Comparison between energy dispersive X-ray fluorescence spectral data and elemental data for soil attributes modelling

Energy dispersive X-ray fluorescence (EDXRF) has been successfully applied for soil attribute prediction. Although, both spectral and elemental EDXRF data may be used in soil fertility attributes modelling, as far as we are concerned, there are no studies that compare the models performance using th...

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Bibliographic Details
Published in:Spectrochimica acta. Part B: Atomic spectroscopy 2021-11, Vol.185, p.106303, Article 106303
Main Authors: dos Santos, Felipe Rodrigues, de Oliveira, José Francirlei, Barbosa, Graziela M.C., Melquiades, Fábio Luiz
Format: Article
Language:English
Subjects:
Energy dispersive X-ray fluorescence
Fertility
Figures of merit
Fluorescence
Least squares method
Linearity
Modelling
Multivariate calibration
Predictions
Regression analysis
Regression models
Robustness
Soil
Soil dispersion
Soil fertility
Soil fertility attributes
Soils
Spectra
X rays
X-ray fluorescence
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Summary:Energy dispersive X-ray fluorescence (EDXRF) has been successfully applied for soil attribute prediction. Although, both spectral and elemental EDXRF data may be used in soil fertility attributes modelling, as far as we are concerned, there are no studies that compare the models performance using the two input possibilities. The objective of this study was to compare the performance of partial least squares regression models for soil fertility attributes prediction using different EDXRF inputs (spectral data and peak intensity data) by the evaluation of some figures of merit such as linearity, trueness, precision and robustness. The results show that the input EDXRF dataset type used in the modelling did not significantly interfere in the fertility attributes prediction, valid for the soils evaluated in the present work. However, the use of peak intensity data presented lack of linearity and robustness in some models. Moreover, the present study report relevant protocols for analytical validation in soil fertility attributes prediction when EDXRF data is applied. [Display omitted] •Two input possibilities for EDXRF data modelling were compared.•Figures of merit were evaluated and compared.•The EDXRF input do not interfere significantly on soil attributes prediction.•Analytical validation protocols in soil attributes prediction were stablished.
ISSN:0584-8547
1873-3565
DOI:10.1016/j.sab.2021.106303