Assessing arsenic species in foods using regularized linear regression of the arsenic K-edge X-ray absorption near edge structure-Reference-Cited by-同舟云学术

Assessing arsenic species in foods using regularized linear regression of the arsenic K-edge X-ray absorption near edge structure

Published:2022 Issue:6 Volume:37 Page:1247-1258
ISSN:0267-9477
Container-title:Journal of Analytical Atomic Spectrometry
language:en
Short-container-title:J. Anal. At. Spectrom.

Author:

Jahrman Evan P.¹^ORCID,Yu Lee L.¹^ORCID,Krekelberg William P.¹,Sheen David A.¹^ORCID,Allison Thomas C.¹,Molloy John L.¹

Affiliation:

1. Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA

Abstract

Solvent-free quantifications of arsenic species in foods are attained by applying lasso regression to the analysis of X-ray absorption spectra and assigning uncertainties by bootstrapping.

Funder

National Research Council

Publisher

Royal Society of Chemistry (RSC)

Subject

Spectroscopy,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/JA/D1JA00445J

Reference53 articles.

1. Assessment of two arsenic-contaminated drinking water mitigation interventions in Bangladesh

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5. Arsenic species in weathering mine tailings and biogenic solids at the Lava Cap Mine Superfund Site, Nevada City, CA

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