• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.238-244
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• 2013

In energy dispersive X-ray fluorescence analysis, the removal of the continuum on which the X-ray spectrum is superimposed is one of the most important processes, since it has a strong influence on the analysis result. The existing methods which have been used for it usually require tight constraints or prior information on the continuum. In this paper, an efficient background correction method is proposed for Energy Dispersive X-ray fluorescence (EDXRF) spectra. The proposed method has two steps of background modeling and background correction. It is based on the basic concept which differentiates background areas from the peak areas in a spectrum and the SNIP algorithm, one of the popular methods for background removal, is used to enhance the performance. After detecting some points which belong to the background from a spectrum, its background is modeled by a curve fitting method based on them. And then the obtained background model is subtracted from the raw spectrum. The method has been shown to give better results than some of traditional methods, while working under relatively weak constraints or prior information.

• Korean Journal of Food Science and Technology
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• v.40 no.2
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• pp.135-140
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• 2008

In this study, the macromineral content ratios of four herbal medicine samples(Saposhnikoviae Radix, Bupleuri Radix, Cnidii Rhizoma, and Astragali Radix) were analyzed to discriminate their geographical origins using an energydispersive x-ray fluorescence (EDXRF) technique. EDXRF is a rapid, non-destructive, and multi-elemental analysis technique. Initially, samples of both domestic and imported herbal medicines were pulverized, and then their macromineral contents, including P, S, K, and Ca, were analyzed using EDXRF. For the discrimination of their geographical origins, canonical discriminant analysis was carried out based on the estimated macromineral relative content ratios of the samples. According to the results, the discrimination accuracies were as follows: 93.3% for Saposhnikoviae Radix, 95.7% for Bupleuri Radix, 98.8% for Cnidii Rhizoma, and 87.5% for Astragali Radix. Overall, the results imply that this technique could be used as a standard method, to discriminate their geographical origins between domestic and imported herbal medicines.