Dataset Information

Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements.

ABSTRACT: Portable X-ray fluorescence (PXRF) measurements on 1520 soil samples were used to create national prediction models for copper (Cu), zinc (Zn), and cadmium (Cd) concentrations in agricultural soil. The models were validated at both national and farm scales. Multiple linear regression (MLR), random forest (RF), and multivariate adaptive regression spline (MARS) models were created and compared. National scale cross-validation of the models gave the following R2 values for predictions of Cu (R2 = 0.63), Zn (R2 = 0.92), and Cd (R2 = 0.70) concentrations. Independent validation at the farm scale revealed that Zn predictions were relatively successful regardless of the model used (R2 > 0.90), showing that a simple MLR model can be sufficient for certain predictions. However, predictions at the farm scale revealed that the non-linear models, especially MARS, were more accurate than MLR for Cu (R2 = 0.94) and Cd (R2 = 0.80). These results show that multivariate modelling can compensate for some of the shortcomings of the PXRF device (e.g., high limits of detection for certain elements and some elements not being directly measurable), making PXRF sensors capable of predicting elemental concentrations in soil at comparable levels of accuracy to conventional laboratory analyses.

SUBMITTER: Adler K

PROVIDER: S-EPMC7014454 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements.

Adler Karl K Piikki Kristin K Söderström Mats M Eriksson Jan J Alshihabi Omran O

Sensors (Basel, Switzerland) 20200114 2

Portable X-ray fluorescence (PXRF) measurements on 1520 soil samples were used to create national prediction models for copper (Cu), zinc (Zn), and cadmium (Cd) concentrations in agricultural soil. The models were validated at both national and farm scales. Multiple linear regression (MLR), random forest (RF), and multivariate adaptive regression spline (MARS) models were created and compared. National scale cross-validation of the models gave the following R<sup>2</sup> values for predictions o ...[more]

PMID: 31947672

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Project description:Soil contamination with trace metal(loid) elements (TME) is a global concern. This has focused interest on TME-tolerant plants, some of which can hyperaccumulate extraordinary amounts of TME into above-ground tissues, for potential treatment of these soils. However, intra-species variability in TME hyperaccumulation is not yet sufficiently understood to fully harness this potential. Particularly, little is known about the rhizosphere microbial communities associated with hyperaccumulating plants and whether or not they facilitate TME uptake. The aim of this study is to characterize the diversity and structure of Arabidopsis halleri rhizosphere-influenced and background (i.e., non-Arabidopsis) soil microbial communities in four plant populations with contrasting Zn and Cd hyperaccumulation traits, two each from contaminated and uncontaminated sites. Microbial community properties were assessed along with geographic location, climate, abiotic soil properties, and plant parameters to explain variation in Zn and Cd hyperaccumulation. Site type (TME-contaminated vs. uncontaminated) and location explained 44% of bacterial/archaeal and 28% of fungal community variability. A linear discriminant effect size (LEfSe) analysis identified a greater number of taxa defining rhizosphere microbial communities than associated background soils. Further, in TME-contaminated soils, the number of rhizosphere-defining taxa was 6-fold greater than in the background soils. In contrast, the corresponding ratio for uncontaminated sites, was 3 and 1.6 for bacteria/archaea and fungi, respectively. The variables analyzed explained 71% and 76% of the variance in Zn and Cd hyperaccumulation, respectively; however, each hyperaccumulation pattern was associated with different variables. A. halleri rhizosphere fungal richness and diversity associated most strongly with Zn hyperaccumulation, whereas soil Cd and Zn bioavailability had the strongest associations with Cd hyperaccumulation. Our results indicate strong associations between A. halleri TME hyperaccumulation and rhizosphere microbial community properties, a finding that needs to be further explored to optimize phytoremediation technology that is based on hyperaccumulation.

Dataset Information

Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements.

Publications

Predictions of Cu, Zn, and Cd Concentrations in Soil Using Portable X-Ray Fluorescence Measurements.

Similar Datasets

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