Show simple item record

dc.contributor.authorOkonda, JJ
dc.contributor.authorAngeyo, KH
dc.contributor.authorMangala, JM
dc.contributor.authorKisia, SM
dc.date.accessioned2017-12-04T13:20:34Z
dc.date.available2017-12-04T13:20:34Z
dc.date.issued2017
dc.identifier.citationAppl Radiat Isot. 2017 Nov;129:49-56. doi: 10.1016/j.apradiso.2017en_US
dc.identifier.urihttps://www.ncbi.nlm.nih.gov/pubmed/28806597
dc.identifier.urihttp://hdl.handle.net/11295/101556
dc.description.abstractCompton scatter-modulated fluorescence and multivariate chemometric (artificial neural network (ANN) and principal component regression (PCR)) calibration strategy was explored for direct rapid trace biometals (Mn, Fe, Cu, Zn, Se) analysis in "complex" matrices (model soft tissues). This involved spectral feature selection (multiple fluorescence signatures) normalized to or in conjunction with Compton scatter. ANN model resulted in more accurate trace biometal determination (R2>0.9) compared to PCR. Hybrid nested (ANN and PCR) approach led to optimized accurate biometals' concentrations in Oyster tissue (≤ ± 10%).en_US
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectBiometals; Calibration strategy; Chemometrics; Model soft tissue; Oyster tissueen_US
dc.titleA nested multivariate chemometrics based calibration strategy for direct trace biometal analysis in soft tissue utilizing Energy Dispersive X-Ray Fluorescence (EDXRF) and scattering spectrometry.en_US
dc.typeArticleen_US


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States