International Journal of Ecosystem
p-ISSN: 2165-8889 e-ISSN: 2165-8919
2015; 5(3A): 47-54
doi:10.5923/c.ije.201501.07
Swati Mollah
Dumkal College, Basantpur, Murshidabad
Correspondence to: Swati Mollah, Dumkal College, Basantpur, Murshidabad.
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Copyright © 2015 Scientific & Academic Publishing. All Rights Reserved.
Murshidabad district practices rice cultivation with irrigation from groundwater. The shallow tube-wells installed for agricultural irrigation contain average arsenic of 0.094 mg/l and drinking water contains 0.11mg/l. The mean arsenic levels in food categories in the study area are vegetables 21.2μg/kg, cereals and bakery goods 179μg/kg and spices 202μg/kg (Roychowdhury et al., 2003). Although six arsenic removal plants had been previously installed in the village, the villagers are still exposed to elevated levels of arsenic daily. 92.6 per cent of analyzed biological sample contained arsenic at above normal levels in the area (Rahaman et al., 2005). The paper tries to explore the perception of farmers towards the management of arsenic contamination problem in their locality through sample survey in Murshidabad district using RIDIT analysis. The paper finds that the respondents have limited knowledge about the arsenic contamination in foods and they are not aware about the sustainable management options also. They emphasise on the improvement of overall economic condition of the area, establishment of more water test centers and govt. regulations on groundwater extraction etc. to manage the contamination of arsenic in food.
Keywords: Arsenic contamination, RIDIT Analysis, Risk perception
Cite this paper: Swati Mollah, Prioritizing Options for Removal of Arsenic Contamination in Daily Food Using Ridit Analysis, International Journal of Ecosystem, Vol. 5 No. 3A, 2015, pp. 47-54. doi: 10.5923/c.ije.201501.07.
![]() | Figure 1. Location of the study area |

(d) Compute ridit value Rj for each category of responses in the reference data set.
N is the total number of responses from the Likert scale survey of interest. By definition, the expected value of R for the reference data set is always 0.5. 2. Compute ridits and mean ridits for comparison data sets. Note that a comparison data set is comprised of the frequencies of responses for each category of a Likert scale item. Since there are m Likert scale items in this illustration, there will be m comparison data sets.(a) Compute ridit value rij for each category of scale items. 
the frequency of category j for ith scale item,
is the summation of frequencies for scale item i across all categories i.e.
(b) Compute mean ridit ρi for each Likert scale item,
(c) Compute confidence interval for ρi . When the size of the reference data set is very large relative to that of any comparison data set, the 95% confidence interval of any ρi is:
(d) Test the following hypothesis using Kruskal-Wallis statistics W:
W follows a χ2 distribution with (m- 1) degree of freedom.![]() | Figure 2. Locations of the sample villages for survey |
![]() | Figure 3. Respondents’ knowledge about arsenic contamination in their locality; Source: Field survey, 2013 |
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