson State University, Jackson, MS 39217, USA
* Authors to whom correspondence should be addressed.
Received: 7 January 2010 / Revised: 27 February 2010 / Accepted: 3 April 2010 / Published: 28 April 2010
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Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i) metabolism of arsenic in the human body; (ii) arsenic concentrations in various foods; (ii) factors affecting arsenic uptake in plants; (ii) introduction to visual analytics; and (iv) benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species.
Keywords: arsenic; foods; risk assessment; toxicity; visual analytics arsenic; foods; risk assessment; toxicity; visual analytics
This is an open access article distributed under the Creative Commons Attribution License (CC BY) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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Johnson, M.O.; Cohly, H.H.; Isokpehi, R.D.; Awofolu, O.R. The Case for Visual Analytics of Arsenic Concentrations in Foods. Int. J. Environ. Res. Public Health 2010, 7, 1970-1983.

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