Next Article in Journal
Quantifying the Effects of Hurricanes Irma and Maria on Coastal Water Quality in Puerto Rico using Moderate Resolution Satellite Sensors
Next Article in Special Issue
Rapid Determination of Soil Class Based on Visible-Near Infrared, Mid-Infrared Spectroscopy and Data Fusion
Previous Article in Journal
MODIS Fractional Snow Cover Mapping Using Machine Learning Technology in a Mountainous Area
Previous Article in Special Issue
Estimation of Secondary Soil Properties by Fusion of Laboratory and On-Line Measured Vis–NIR Spectra
Open AccessArticle

Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF

1
Laboratory of Precision Agriculture (LAP), Department of Biosystems Engineering, “Luiz de Queiroz” College of Agriculture (ESALQ), University of São Paulo (USP), Piracicaba, São Paulo 13418900, Brazil
2
Precision Soil and Crop Engineering Group (Precision SCoRing), Department of Environment, Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, Blok B, 1st Floor 9000 Gent, Belgium
3
Laboratory of Analytical Chemistry (LQA), Center for Nuclear Energy in Agriculture (CENA), University of São Paulo (USP), Piracicaba, São Paulo 13416000, Brazil
4
Laboratory of 14 Carbon (LC14), Center for Nuclear Energy in Agriculture (CENA), University of São Paulo (USP), Piracicaba, São Paulo 13416000, Brazil
5
Laboratory of Applied Nuclear Physics (LFNA), Department of Physics, Londrina State University (UEL), Londrina, Paraná 86057970, Brazil
6
Laboratory of Nuclear Instrumentation (LIN), Center for Nuclear Energy in Agriculture (CENA), University of São Paulo (USP), Piracicaba, São Paulo 13416000, Brazil
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(6), 963; https://doi.org/10.3390/rs12060963
Received: 14 February 2020 / Revised: 12 March 2020 / Accepted: 13 March 2020 / Published: 17 March 2020
The successful use of energy-dispersive X-ray fluorescence (ED-XRF) sensors for soil analysis requires the selection of an optimal procedure of data acquisition and a simple modelling approach. This work aimed at assessing the performance of a portable XRF (XRF) sensor set up with two different X-ray tube configurations (combinations of voltage and current) to predict nine key soil fertility attributes: (clay, organic matter (OM), cation exchange capacity (CEC), pH, base saturation (V), and extractable nutrients (P, K, Ca, and Mg). An XRF, operated at a voltage of 15 kV (and current of 23 μA) and 35 kV (and current of 7 μA), was used for analyzing 102 soil samples collected from two agricultural fields in Brazil. Two different XRF data analysis scenarios were used to build the predictive models: (i) 10 emission lines of 15 keV spectra (EL-15), and (ii) 12 emission lines of 35 keV spectra (EL-35). Multiple linear regressions (MLR) were used for model calibration, and the models’ prediction performance was evaluated using different figures of merit. The results show that although X-ray tube configuration affected the intensity of the emission lines of the different elements detected, it did not influence the prediction accuracy of the studied key fertility attributes, suggesting that both X-ray tube configurations tested can be used for future analyses. Satisfactory predictions with residual prediction deviation (RPD) ≥ 1.54 and coefficient of determination (R2) ≥ 0.61 were obtained for eight out of the ten studied soil fertility attributes (clay, OM, CEC, V, and extractable K, Ca, and Mg). In addition, simple MLR models with a limited number of emission lines was effective for practical soil analysis of the key soil fertility attributes (except pH and extractable P) using XRF. The simple and transparent methodology suggested also enables future researches that seek to optimize the XRF scanning time in order to speed up the XRF analysis in soil samples. View Full-Text
Keywords: precision agriculture; proximal soil sensing; hybrid laboratory; soil testing; XRF spectroscopy; Brazilian tropical soils precision agriculture; proximal soil sensing; hybrid laboratory; soil testing; XRF spectroscopy; Brazilian tropical soils
Show Figures

Graphical abstract

MDPI and ACS Style

Tavares, T.R.; Molin, J.P.; Nunes, L.C.; Alves, E.E.N.; Melquiades, F.L.; de Carvalho, H.W.P.; Mouazen, A.M. Effect of X-Ray Tube Configuration on Measurement of Key Soil Fertility Attributes with XRF. Remote Sens. 2020, 12, 963.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop