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a Institute of Soil Science and Plant Cultivation, Pulawy, Poland
b USDA-ARS, Environmental Quality Laboratory, Beltsville, MD 20705
* Corresponding author (mccartyg{at}ba.ars.usda.gov)
Received for publication July 16, 2003. Rapid and nondestructive methods such as diffuse reflectance infrared spectroscopy provide potentially useful alternatives to time-consuming chemical methods of soil metal analysis. To assess the utility of near-infrared reflectance spectroscopy (NIRS) and diffuse mid-infrared reflectance spectroscopy (DRIFTS) for soil metal determination, 70 soil samples from the metal mining region of Tarnowskie Gory (Upper Silesia, Poland) were analyzed by both chemical and spectroscopic methods. Soils represented a wide range of pH (4.08.0), total carbon (5.173.2 g kg1), and textural classes (from sand to silty clay loam). Soils had various contents of metals (144500 mg kg1 for Zn, 186530 mg kg1 for Pb, and 0.1734 mg kg1 for Cd), ranging from natural background levels to high contents indicative of industrial contamination in the region. Soil samples were scanned at the wavelengths from 400 to 2498 nm (near-infrared region) and from 2500 to 25000 nm (mid-infrared region). Calibrations were developed using the one-out validation procedure under partial least squares (PLS) regression. Mid-infrared spectroscopy markedly outperformed NIRS. Iron, Cd, Cu, Ni, and Zn were successfully predicted using DRIFTS. The coefficients of determination (R2) between actual and predicted contents were 0.97, 0.94, 0.80, 0.99, and 0.96 for those metals, respectively. Only Pb content was predicted poorly. Calibrations using NIRS were less accurate. Root mean squared deviation (RMSD) values were from 1.27 (Pb) to 3.3 (Ni) times higher for NIRS than for DRIFTS. Results indicate that DRIFTS may be useful for accurate predictions of metals if samples originate from one region.
Abbreviations: DRIFTS, diffuse mid-infrared reflectance spectroscopy MIDIR, mid-infrared NIR, near-infrared NIRS, near-infrared reflectance spectroscopy NRMSD, normalized root mean squared deviation PLS, partial least squares RMSD, root mean squared deviation
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Y. Wu, J. Chen, J. Ji, P. Gong, Q. Liao, Q. Tian, and H. Ma A Mechanism Study of Reflectance Spectroscopy for Investigating Heavy Metals in Soils Soil Sci. Soc. Am. J., May 16, 2007; 71(3): 918 - 926. [Abstract] [Full Text] [PDF] |
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