X-ray fluorescence and gamma-ray spectrometry combined with multivariate analysis for topographic studies in agricultural soil

Gamma-rays and X-rays spectrometries applied to evaluate soil redistribution

This work responds to the growing global demand for food, which requires improvements in agricultural production and sustainable management of natural resources. The focus is on soil erosion as a critical element in preserving agricultural productivity. From this perspective, the levels of radionuclides and chemical elements present in the soil, quantified through Gamma-Rays Spectrometry (GRS) and Energy Dispersive X-ray Fluorescence (EDXRF), were used to investigate soil redistribution over time. 27 soil samples ranging from 0 to 30 cm in depth were collected in an agricultural plot located in southern Brazil. Quantitative analysis indicated high mean concentrations of Fe (161 ± 7 gkg-1), Al (110 ± 17 gkg-1), Ca (2.6 ± 0.5 gkg-1), Mn (2.4 ± 0.3 gkg-1) and K (543 ± 165 mgkg-1) in comparison with the other detected elements. The quantification of 137Cs provided a mean inventory of 27 ± 17 Bqm-2. Using the proportional model, an estimated gross erosion rate of 28.2 tonha-1year-1 and a net soil deposition of 6.6 tonha-1year-1 were calculated. Therefore, a net soil loss of 21.6 tonha-1year-1 was experienced within the agricultural plot studied. The data set combination of both techniques with Principal Component Analysis (PCA) revealed correlations between the variables studied and the soil erosion dynamics. The PCA showed a tendency to separate the samples according to their sampling depth. Moreover, 137Cs behavior in soil proved to be similar to the behavior of elements found in fertilizers, like K. On the other hand, the individual influence of 137Cs was not enough to cause significant changes in the samples distribution in the scores plot, highlighting EDXRF as a promising technique to complement soil erosion studies.

Recovering and restitution of unknown, unidentified, and unlabeled samples in laboratories using EDXRF analysis

This Study presents a method to recover and label unknown samples in a nuclear laboratory using Energy Dispersive X-Ray Fluorescence (EDXRF) spectrometry based on spectra differentiation and analysis. This method was found to be a new powerful tool that can be used in different laboratories where a certain number of samples cannot be identified because they have never been identified, their labeling and identification cannot be assessed because of degradation, and/or any other causes. The method was found to be simple, timely appropriate, not expensive, and powerful in identifying and recover the information needed for a sample. The EDXRF spectrometry method for recovering unknown samples in laboratories was based on the following three main points:•

EDXRF method allows the elemental characterization of any sample without clear identification in a laboratory;

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The displaying of several samples’ spectra on the same graph allows direct comparison and identification when the sample's data overlap one of the stored data; and

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The identification of the unknown sample based on the EDXRF results: The faster method being the overlapping comparison while the elemental characterization-based identification needs high skilled expertise in X-ray fluorescence analysis.

X-ray fluorescence application in food, feed, and agricultural science: a critical review

Recently X-ray fluorescence techniques have been widely used in food and agricultural science areas. Minimal sample preparation, nondestructive analysis, high spatial resolution, and multiple elements measurements within a single sample are among its advantages. In this review, literature of X-ray fluorescence are extensively researched and summarized from food and agricultural science areas focusing on food safety inspection, food nutrition, plant science, soil science, and Ca-related problems in horticultural crops. In addition, the advantages and disadvantages of X-ray fluorescence comparing with traditional analytical techniques of elements are also discussed. The more advanced technology such as developments of detector, scanning system, beamline capability among others would significantly increase future application of X-ray fluorescence techniques. Combination use of XRF with other tools such as chemometrics or data analytics would greatly improve its prediction performance. These further improvements offer exciting perspectives for the application of X-ray fluorescence in the food and agricultural science areas.