Abstract
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.
Highlights
Precision agriculture (PA) approaches that seek to optimize the use of fertilizers have great potential to boost agronomic and environmental benefits in agricultural production systems [1]
Given the need to understand the effect of the X-ray tube configuration to establish practical and transparent methodologies for X-ray fluorescence (XRF) data acquisition, this work aimed to evaluate the performance of a portable energy-dispersive X-ray fluorescence (ED-XRF) configured with different X-ray tube voltages (15 and 35 kV) to predict key fertility attributes in agricultural fields under tropical environment
We propose a simple and transparent methodology for XRF data acquisition and processing, which proved in this work to provide satisfactory prediction results (0.61 ≤ R2 ≤ 0.96) for clay, organic matter (OM), CEC, V, ex-K, ex-Ca, and ex-Mg (Table 3), with the exception being for pH and re-P, which gave poor results (R2 ≤ 0.38)
Summary
Precision agriculture (PA) approaches that seek to optimize the use of fertilizers have great potential to boost agronomic and environmental benefits in agricultural production systems [1]. This requires a detailed characterization of soil fertility in the field, which is fundamental to the implementation of variable rate fertilization. Proximal soil sensing (PSS) is considered as an alternative approach to analyse soil in a practical and environmentally friendly way that allows an increase in sampling density without relying exclusively on traditional soil tests [3,4,5]. The development of a hybrid methodology suitable for laboratory and field applications for the prediction of soil fertility attributes should play an important role in soil analysis, as commented by Molin and Tavares [1]
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