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dc.contributor.authorHuhmann, Linden B.
dc.contributor.authorHarvey, Charles F.
dc.contributor.authorGross, Jason
dc.contributor.authorUddin, Anjal
dc.contributor.authorChoudhury, Imtiaz
dc.contributor.authorAhmed, Kazi M.
dc.contributor.authorDuxbury, John M.
dc.contributor.authorBostick, Benjamin
dc.contributor.authorvan Geen, Alexander
dc.date.accessioned2022-02-16T15:48:32Z
dc.date.available2022-01-24T16:16:56Z
dc.date.available2022-02-16T15:48:32Z
dc.date.issued2021-01
dc.date.submitted2020-09
dc.identifier.issn0016-7061
dc.identifier.urihttps://hdl.handle.net/1721.1/139667.2
dc.description.abstract© 2020 Elsevier B.V. Rice is the primary crop in Bangladesh and rice yield is diminished due to the buildup of arsenic (As) in soil from irrigation with high-As groundwater. Soil testing with an inexpensive kit could help farmers target high-As soil for mitigation or decide to switch to a different crop that is less sensitive to As in soil. A total of 3240 field kit measurements of As in 0.5 g of fresh soil added to 50 mL of water were compared with total soil As concentrations measured on oven-dried homogenized soil by X-ray fluorescence (XRF). For sets of 12 soil samples collected within a series of rice fields, the average of kit As measurements was a linear function of the average of XRF measurements (r2 = 0.69). Taking into account that the kit overestimates water As concentrations by about a factor of two, the relationship suggests that about a quarter of the As in paddy soil is released in the kit's reaction vessel. Using the relationship and considering XRF measurements as the reference, the 12-sample average determined correctly whether soil As was above or below a 30 mg/kg threshold in 86% of cases where soil As was above the threshold and in 79% of cases where soil As was below the threshold. We also used a Bayesian approach using 12 kit measurements to estimate the probability that soil As was above a given threshold indicated by XRF measurements. The Bayesian approach is theoretically optimal but was only slightly more accurate than the linear regression. These results show that rice farmers can identify high-As portions of their fields for mitigation using a dozen field kit measurements on fresh soil and base their decisions on this information.en_US
dc.language.isoen
dc.publisherElsevier BVen_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/j.geoderma.2020.114755en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcePMCen_US
dc.titleEvaluation of a field kit for testing arsenic in paddy soil contaminated by irrigation wateren_US
dc.typeArticleen_US
dc.identifier.citationHuhmann, Linden B, Harvey, Charles F, Gross, Jason, Uddin, Anjal, Choudhury, Imtiaz et al. 2021. "Evaluation of a field kit for testing arsenic in paddy soil contaminated by irrigation water." Geoderma, 382.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Civil and Environmental Engineering
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.relation.journalGeodermaen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2022-01-24T16:14:38Z
dspace.orderedauthorsHuhmann, LB; Harvey, CF; Gross, J; Uddin, A; Choudhury, I; Ahmed, KM; Duxbury, JM; Bostick, B; van Geen, Aen_US
dspace.date.submission2022-01-24T16:14:40Z
mit.journal.volume382en_US
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work Neededen_US


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