The use of diffuse reflectance mid-infrared spectroscopy for the prediction of the concentration of chemical elements estimated by X-ray fluorescence in agricultural and grazing European soils

The aim of this study was to develop partial least-squares (PLS) regression models using diffuse reflectance Fourier transform mid-infrared (MIR) spectroscopy for the prediction of the concentration of elements in soil determined by X-ray fluorescence (XRF). A total of 4130 soils from the GEMAS European soil sampling program (geochemical mapping of agricultural soils and grazing land of Europe) were used for the development of models to predict concentrations of Al, As, Ba, Ca, Ce, Co, Cr, Cs, Cu, Fe, Ga, Hf, K, La, Mg, Mn, Na, Nb, Ni, P, Pb, Rb, Sc, Si, Sr, Th, Ti, V, Y, Zn and Zr in soil using MIR spectroscopy. The results were compared with those obtained where MIR models were developed with the same soils but using the concentration of elements extracted with aqua regia (AR). The PLS models were cross-validated against the experimental log-transformed XRF values of all the elements. The calibration models were derived from a set of 1000 randomly selected calibration samples. The rest of the samples (3130) were used as an independent validation set. According to the residual predictive deviation (RPD), predictions were classified as follows: “Good quality”, Ca (2.9), Mg (2.5), Al (2.3), Fe (2.2), Ga (2.2), Si (2.1), Na (2.0); “Indicator quality”, V (1.9), Ni (1.9), Sc (1.9), K (1.8), Ti (1.8), Rb (1.8), Zn (1.7), Co (1.7), Zr (1.6), Cr (1.6), Sr (1.6), Y (1.6), Nb (1.6), Ba (1.5), Mn (1.5), As (1.5), Ce (1.5); “Poor quality”, Cs (1.4), Th (1.4), P (1.4), Cu (1.4), Pb (1.3), La (1.2), Hf (1.1). Good agreement was observed between the RPD values obtained for the elements analysed in this study and those from the AR study. Despite the different elemental concentrations determined by the XRF method compared to the AR method, MIR spectroscopy was still capable of predicting elemental concentrations

Prediction of the concentration of chemical elements extracted by aqua regia in agricultural and grazing European soils using diffuse reflectance mid-infrared spectroscopy

Prediction of the concentration of chemical elements extracted by aqua regia in agricultural and grazing European soils using diffuse reflectance mid-infrared spectroscopy / J. M. Soriano-Disla... [et al.]. - Amsterdam : Elsevier, 2013. - il., 2 figuras e 3 tabelas ; 30 cm The aim of this study was to develop partial least squares (PLS) models to predict the concentrations of 45 elements in soils extracted by the aqua regia (AR) method using diffuse reflectance Fourier Transform mid-infrared (MIR; 4000–500 cm-1) spectroscopy. A total of 4130 soils from the GEMAS European soil sampling program (geochemical mapping of agricultural soils and grazing land of Europe) were selected. From the full soil set, 1000 samples were randomly selected to develop PLS models. Cross-validation was used for model training and the remaining 3130 samples used for model testing. According to the ratio of standard deviation to root mean square error (RPD) of the predictions, the elements were allocated into two main groups; Group 1 (successful calibrations, 30 elements), including those elements with RPD ? 1.5 (the coefficient of determination, R2, also provided): Ca (3.3, 0.91), Mg (2.5, 0.84), Al (2.4, 0.83), Fe (2.2, 0.79), Ga (2.1, 0.78), Co (2.1, 0.77), Ni (2.0, 0.77), Sc (2.1, 0.76), Ti (2.0, 0.75), Li (1.9, 0.73), Sr (1.9, 0.72), K (1.8, 0.70), Cr (1.8, 0.70), Th (1.8, 0.69), Be (1.7, 0.66), S (1.7, 0.66), B (1.6, 0.63), Rb (1.6, 0.62), V (1.6, 0.62), Y (1.6, 0.61), Zn (1.6, 0.60), Zr (1.6, 0.59), Nb (1.5, 0.58), Ce (1.5, 0.58), Cs (1.5, 0.58), Na (1.5, 0.57), In (1.5, 0.57), Bi (1.5, 0.56), Cu (1.5, 0.55), and Mn (1.5, 0.54); and Group 2 for 15 elements with RPD values lower than 1.5: As (1.4, 0.52), Ba (1.4, 0.52), La (1.4, 0.52), Tl (1.4, 0.51), P (1.4, 0.46), U (1.4, 0.45), Sb (1.3, 0.46), Mo (1.3, 0.43), Pb (1.3, 0.42), Se (1.3, 0.40), Cd (1.3, 0.40), Sn (1.3, 0.38), Hg (1.2, 0.33), Ag (1.2, 0.32) and W (1.1, 0.19). The success of the PLS models was found to be dependent on their relationships (directly or indirectly) with MIR-active soil components

Monitoring biological wastewater treatment processes: Recent advances in spectroscopy applications

Biological processes based on aerobic and anaerobic technologies have been continuously developed to wastewater treatment and are currently routinely employed to reduce the contaminants discharge levels in the environment. However, most methodologies commonly applied for monitoring key parameters are labor intensive, time-consuming and just provide a snapshot of the process. Thus, spectroscopy applications in biological processes are, nowadays, considered a rapid and effective alternative technology for real-time monitoring though still lacking implementation in full-scale plants. In this review, the application of spectroscopic techniques to aerobic and anaerobic systems is addressed focusing on UV--Vis, infrared, and fluorescence spectroscopy. Furthermore, chemometric techniques, valuable tools to extract the relevant data, are also referred. To that effect, a detailed analysis is performed for aerobic and anaerobic systems to summarize the findings that have been obtained since 2000. Future prospects for the application of spectroscopic techniques in biological wastewater treatment processes are further discussed.The authors thank the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, COMPETE 2020 (POCI-01-0145-FEDER-006684) and the project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020 - Programa Operacional Regional do Norte. The authors also acknowledge the financial support to Daniela P. Mesquita and Cristina Quintelas through the postdoctoral Grants (SFRH/BPD/82558/2011 and SFRH/BPD/101338/2014) provided by FCT - Portugal.info:eu-repo/semantics/publishedVersio

Assessment of cyanide contamination in soils with a handheld mid-infrared spectrometer

We examined the feasibility of using handheld mid-infrared (MIR) Fourier-Transform infrared (FT-IR) instrumentation for detecting and analysing cyanide (CN) contamination in field contaminated soils. Cyanide spiking experiments were first carried out, in the laboratory, to test the sensitivity of infrared Fourier transform (DRIFT) spectrometry to ferro- and ferricyanide compounds across a range of reference soils and minerals. Both benchtop and handheld diffuse reflectance infrared spectrometers were tested. Excellent results were obtained for the reference soils and minerals, with the MIR outperforming the near-infrared (NIR) range. Spectral peaks characteristic of the -C≡N group were observed near 2062 and 2118cm-1 in the MIR region for the ferro- and ferricyanide compounds spiked into soils/minerals, respectively. In the NIR region such peaks were observed near 4134 and 4220cm-1. Cyanide-contaminated samples were then collected in the field and analyzed with the two spectrometers to further test the applicability of the DRIFT technique for soils containing aged CN residues. The prediction of total CN in dry and ground contaminated soils using the handheld MIR instrument resulted in a coefficient of determination (R2) of 0.88-0.98 and root mean square error of the cross-validation (RMSE) of 21-49mgkg-1 for a CN range of 0-611mgkg-1. A major peak was observed in the MIR at about 2092cm-1 which was attributed to "Prussian Blue" (Fe4[Fe(CN)6]3·xH2O). These results demonstrate the potential of handheld DRIFT instrumentation as a promising alternative to the standard laboratory method to predict CN concentrations in contaminated field soils.José M. Soriano-Disla, Leslie J. Janik, Michael J. McLaughli

Evaluation of the performance of portable visible-infrared instruments for the prediction of soil properties

Abstract not availableJosé M. Soriano-Disla, Leslie J. Janik, Danielle J. Allen, Michael J. McLaughli

Effects of soil composition and preparation on the prediction of particle size distribution using mid-infrared spectroscopy and partial least-squares regression

Soil composition and preparation can affect prediction accuracy using diffuse reflectance mid-infrared Fourier transform spectroscopy (DRIFTS). In the present study, we evaluated the effect of soil composition, preparation and carbonate content on the accuracy of particle size distribution (PSD) predictions in four contrasting sets of soils, including calcareous soils, using partial least-squares regression (PLSR). The soils were scanned as <2- and <0.1-mm fine-ground samples. Regression calibrations were derived for individual soil sets, as well as a composite of the four sets. Predictions for clay and sand for the <2-mm composite calibration resulted in good accuracy (coefficient of determination R² = 0.78; ratio of the standard deviation of reference values to the prediction error (RPD) = 2.2), but were less accurate for clay in the calcareous soils (R² = 0.70–0.78; RPD = 1.8–1.1) and similarly accurate for sand (R² = 0.68–0.80; RPD = 1.7–2.2). Predictions for silt were poor. Accuracies improved by fine grinding (R² = 0.88, RPD = 2.9 for clay; R² = 0.84, RPD = 2.9 for sand). It was concluded that single, large and highly variable sets rather than site-specific calibrations could be used for the PSD predictions of specific soil sets. Changes in the PLSR loading weights, resulting from grinding, could be linked to an improved access of the infrared beam to the soil matrix by removal or dilution of surface coatings, resulting in a reduction of inter- and intraparticulate heterogeneity.Leslie J. Janik, José M. Soriano-Disla, Sean T. Forrester and Michael J. McLaughli

The transfer of heavy metals to barley plants from soils amended with sewage sludge with different heavy metal burdens

Purpose Our main aim objective was to evaluate the transfer of Cd, Cr, Cu, Ni, Pb and Zn to barley ( Hordeum vulgare ) grown in various soils previously amended with two sewage sludges containing different concentrations of heavy metals. This allowed us to examine the transfer of heavv metals to barley roots and shoots and the occurrence of restriction mechanisms as function of soil type and for different heavy metal concentration scenarios. Material and methods A greenhouse experiment was performed to evaluate the transfer of heavy metals to barley grown in 36 agricultural soils from different parts of Spain previously amended with a single dose (equivalent to 50 t dry weight ha − 1 ) of two sewage sludges with contrasting levels of heavy metals (common and spiked sludge: CS and SS). Results and discussion In soils amended with CS, heavy metals were transferred to roots in the order (mean values of the bio-concentration ratio in roots, BCF Roots ,inbrackets):Cu (2.4)~Ni (2.3)>Cd (2.1)>Zn (1.8)>Cr (0.7)~Pb (0.6); simi- lar values were found for the soils amended with SS. The mean values of the soil-to-shoot ratio were: Cd (0.44)~Zn (0.39)~Cu (0.39)>Cr (0.20)>Ni (0.09)>Pb (0.01) for CS- amended soils; Zn (0.24)>Cu (0.15)~Cd (0.14)>Ni (0.05)~ Cr (0.03)>Pb (0.006) for SS-amended soils. Heavy metals were transferred from roots to shoots in the following order (mean values of the ratio concentration of heavy metals in shoots to roots in brackets): Cr (0.33)>Zn (0.24)~Cd (0.22)> Cu (0.19)>Ni (0.04)>Pb (0.02) for CS-amended soils; Zn (0.14)>Cd (0.09)~Cu (0.08)>Cr (0.05)>Ni (0.02)~Pb (0.010) for SS-amended soils. Conclusions Soils weakly restricted the mobility of heavy metals to roots, plant physiology restricted the transfer of heavy metals from roots to shoots, observing further restriction at high heavy metal loadings, and the transfer of Cd, Cu and Zn from soils to shoots was greater than for Cr, Ni and Pb. Stepwise multiple linear regressions revealed that soils with high sand content allowed greater soil-plant transfer of Cr, Cu, Pb and Zn. For Cd and Ni, soils with low pH and soil organic C, respectively, posed the highest risk.José Martín Soriano-Disla, Ignacio Gómez, José Navarro-Pedreño, Manuel M. Jordá