Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling
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 obje...
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| Format: | Article |
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MDPI AG
2020-08-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/10/17/5726 |
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| author | Rafael López-Núñez Fátima Ajmal-Poley Pilar Burgos-Doménech |
| author_facet | Rafael López-Núñez Fátima Ajmal-Poley Pilar Burgos-Doménech |
| author_sort | Rafael López-Núñez |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T17:13:49Z |
| format | Article |
| id | doaj.art-126759dd47ba4f0585479d3296294071 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T17:13:49Z |
| publishDate | 2020-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-126759dd47ba4f0585479d32962940712023-11-20T10:34:03ZengMDPI AGApplied Sciences2076-34172020-08-011017572610.3390/app10175726Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate ModelingRafael López-Núñez0Fátima Ajmal-Poley1Pilar Burgos-Doménech2Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS-CSIC), Avda, Reina Mercedes 10, 41012 Sevilla, SpainInstituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS-CSIC), Avda, Reina Mercedes 10, 41012 Sevilla, SpainInstituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS-CSIC), Avda, Reina Mercedes 10, 41012 Sevilla, SpainPortable 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.https://www.mdpi.com/2076-3417/10/17/5726pXRFcompostsewage sludgeorganic fertilizeraqua regia extractionchemometry |
| spellingShingle | Rafael López-Núñez Fátima Ajmal-Poley Pilar Burgos-Doménech Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling Applied Sciences pXRF compost sewage sludge organic fertilizer aqua regia extraction chemometry |
| title | Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling |
| title_full | Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling |
| title_fullStr | Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling |
| title_full_unstemmed | Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling |
| title_short | Prediction of As, Cd, Cr, Hg, Ni, and Se Concentrations in Organic Amendments Using Portable X-ray Fluorescence and Multivariate Modeling |
| title_sort | prediction of as cd cr hg ni and se concentrations in organic amendments using portable x ray fluorescence and multivariate modeling |
| topic | pXRF compost sewage sludge organic fertilizer aqua regia extraction chemometry |
| url | https://www.mdpi.com/2076-3417/10/17/5726 |
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