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Open AccessFeature PaperArticle

Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling

Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS-CSIC), Avda, Reina Mercedes 10, 41012 Sevilla, Spain
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Appl. Sci. 2020, 10(17), 5726; https://doi.org/10.3390/app10175726
Received: 23 June 2020 / Revised: 11 August 2020 / Accepted: 13 August 2020 / Published: 19 August 2020
Portable X-ray fluorescence (pXRF) has been a widely used technique in various applications. However, its use for the analysis of organic amendments (composts, sewage sludges, organic fertilizers) is scarce. In these matrices, concentrations of some elements are below their detection limit. The objective of this work was to find multiple linear regression equations that were able to predict the aqua-regia-soluble concentrations of the elements As, Cd, Cr, Hg, Ni, and Se using the pXRF readings of other measurable elements as predictor variables. For this, a set of 30 samples of organic amendments (composts, sewage sludges, and organic fertilizers) from the Manure and Refuse Sample Exchange Programme of the Wageningen Evaluating Programs for Analytical Laboratories (MARSEP-WEPAL) was used. Several amendment type-dependent single or multiple linear functions were found based on 1, 2, or 3 predictors. The predictor readings corresponded to the concentration of elements of geogenic (Fe, Si, Ti, Cl, Zr Al, Ca, S, Mn, and Ba), anthropogenic (Zn and Pb), and agricultural (P and K) origin. The regression coefficients of these functions were r = 0.90–0.99; therefore, they allowed for the quantitative determination of the target elements. These results will allow for fast and reliable analysis of organic amendments using pXRF that is valid for quality control in treatment plants. View Full-Text
Keywords: pXRF; compost; sewage sludge; organic fertilizer; aqua regia extraction; chemometry; multivariate regression pXRF; compost; sewage sludge; organic fertilizer; aqua regia extraction; chemometry; multivariate regression
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López-Núñez, R.; Ajmal-Poley, F.; Burgos-Doménech, P. Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling. Appl. Sci. 2020, 10, 5726.

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