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Article
Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties
Soil Science Society of America Journal
  • Cheng-Wen Chang, Iowa State University
  • David Laird, United States Department of Agriculture
  • Maurice J. Mausbach, United States Department of Agriculture
  • Charles R. Hurburgh, Jr., Iowa State University
Document Type
Article
Publication Date
3-1-2001
DOI
10.2136/sssaj2001.652480x
Abstract
A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of near-infrared reflectance spectroscopy (NIRS) to predict diverse soil properties. Near-infrared reflectance spectra, obtained from a Perstrop NIR Systems 6500 scanning monochromator (Foss NIRSystems, Silver Spring, MD), and 33 chemical, physical, and biochemical properties were studied for 802 soil samples collected from four Major Land Resource Areas (MLRAs). Calibrations were based on principal component regression (PCR) using the first derivatives of optical density [log(1/R)] for the 1300- to 2500-nm spectral range. Total C, total N, moisture, cation-exchange capacity (CEC), 1.5 MPa water, basal respiration rate, sand, silt, and Mehlich III extractable Ca were successfully predicted by NIRS (r 2 > 0.80). Some Mehlich III extractable metals (Fe, K, Mg, Mn) and exchangeable cations (Ca, Mg, and K), sum of exchangeable bases, exchangeable acidity, clay, potentially mineralizable N, total respiration rate, biomass C, and pH were also estimated by NIRS but with less accuracy (r 2 = 0.80∼0.50). The predicted results for aggregation (wt% > 2, 1, 0.5, 0.25 mm, and macroaggregation) were not reliable (r 2 = 0.46∼0.60). Mehlich III extractable Cu, P, and Zn, and exchangeable Na could not be predicted using the NIRS–PCR technique (r 2 < 0.50). The results indicate that NIRS can be used as a rapid analytical technique to simultaneously estimate several soil properties with acceptable accuracy in a very short time.
Comments

This article is from Soil Science Society of America Journal 65 (2001): 480–490, doi:10.2136/sssaj2001.652480x.

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Rights
Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
Language
en
File Format
application/pdf
Citation Information
Cheng-Wen Chang, David Laird, Maurice J. Mausbach and Charles R. Hurburgh. "Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties" Soil Science Society of America Journal Vol. 65 Iss. 2 (2001) p. 480 - 490
Available at: http://works.bepress.com/charles_hurburgh/59/